WO2001019013A1  Turbo detection of spacetime codes  Google Patents
Turbo detection of spacetime codes Download PDFInfo
 Publication number
 WO2001019013A1 WO2001019013A1 PCT/US2000/024641 US0024641W WO0119013A1 WO 2001019013 A1 WO2001019013 A1 WO 2001019013A1 US 0024641 W US0024641 W US 0024641W WO 0119013 A1 WO0119013 A1 WO 0119013A1
 Authority
 WO
 WIPO (PCT)
 Prior art keywords
 layer
 receiver
 antenna elements
 equalizer
 coupled
 Prior art date
Links
 239000010410 layers Substances 0 abstract claims description 142
 238000000034 methods Methods 0 claims description 43
 230000001702 transmitter Effects 0 claims description 26
 230000000694 effects Effects 0 abstract description 13
 230000035611 feeding Effects 0 claims description 10
 238000004891 communication Methods 0 abstract description 9
 230000001808 coupling Effects 0 claims description 9
 238000010168 coupling process Methods 0 claims description 9
 238000005859 coupling reaction Methods 0 claims description 9
 238000005562 fading Methods 0 description 27
 230000000051 modifying Effects 0 description 10
 230000003595 spectral Effects 0 description 9
 238000004088 simulation Methods 0 description 7
 238000004458 analytical methods Methods 0 description 6
 230000015654 memory Effects 0 description 6
 229920001276 Ammonium polyphosphate Polymers 0 description 5
 230000000875 corresponding Effects 0 description 5
 230000001965 increased Effects 0 description 5
 239000004793 Polystyrene Substances 0 description 4
 230000003044 adaptive Effects 0 description 4
 238000001914 filtration Methods 0 description 4
 210000002370 ICC Anatomy 0 description 3
 238000005516 engineering processes Methods 0 description 3
 230000001976 improved Effects 0 description 3
 239000011159 matrix materials Substances 0 description 3
 230000001629 suppression Effects 0 description 3
 230000001364 causal effects Effects 0 description 2
 239000000562 conjugates Substances 0 description 2
 230000003111 delayed Effects 0 description 2
 230000002708 enhancing Effects 0 description 2
 239000000203 mixtures Substances 0 description 2
 230000002829 reduced Effects 0 description 2
 230000004044 response Effects 0 description 2
 241001268392 Dalla Species 0 description 1
 229930013075 Decodine Natural products 0 description 1
 241000276438 Gadus morhua Species 0 description 1
 241001415961 Gaviidae Species 0 description 1
 238000007476 Maximum Likelihood Methods 0 description 1
 241000539716 Mea Species 0 description 1
 238000000342 Monte Carlo simulations Methods 0 description 1
 241000206607 Porphyra umbilicalis Species 0 description 1
 USNBCAPIYYPNGOUHFFFAOYSAN Verticillatine Chemical compound data:image/svg+xml;base64,<?xml version='1.0' encoding='iso-8859-1'?>
<svg version='1.1' baseProfile='full'
              xmlns='http://www.w3.org/2000/svg'
                      xmlns:rdkit='http://www.rdkit.org/xml'
                      xmlns:xlink='http://www.w3.org/1999/xlink'
                  xml:space='preserve'
width='300px' height='300px' >
<!-- END OF HEADER -->
<rect style='opacity:1.0;fill:#FFFFFF;stroke:none' width='300' height='300' x='0' y='0'> </rect>
<path class='bond-0' d='M 111.696,169.419 92.8788,197.537' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-0' d='M 114.497,177.4 101.325,197.082' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-30' d='M 111.696,169.419 83.5784,150.602' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-31' d='M 111.696,169.419 145.455,171.656' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-1' d='M 92.8788,197.537 81.0763,196.754' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-1' d='M 81.0763,196.754 69.2738,195.972' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-2' d='M 92.8788,197.537 107.821,227.891' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-3' d='M 107.821,227.891 100.299,239.131' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-3' d='M 100.299,239.131 92.7773,250.37' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-5' d='M 107.821,227.891 141.58,230.129' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-5' d='M 113.332,221.475 136.963,223.041' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-4' d='M 91.7793,261.648 97.8624,274.006' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-4' d='M 97.8624,274.006 103.946,286.364' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-6' d='M 141.58,230.129 160.397,202.011' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-7' d='M 160.397,202.011 145.455,171.656' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-7' d='M 152.085,200.446 141.625,179.198' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-8' d='M 145.455,171.656 175.81,156.714' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-9' d='M 175.81,156.714 189.381,161.332' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-9' d='M 189.381,161.332 202.952,165.95' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-16' d='M 175.81,156.714 169.233,123.527' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-10' d='M 208.957,173.252 211.686,187.026' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-10' d='M 211.686,187.026 214.416,200.801' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-32' d='M 212.727,163.333 223.01,154.328' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-32' d='M 223.01,154.328 233.293,145.324' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-11' d='M 214.416,200.801 246.445,211.699' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-12' d='M 246.445,211.699 271.899,189.41' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-13' d='M 271.899,189.41 265.322,156.222' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-14' d='M 265.322,156.222 233.293,145.324' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-15' d='M 233.293,145.324 226.716,112.136' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-33' d='M 226.716,112.136 194.687,101.237' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-17' d='M 169.233,123.527 194.687,101.237' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-18' d='M 194.687,101.237 189.283,85.6797' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-18' d='M 189.283,85.6797 183.88,70.1219' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-19' d='M 176.656,60.9586 165.23,53.3123' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-19' d='M 165.23,53.3123 153.805,45.666' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 157.008,46.7559 161.498,33.5605' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 161.498,33.5605 165.987,20.3651' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 150.602,44.5761 155.092,31.3807' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 155.092,31.3807 159.582,18.1854' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-21' d='M 153.805,45.666 120.046,43.4287' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-22' d='M 120.046,43.4287 89.6908,58.3706' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-23' d='M 89.6908,58.3706 70.8737,86.4881' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-24' d='M 70.8737,86.4881 39,99.6954' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-34' d='M 70.8737,86.4881 68.6364,120.247' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-34' d='M 77.29,91.9994 75.7238,115.631' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-25' d='M 39,99.6954 28.1014,131.725' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-25' d='M 43.7711,106.68 36.1421,129.1' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-26' d='M 28.1014,131.725 50.3906,157.178' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-27' d='M 50.3906,157.178 45.9007,170.374' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-27' d='M 45.9007,170.374 41.4108,183.569' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-28' d='M 50.3906,157.178 83.5784,150.602' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-28' d='M 54.0535,149.554 77.2849,144.951' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-29' d='M 83.5784,150.602 68.6364,120.247' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<text x='48.9658' y='200.938' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>HO</tspan></text>
<text x='83.7371' y='261.648' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='202.952' y='173.252' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#0000FF' ><tspan>N</tspan></text>
<text x='176.656' y='70.1219' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='159.437' y='19.2752' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='29.3381' y='194.847' style='font-size:11px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>OH</tspan></text>
</svg>
 data:image/svg+xml;base64,<?xml version='1.0' encoding='iso-8859-1'?>
<svg version='1.1' baseProfile='full'
              xmlns='http://www.w3.org/2000/svg'
                      xmlns:rdkit='http://www.rdkit.org/xml'
                      xmlns:xlink='http://www.w3.org/1999/xlink'
                  xml:space='preserve'
width='85px' height='85px' >
<!-- END OF HEADER -->
<rect style='opacity:1.0;fill:#FFFFFF;stroke:none' width='85' height='85' x='0' y='0'> </rect>
<path class='bond-0' d='M 31.1472,47.5021 25.8157,55.4687' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-0' d='M 31.9408,49.7633 28.2087,55.34' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-30' d='M 31.1472,47.5021 23.1805,42.1705' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-31' d='M 31.1472,47.5021 40.7122,48.136' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-1' d='M 25.8157,55.4687 22.4716,55.2471' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-1' d='M 22.4716,55.2471 19.1276,55.0254' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-2' d='M 25.8157,55.4687 30.0492,64.0692' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-3' d='M 30.0492,64.0692 27.9181,67.2537' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-3' d='M 27.9181,67.2537 25.7869,70.4382' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-5' d='M 30.0492,64.0692 39.6143,64.7031' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-5' d='M 31.6107,62.2513 38.3063,62.695' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-4' d='M 25.5041,73.6335 27.2277,77.1349' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-4' d='M 27.2277,77.1349 28.9512,80.6364' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-6' d='M 39.6143,64.7031 44.9458,56.7365' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-7' d='M 44.9458,56.7365 40.7122,48.136' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-7' d='M 42.5906,56.2931 39.6271,50.2727' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-8' d='M 40.7122,48.136 49.3127,43.9024' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-9' d='M 49.3127,43.9024 53.1579,45.2108' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-9' d='M 53.1579,45.2108 57.003,46.5191' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-16' d='M 49.3127,43.9024 47.4494,34.4992' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-10' d='M 58.7044,48.588 59.4778,52.4908' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-10' d='M 59.4778,52.4908 60.2511,56.3935' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-32' d='M 59.7726,45.7777 62.6861,43.2264' style='fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-32' d='M 62.6861,43.2264 65.5996,40.6751' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-11' d='M 60.2511,56.3935 69.3262,59.4815' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-12' d='M 69.3262,59.4815 76.5379,53.1662' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-13' d='M 76.5379,53.1662 74.6746,43.763' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-14' d='M 74.6746,43.763 65.5996,40.6751' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-15' d='M 65.5996,40.6751 63.7362,31.2719' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-33' d='M 63.7362,31.2719 54.6612,28.1839' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-17' d='M 47.4494,34.4992 54.6612,28.1839' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-18' d='M 54.6612,28.1839 53.1303,23.7759' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-18' d='M 53.1303,23.7759 51.5995,19.3679' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-19' d='M 49.5524,16.7716 46.3152,14.6051' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-19' d='M 46.3152,14.6051 43.078,12.4387' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 43.9855,12.7475 45.2576,9.0088' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 45.2576,9.0088 46.5298,5.2701' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 42.1705,12.1299 43.4426,8.39121' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-20' d='M 43.4426,8.39121 44.7148,4.65252' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-21' d='M 43.078,12.4387 33.5129,11.8048' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-22' d='M 33.5129,11.8048 24.9124,16.0383' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-23' d='M 24.9124,16.0383 19.5809,24.005' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-24' d='M 19.5809,24.005 10.55,27.747' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-34' d='M 19.5809,24.005 18.947,33.57' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-34' d='M 21.3988,25.5665 20.9551,32.262' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-25' d='M 10.55,27.747 7.46207,36.8221' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-25' d='M 11.9018,29.7259 9.74027,36.0784' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-26' d='M 7.46207,36.8221 13.7773,44.0339' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-27' d='M 13.7773,44.0339 12.5052,47.7726' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-27' d='M 12.5052,47.7726 11.233,51.5113' style='fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-28' d='M 13.7773,44.0339 23.1805,42.1705' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-28' d='M 14.8152,41.8737 21.3974,40.5694' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<path class='bond-29' d='M 23.1805,42.1705 18.947,33.57' style='fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1' />
<text x='13.3736' y='56.4324' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>HO</tspan></text>
<text x='23.2255' y='73.6335' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='57.003' y='48.588' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#0000FF' ><tspan>N</tspan></text>
<text x='49.5524' y='19.3679' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='44.6737' y='4.96131' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>O</tspan></text>
<text x='7.81245' y='54.7066' style='font-size:3px;font-style:normal;font-weight:normal;fill-opacity:1;stroke:none;font-family:sans-serif;text-anchor:start;fill:#FF0000' ><tspan>OH</tspan></text>
</svg>
 C12=C(O)C(OC)=CC=C2C(N2CCCCC2C2)CC2OC(=O)CCC2=CC=C(O)C1=C2 USNBCAPIYYPNGOUHFFFAOYSAN 0 description 1
 230000000996 additive Effects 0 description 1
 239000000654 additives Substances 0 description 1
 239000004452 animal feeding substances Substances 0 description 1
 230000015572 biosynthetic process Effects 0 description 1
 238000004422 calculation algorithm Methods 0 description 1
 230000015556 catabolic process Effects 0 description 1
 230000001413 cellular Effects 0 description 1
 230000001143 conditioned Effects 0 description 1
 238000010276 construction Methods 0 description 1
 230000004059 degradation Effects 0 description 1
 238000006731 degradation Methods 0 description 1
 230000001419 dependent Effects 0 description 1
 230000018109 developmental process Effects 0 description 1
 230000003467 diminishing Effects 0 description 1
 239000006185 dispersions Substances 0 description 1
 238000005755 formation Methods 0 description 1
 230000001939 inductive effects Effects 0 description 1
 239000010912 leaf Substances 0 description 1
 230000036629 mind Effects 0 description 1
 238000005457 optimization Methods 0 description 1
 230000036961 partial Effects 0 description 1
 239000011049 pearl Substances 0 description 1
 239000010932 platinum Substances 0 description 1
 238000007781 preprocessing Methods 0 description 1
 230000004224 protection Effects 0 description 1
 238000005070 sampling Methods 0 description 1
 230000011664 signaling Effects 0 description 1
 238000001228 spectrum Methods 0 description 1
 230000003068 static Effects 0 description 1
 230000001360 synchronised Effects 0 description 1
 230000002123 temporal effects Effects 0 description 1
 239000002699 waste material Substances 0 description 1
 230000002087 whitening Effects 0 description 1
Classifications

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L1/00—Arrangements for detecting or preventing errors in the information received
 H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
 H04L1/0045—Arrangements at the receiver end
 H04L1/0047—Decoding adapted to other signal detection operation
 H04L1/005—Iterative decoding, including iteration between signal detection and decoding operation

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L1/00—Arrangements for detecting or preventing errors in the information received
 H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
 H04L1/0056—Systems characterized by the type of code used
 H04L1/0064—Concatenated codes
 H04L1/0066—Parallel concatenated codes

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L1/00—Arrangements for detecting or preventing errors in the information received
 H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
 H04L1/0056—Systems characterized by the type of code used
 H04L1/0071—Use of interleaving

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L1/00—Arrangements for detecting or preventing errors in the information received
 H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
 H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
 H04L1/0618—Spacetime coding

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L25/00—Baseband systems
 H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
 H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
 H04L25/03006—Arrangements for removing intersymbol interference
 H04L25/03171—Arrangements involving maximum a posteriori probability [MAP] detection

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L25/00—Baseband systems
 H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
 H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
 H04L25/03006—Arrangements for removing intersymbol interference
 H04L25/03178—Arrangements involving sequence estimation techniques
 H04L25/03305—Joint sequence estimation and interference removal

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L25/00—Baseband systems
 H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
 H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
 H04L25/03006—Arrangements for removing intersymbol interference
 H04L25/03178—Arrangements involving sequence estimation techniques
 H04L25/03312—Arrangements specific to the provision of output signals
 H04L25/03324—Provision of tentative decisions

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L25/00—Baseband systems
 H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
 H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
 H04L25/03891—Spatial equalizers

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04B—TRANSMISSION
 H04B7/00—Radio transmission systems, i.e. using radiation field
 H04B7/02—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas
 H04B7/04—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
 H04B7/06—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
 H04B7/0613—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
 H04B7/0667—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of delayed versions of same signal
 H04B7/0669—Diversity systems; Multiantenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of delayed versions of same signal using different channel coding between antennas
Abstract
Description
1/19013 ^{rL} '
TURBO DETECTION OF SPACETIME CODES
RELATED APPLICATIONS
This document claims priority to and incorporates by reference copending provisional USSN 60 / 152,982 entitled "Turbo SpaceTime Processing to Improve Wireless Channel Capacity" filed on September 9, 1999.
FIELD OF INVENTION
The present invention relates to systems and processes for radio communications using multipleelement antenna array technology.
BACKGROUND
Turbo processing and spacetime equalization are terms that comprehend several conventional ways to increase wireless channel capacity. Generally, turbo coding and/or processing refers to techniques aimed at approaching the Shannon limit in a channel, while spacetime processing refers to techniques for processing signals from multielement antenna arrays to exploit the multipath nature of fading wireless environments.
European patent application no. EP 817 401 A2 published July 1 , 1998 in the name of Foschini discloses the use of a number of processing layers for space time processing of signals from multiplereceiver antenna elements. There, the transmitter feeds a number of transmitter antenna elements by cyclically apportioning segments of the modulated encoded stream of data to transmitter antenna elements. At the receiver, a number of receiver antenna elements are coupled to a number of processing layers, in order to perform the spacetime processing. Signal components received during respective periods of time over a plurality of the receive antenna elements are formed into respective space and time relationships in which space is associated with respective transmitter antenna elements. Preprocessing occurs so that a collection of signal components having the same spacetime relationship
l 1/19013 r^ ^{i /}u
forms a signal vector such that particular decoded signal contributions can be subtracted from the signal vector while particular undecoded contributions can be nulled out of the signal vector. The resulting vector is then supplied to a decoder for decoding to reform the data stream. Such conventional systems and techniques are further described in documents referred to in the "Detailed Description" section of this document.
SUMMARY OF THE INVENTION
Systems and processes according to the present invention employ a number of transmitter antenna elements and a number of receiver antenna elements coupled to multiple spacetime processing layers in the receiver. In the present invention, however, portions of the information stream being communicated can be interleaved among transmitter antenna elements such as on a random or pseudo random basis; among other things, such interleaving decreases decision errors in the spacetime equalization process. Furthermore, each processing layer preferably includes turbo processing in order to feed soft decisions about information being processed back to the equalizers. Moreover, spacetime equalization processes according to the present invention preferably seek to maximize signal to noise ratio rather than zero forcing, as well as reduce multipath effects and intersymbol interference. A preferred process uses minimum mean square error processing which allows the Shannon limit actually to be achieved. Furthermore, systems and processes according to the present invention preferably allow selection of the number and identity of receiver antenna elements to which the receiver may be coupled in order to optimize performance.
According to one embodiment of the invention, an information source is coupled to provide a plurality of data streams to a plurality of transmit antennas, via, for each stream, an encoder, interleaver and symbol mapper. On the receiver side, a plurality of M receiver elements are coupled to a plurality of processing layers. The number of receiver antenna elements M is preferably greater than or equal to the number N of transmit antenna elements, since equalization according to the present invention does not require an extra degree of freedom. The M receiver antenna elements are coupled to the first processing layer by coupling to a spacetime equalizer which preferably applies minimum mean square error processing in order to maximize signal to noise ratio. The output of the equalizer is applied to a deinterleaver, after which the deinterleaved stream is supplied to a decoder in the layer. Output of the decoder is provided for output common with the output from the other decoders in the other layers. Preferably, each layer also includes an interleaver which receives output from the decoder and deinterleaver and supplies its interleaved output back to the equalizer in the layer in order to provide soft decision making to the equalizer. In successive processing layers, output from the decoder of the preceding layer is combined with information from the interference canceler of the layer preceding the preceding layer (except the second layer, which receives signals from an interference canceller which is coupled to the decoder of the first layer and to the receive antenna elements).
According to an alternate embodiment, the deinterleaver, interleaver and decoder are shared among layers, so that the equalizer of each layer outputs to a deinterleaver common to all layers. The output of the deinterleaver may then be coupled to a decoder which again is common to all layers. An interleaver may be provided which receives output from the deinterleaver and the decoder and applies it to each equalizer for soft decisions to be applied to the equalizers.
Accordingly, components for deinterleaving, decoding and reinterleaving may be functionally located in each layer, or common to the layers. In the first case, each layer below the first layer processes signals from an interference canceller which receives signals from a decoder in the preceding layer and from the antenna elements (in the case of the second layer) or the interference canceller in the nextpreceding layer (in the case of other layers). In the second case, each layer below the first processes signals from an interference canceller which receives signals from the equalizer in the preceding layer and from the antenna elements (in the case of the second layer) or the interference canceller in the next preceding layer (in the case of other layers). Such turbo processing architectures can be used in connection with layered spacetime equalization which relies on zero forcing rather than minimum square error processing. They can also be used in multi array systems in which the data streams are periodically cycled rather than interleaved.
It is accordingly an object of the present invention to provide improved layer spacetime processing for communication systems which employ turbo processing techniques in order, among other things, to reduce decision errors.
It is an additional object of the present invention to provide layered spacetime processing for communication systems which seeks to maximize signal to noise ratio, thereby better addressing the Shannon limit, and which also addresses mulitpath effects and / or intersymbol interference.
It is an additional object of the present invention to provide processing for communication systems in which data streams may be interleaved rather than periodically cycled among transmit antenna elements, in order, among other things, to reduce decision errors.
It is an additional object of the present invention to provide layered spacetime processing for communication systems in which a receiver can select a set of antenna elements, including their number and / or identity, from among a larger group of antenna elements in order to optimize performance of the system.
Other objects, features, and advantages of present invention will become apparent with respect to the remainder of this document. BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1(a) is a schematic diagram showing a first embodiment of communications systems according to the present invention.
Fig. 1(b) is a schematic diagram showing a second embodiment of communications systems according to the present invention.
Fig. 2 is schematic diagram showing one form of spacetime processing according to the present invention. Figs. 3(a) and 3(b) are diagrams which compare performance between two coding schemes according to the present invention.
Fig. 4 is a diagram which shows different capacity bounds for processing according to the present invention over a flat Rayleigh fading channel.
Fig. 5 is a diagram which shows simulation results for a system according to the first embodiment of the present invention with two transmit and two receive antenna elements.
Fig. 6 is a diagram which shows simulation results for a system according to the first embodiment of the present invention with two transmit and four receive antenna elements.
Fig. 7 is a diagram which shows simulation results for a system according to the first embodiment of the present invention with two, four and eight receive antenna elements, using soft decisions and six turbo iterations.
Fig. 8 is a diagram which shows simulation results for a system according to the second embodiment of the present invention with two, four and eight receive antenna elements, using soft decisions and two turbo iterations.
Figs. 9(a) and 9(b) are diagrams which show simulated performance of the first embodiment of the present invention using soft decisions and four antenna elements for typical urban and hilly terrain profiles.
DETAILED DESCRIPTION
The documents and references cited in the following disclosure are incorporated herein by this reference.
Abstract — By deriving a generalized Shannon capacity formula The basic information theory results reported by Foschini and for multipleinput, multipleoutput Rayleigh fading channels, and Gans [ 1 ] have promised extremely high spectral efficiencies by suggesting a layered spacetime architecture concept that attains a tight lower bound on the capacity achievable, Foschini has possible through multipleelement antenna array technology. shown a potential enormous increase in the information capacity In high scatteπng wireless environments (e g., troposcatter, of a wireless system employing multipleelement antenna arrays cellular, and indoor radio), the use of multiple spatially sepaat both the transmitter and receiver. The layered spacetime rated and/or differently polaπzed antennas at the receiver has architecture allows signal processing complexity to grow linearly, been very effective in providing diversity agamst fading [2], rather than exponentially, with the promised capacity increase. [3]. Receiver diversity techniques also create signal processing This paper includes two important contributions: First, we show that Foschini 's lower bound is, in fact, the Shannon bound when the opportunities for mterference suppression and equalization output signaltonoise ratio (SNR) of the spacetime processing in (e g., [4][6]) However, using multiple antennas at either the each layer is represented by the corresponding "matched filter" transmitter or the receiver does not enable a significant gain in bound. This proves the optimality of the layered spacetime the possible channel capacity According to [ 1 ], the Shannon concept. Second, we present an embodiment of this concept capacity for a system with 1 transmit and N receive antennas for a coded system operating at a low average SNR and in the presence of possible intersymbol interference. This embodiment scales only logarithmically with N. as .V — <• oc. For a system utilizes the already advanced spacetime filtering, coding and using .V transmit and 1 receive antennas, asymptotically turbo processing techniques to provide yet a practical solution there is no additional capacity to be gained, assuming that the to the processing needed. Performance results are provided for transmit power is divided equally among the N antennas. quasistatic Rayleigh fading channels with no channel estimation Foschini and Gans [1 ] have shown that the asymptotic errors. We see for the first time that the Shannon capacity for wireless communications can be both increased by N times (where capacity of multipleinput, multipleoutput (MIMO) Rayleigh N is the number of the antenna elements at the transmitter fading channels grows, instead, linearly with .V when N and receiver) and achieved within about 3 dB in average SNR, antennas are used at both the transmitter and the receiver. about 2 dB of which is a loss due to the practical coding scheme Furthermore, in [7], Foschini suggested a layered spacetime we assume — the layered spacetime processing itself is nearly architecture concept that can attain a tight lower bound on the informationlossless! capacity achievable. In this layered spacetime architecture,
Index Terms — Equalization, interference suppression, space .V information bit streams are transmitted simultaneously time processing, turbo processing. (in the same frequency band) using .V diversity antennas. The receiver uses another N diversity antennas to decouple
I INTRODUCTION and detect the .V transmitted signals, one signal at a time. The decoupling process in each of the ,V processing "layers"
T URBO" and "spacetime" are two of the most explored involves a combination of nulling out the mterference from concepts in modemday communication theory and yet undetected signals ( ^{r} diversity antennas can null up to wireless research From a communication theoπst's viewpoint, iV — 1 mterferers, regardless of the anglesofarπval [5]) and "'turbo" coding/processing is a way to approach the Shannon canceling out the interference from already detected signals. limit on channel capacity, while "spacetime" processing is One very significant aspect of this architecture is that it a way to increase the possible capacity by exploiting the πch allows an N dimensional signal processing problem — which multipath nature of fading wireless environments We will see would otherwise be solvable only through multiuser detection through a specific embodiment in this paper that combining the methods [8] with complexity (m is the signal constellation two concepts provides even a practical way to both increase size) — to be solved with only N similar 1D processing steps. and approach the possible wireless channel capacity. Namely, the processing complexity grows only linearly with
With growing bit rate demand in wireless communications, the promised capacity it is especially important to use the spectral resource efficiently
This paper includes two important contributions. First, we show that Foschini's lower bound is. in fact, the Shannon bound when the output SNR of the spacetime processing in
Paper approved bv K B Letaief. the Editor for Wireless Svstems ot the IEEE Communications Society Manuscπpt received September 15 1999 revised Deeach layer is represented by the corresponding "matched filter" cember i 1999 This paper was presented at the IEEE International Coπterence bound [6], i e . the maximum SNR achievable in a hypothetical on Communications New Orleans. LA June 2000
The author is with the Home Wireless Networks Norcross GA 30071 USA situation where the array processing weights to suppress the (email lek@homewιretess com) remaining interference in each layer are chosen to maximize the
Publisher Item Identifier S 00906778(00)071 1 1 7 output signaltointerferenceplusnoise ratio and any possible intersymbol interference ( ISI) is assumed to be completely able using 1D processing and coding techniques that are aleliminated by some means ot equalization The 'matched filter" ready practical and "legacycompatible" with the EDGE stanbound has been shown to be approachable using minimum dard, e g , the use of bitinterleaved 8ary phaseshift keying meansquare error (MMSE) spacetime filtering techniques (8PS ) with rate 1/3 convolutional coding and an equalizer [6] ' By showing the equivalence ot the generalized Foschim's w ith a similar length and structure bound and the Shannon bound, we essentially prove the A slightly different lavered spacetime approach based on optimahtv of the layered spacetime concept spacetime coding [23]. [24j has been studied in [25]. Although
Second, we present an embodiment of Foschini 's lavered it is difficult to make a general compaπson. we will see later that spacetime concept for a coded system operating at a low avour coded layered spacetime approach does by far outperform erage SNR and in the presence ot unavoidable ISI Previously, the results reported in [25] for .V = 4 and N = 8. On the a different embodiment has been provided in [9] for an uncoded other hand, for N = 2, spacetime coded quaternary phaseshift system with vaπable signal constellation sizes, operatmg at keying (QPSK) without layered processing appears to be the a high average SNR without ISI. Adding coding redundancy best known technique tor achieving a spectral efficiency of 2 might, at first, seem conflicting with the desire to increase the bps Hz channel bit rate Our justification is as follows First, we seek This paper is organized as follows Section II provides a to enhance the channel capacity from a system perspective. bπef review of Foschim's layered spacetime concept. Section We use "noise^{"} in SNR to represent all system impairments, III descπbes the two coded layered spacetime architectures including thermal noise and multiuser interference. The ability and presents a capacity analysis which reveals the equivalence to operate at low SNR's means that more users per unit area of a generalized Foschim's lower bound formula and the true can occupy the same bandwidth simultaneously Second, we capacity bound Section IV provides details on the array proanticipate the use of adaptiverate coding schemes to permit cessing, equalization, and iterative MAP techniques. Section V different degrees ot error protection according to the channel presents performance results. A summary and conclusions are SNR's. Incremental redundancy transmission [ 10], currently given in Section VI being considered for the Enhance Data Services for GSM Evolution (EDGE, GSM stands for Global System for Mobile II. BACKGROUND THEORY Communications) standard, is an efficient way to implement We bπefly review the theory behind Foschim's layered adaptive code rates without requiπng channel SNR monitoring. spacetime concept. The generalized Shannon capacity for a With such adaptiverate coding, the system does not "waste" MIMO Rayleigh fading system with N transmit and M receive spectral resources under good channel conditions. antennas is given in [ 1 ] as
Meanwhile, the iterative processing pπnciple used in turbo and seπal concatenated coding [ 1 1 ][ 15] has been successfully C = log_{2} [det (/ + ##')] (1) applied to a wide vaπety of joint detection and decoding problems. One such application is the socalled "turbo equalization" where H is an M x N matπx. the (i. j)ιh element of which [ 16]— [ 19], where successive maximum a posteriori (MAP) is the normalized channel transfer function of the transmission processing is performed by the equalizer and channel decoder link between the _{7}th transmit antenna and the nh receive anto provide a priori information about the transmit sequence tenna. / is the M x M identity matπx. p is the average SNR to one another. Similar to the layered spacetime concept, per receive antenna, and det( )and superscript t denote deterturbo processing allows a multidimensional (fu'odimensional minant and con_{j}ugate transpose. It is assumed that the transmit in this case) problem to be optimally solved with successive power is equally divided among the N transmit antennas. The 1 D processing steps without much performance penalty. In normalization of the channel transfer function is done such that this paper, we apply the turbo pπnciple to layered spacetime the average (over Rayleigh fading) of its squared magnitude is processing in order to prevent decision errors produced in each equal to unity layer from catastrophically affecting the signal detection in The lower bound on capacity is provided in [ 1] as subsequent layers.
We consider two possible coded layered spacetime strucC > ∑ log_{2} [l +  χ^{2} _{2k}] = C_{F} (2) tures: one applying coding across the multiple signal processing k  \l + \ layers, and the other assuming independent coding within each layer. Similar to [ 1 ]. we assume a quasistatic random Rayleigh where
is a chisquared random vaπable with 2k degrees of channel model, where the channel characteπstics are stationary freedom For M = within each data block, but statistically independent between different data blocks, different antennas, and. in the case of disC_{F} = ∑ log, [l t ],] (3) persive multipath channels, different paths The system is assumed to have similar ISI situations as in EDGE and GSM,Since χ _{k} represents a fading channel with a diversity order where multipath dispersions may last up to several symbol peot k. the lowerbound capacity in ( 3) can be viewed as the sum riods [20] We show that nearcapacity performance is achiev ot the capacities of V independent channels with increasing di¬
^{1} In a flat fading case MMSE arrav processing achieves exactlv the matched versity orders trom 1 to V This suggests a layered spacetime tiller bound pertorniαncc approach [7] for detecting the V transmitted signals as follows In the first layer, the receiver detects a first transmitted signal H,_{j}(f) is the channel transfer function (not normalized) of the by nulling out mterference from ,V  1 other transmitted signals transmission link between the zth transmit antenna and the through array processing Assuming a "zero forcing ' (ZF) con_{7}th receive antenna, and superscπpts * and T denote complex straint, one receive antenna is needed to completely correlate conjugate and transpose Note in (7) and (8) that we consider and subtract each interference [5] Thus, the overall process of the folded spectra H_{t]}(f  {m/T)) and «_,(/  (m/T)) of nulling Λ — 1 interferences leaves the receiver with .V — (Λ^{*} — the channel transfer function and noise power density, where 1 ) = 1 degree of freedom to provide diversity for detecting the m — —J. . J (J is finite because the signal sources are first signal, I e , a diversity order of 1 (or simply no diversity) assumed to be bandlimited) This is to take into account the Once detected, the first signal is subtracted out from the received effect of excess bandwidth and symbolrate sampling when signals on all N antennas the frequency selectivity of the channel is not symmetπcal
In the second layer, the receiver performs similar mterference around the Nyquist band edges. Even though we assume white nulling to detect a second transmitted signal. This time, since Gaussian noise, the noise power density near and outside the there are only .V  2 remaining mterferences. the receiver afNyquist band edges actually attenuates with the receive filter fords a diversity order of 2. The detected signal is again subtransfer function. From our expeπment (assuming a squareroot tracted out from the received signals provided by the first layer Nyquist filter with a 50% rolloff factor), the computed capacity
Repeating the above mterference nulling/canceling step can be underestimated by as much as 0.5 dB if this attenuation through .V layers, we see that the receiver affords an increasing is not taken into account. order of diversity from 1 to N. If the capacities achieved in individual layers can be combined in some manner, then the in. CODED LAYERED SPACETIME ARCHITECTURES layered spacetime approach just mentioned will achieve the A Basic Concepts capacity lower bound expressed in (3) We will explore two capacity combining possibilities in the next section. We consider two coded layered spacetime approaches as
Note that the capacity and capacity low bound given in shown in Fig. 1(a) and (b). In the first approach, named "LSTI" ( 1H3) are actually frequencydependent. We here provide an (LST stands for "layered spacetime"), the coded mformation explicit capacity formula for bandlimited, frequencyselective bits are interleaved across the N parallel data streams xι, channels (some vanables are redefined to be consistent with x_{2}, , x,v, where x, denotes a sequence of complexvalued, later analytical development). transmit data symbols (e.g., 8PS symbols). The receiver first decouples the N data streams through interference nulling/can¬
C = (log_{2}[det(»«^{1} )]) (4) cellation, as descnbed in Section II, then demterleaves and decodes all the JV data streams as one information block. In where, as shown in equations (5)(8) at the bottom of the page. the second approach, "LSTII," the information is first divided Si is the frequencydomain correlation matπx of the signals into N uncoded bit sequences m, u_{2}, . . " T, each of which on M receive antennas, N_{;} (/) is the noise power density at is independently encoded, interleaved, and symbolmapped to frequency / on the th receive antenna. T is the symbol peπod. generate one of the N parallel data streams At the receiver, the
/^{■}( 1/2T)
< > = T / [ } df (5)
Λ/ Transmit
Fig I Coded layered spacetime architecture ( a) LSTI and (b) LSTII
.V data streams are decoupled and independently deinterleaved cient condition for nulling Λ^{'}  1 interference), we only consider and decoded. The output of LSTII produces Λ^{r} information Λ/ = N in this study blocks at a rate of l/.V times the output rate of LSTI. Similar to [9], the underlying assumption of our layered
In Fig. 1(a) and (b), "spacetime equalizer" refers to a comspacetime architecture is that the receiver can order the detecbined array processing (for interference nulling) and equalizations of iV data streams such that an undetected layer always tion function. Instead of the ZF cπteπon, we assume that the ophas the strongest received SNR In LSTI. the spacetime timization of the antenna equalizer weights is based on a MMSE equalizer in each layer must provide data decisions x _{\{l)} (Λ decπteπon. which in general provides better performance than a notes the permutation due to layer ordeπng) to the interference ZF approach. Foschini [7] has also indicated a potential percanceller, since decoding cannot be done until all the layers formance benefit of using MMSE (or "maximum SNR") rather are processed In LSTII. the interference cancellation in each than ZF in a layered spacetime architecture. Although we show laver can use more reliable data decisions u _{\(l )} provided by \l receive antennas in Fig. 1 (a) and ( b) (Λ/ > V is the suffi the decoder Thus. LSTI ts more prone to decision errors than LSTII In order to minimize the effects of decision errors, and also to improve the joint detection/decoding performance in general, we assume the use of turbo processing m our layered spacetime architecture As shown in Fig 1(a) and (b), the spacetime equalizers and the decoders provide extrinsic soft information to one another by subtracting the received soft information from the newly computed soft information. Details on MMSE spacetime equalization and turbo processing will be provided m the Section IV
B Capacity Analysis Fig 2 Spacetime DDFSE with MAP processing
Without getting into the detail of all the processing functions, we first discuss the general differences between the two coded Note that ( 1 1) is an explicit formula similar to (4), it shows the layered spacetime approaches. In particular, we are most interfrequency dependence of the output SNR and the mtegration of ested in the capaciry combining aspects of the two approaches capacity over the signal bandwidth. Also, we assume that the
Let SNR_{f}c denote the output SNR of the array processing in kt layer has k — 1 interferences. the fcth layer. First, we note that, in LSTII, the capacity of each In the process of analyzing the meaning of ( 1 1 ), we discovprocessing layer is bounded by the spectral efficiency R of the ered an identical relationship between ( 11 ) and (4) regardless of modulation and coding in each layer, e g , R = 1 for 8PS how the layers are ordered We show the proof in the Appendix with rate 1/3 coding Thus, the total capacity of LSTII is given (this proof is valid even when M ≠ N). Thus, Foschim's lower by (similar to ( l)(3), we wπte capacity without showing the bound (3) is actuallv the true Shannon capacity bound when frequency dependence) the output SNR of the spacetime processing in each layer is represented by the corresponding ' matched filter" bound. This proves the optima ty of the layered spacetime concept.
CLSTII = ∑ mιn{Λ, log_{2}[l + SNR*] } (9)
The capaciry analysis presented above is based on the as¬
*=ι sumption of perfect layer detection, I e., no decision errors af¬
Without layer ordeπng, it is most likely that the overall perforfecting the detection in subsequent layers In reality, LSTI is mance of LSTII will be largely influenced by the error probamore prone to decision errors than LSTII and layer ordeπng bility of the first processing layer with a diversity order of only becomes important for both schemes Our simulation results in 1 In contrast, our simulation results in Section V will show that Section V will demonstrate how decision errors affect the actual LSTII with layer ordeπng can actually achieve a diversity order performance of the two coded layered spacetime approaches. of approximately N
Since coding is performed across all the processing layers in IV. SIGNAL PROCESSING FUNCTIONS LSTI, the achieved SNR in each layer will contribute to the overall layer processing performance. As Foschini [7] indicated, A SpaceTime Equalization such a coding scheme should be able to achieve the capacity We consider combined array processing and equalization m lower bound in (3). Here, we provide a generalized formula of order to cope with dispersive channels A spacetime equalizer, Foschi 's lower bound by removing the ZF constraint and inconsisting of a spatial/temporal whitening filter, followed by stead using SNR*. as the generalized output SNR. a decisionfeedback equalizer (DFE) or maximumlikelihood sequence estimator, can suppress both ISI and dispersive
C_{F} = ∑ log_{2}[l + SNR_{fc}] ( 10) interference [6]. The spacetime equalizer used in this study is shown in Fig 2 It consists of a linear feedforward filter W_{j}(f), j = 1, M, on each diversity branch, a combiner,
Reference [6] provides output SNR formulas for different symbolrate sampler, softinput, softoutput (SISO) MAP types of optimum spacetime processors. Here, it is of great sequence estimator, and synchronous iinear feedback filter interest to express the capacity lower bound using the best perE ' (f). The feedforward filters { W_{j} (f) \ are shown as conformance achievable In the following equation, we represent tinuoustime filters, but they can be implemented in practice SNR*. in ( 10) by the "matched filter" boundthe maximum using fractionallyspaced tapped delay lines The combmed achievable SNR by any spacetime processing receiver: use ot a sequence estimator and feedback filter after diversity combining is similar to the structure ot a delayed decisionfeedc_{F} stF = ( ∑ iog_{3}[ι + r_{k} f)\ (I D back sequence estimator (DDFSE) [27] Thus, we refer to the =ι spacetime equalizer in Fig 2 as a spacetime DDFSE.^{"} A "spacetime DFE" is a structure where the sequence estimator where I (/) is the "matched filter" bound^{2} given by equation is replaced by a memoryless hard sheer ( 15) in Section IVA (simply a rewπting of the result in [6])
It has been shown in [20) that a spacetime DDFSE with a
^{:}Note thai the matched tilter bound usually refers to the integrated SNR sequence estimator memory of μ and a feedback filter of length (l\ ( / )) over the signal bandwidth (e g , [61) However in the capacity context La — μ can be optimized in a MMSE manner as if it was a we assume the beM possible way lo exploit the SNR s in all frequency components spacetime DFE with a feedback filter ot length Lo In fact. numencai results in [6] showed that an optimum spacetime TABLE I DFE (with unconstrained filter lengths and no feedback decision GSM TYPICAL LRBAN (TU) CHANNEL MODEL errors) can perform within only 12 dB of the ideal "matched filter" bound performance Thus, in order to have a practical Path Delay ( μs) 0 0 0 2 0 5 1 6 2 3 5 0 receiver structure for layered spacetime processing, we consider a spacetime DDFSE with a minimum sequence estimator Path Power (dB) 3 0 00 2 0 6 0 8 0 10 0 memory, I e , μ = 1 The sequence estimator is used only to provide a trellis structure needed for turbo processing, and presumably more reliable feedback decisions than the sheer used TABLE II GSM HILLY TERRAIN (HT) CHANNEL MODEL in a spacetime DFE. Details on MAP processing will be given in Section IVB
We first provide a bπef review of the spacetime filtering Path Delay (μs) 0 0 0 2 0 4 0 6 15 0 17 2 theory Based on the spacetime DFE equivalent model de scπbed above, the MMSE solution tor the feedforward filters Path Power (dB) 0 0 2 0 1 0 7 0 6 0 12 0 {W (/) } with unconstrained length can be given using the results of [6] (see also [28]) forward filter on each branch should have the following causal and anticausal lengths to achieve nearoptimum performance
W = X^HKl + B(f)) = X^Hl } +?!^{{}P_{t}. (12) i + 1 / L_{c} K(N  l)(p_{dB}/W) L » K + KN(_{PdB}/ W) ( 16) where where K is the channel memory, .V is used here to indicate the total number of signals, including the desired and mterfer¬
( 13) ence signals, and p _{B} is the average SNR in decibels. In our case, K = 5, and assume for example that the system has four w έ w_{v} f transmit and four receive antennas (N = 4) and the operating
 f) range of average SNR is around 5 dB ( as = 5) The required filter length, including the center tap, will be Lc + £ ι + l ~
Wy. I f + W^{'}vz / + ( 14) 23.5. This is a highly impractical number, considering that four such filters are required, one per each receive antenna. Fur(15) thermore, as mentioned earlier, the optimum feedforward filters should be implemented using fractionallyspaced tapped delay
In the above equations, we assume that there are a total of k lines. If a T/2spaced filters are used, the total number of taps signal sources and we use H_{k} to indicate the channel vector will be doubled. Such a spacetime system with about 200 coefficients would be nearly impossible to compute in any radio link design.
Faced with such impracticality of an ideal signal processing arrangement, we proceed to consider a suboptimum option. First, we will use svmbolspaced instead of fractionallyspaced feedforward filters In order to avoid significant performance penalties, a channel estimationbased timing recovery algo πthm descπbed in [29] will be used to optimize the symbol timing and the decision delay of the center tap relative to the measured channel impulse response In pπnciple, such timing optimization also allows the DFE to use a feedforward filter with a shorter span than the channel memory while achieving a reasonable performance [29], [30] After expeπmenting with a number of significantly reduced filter length options, we decided on the following suboptimum spacetime equalizer structure The feedforward filter on each branch has a total ot nine symbolspaced taps, which are positioned such that L_{c} = L = 4 The feedback filter has a length of 8. i e .
L _{0}  0 with the MAP processor memory μ = 1 included bles I and II). and assuming the same symbol rate of 270 833 ( in order to completely cancel postcursor ISI. B must be at kbaud (T = i 692 μs) with Nyquist filteπng (partial response least as large as the channel memory plus the number of causal signaling is used in EDGE and GSM) the ISI lasts up to five taps in the feedforward filter) The method m [29] is used to symbol periods for the hilly terrain (HT) profile in Table II Acoptimize the symbol timing and the decision delay of the center cording to the empirical filter length formulas in [6], the feed tap as descπbed above Direct matπx inversion is used to set all the filter coefficients in a standard MMSE linear processing effect in bitmterleaved coded modulation [36][38]. However, fashion [4], [26], [31 ], assuming perfect channel estimation this effect can be overcome by iterative decoding [38], which is implicit in our turbo spacetime processing approach.B Turbo Processing As noted earlier, in LSTI. the spacetime equalizer in each layer must provide immediate data decisions to be used for mter¬
The turbo processing technique used in this study is also ference cancellation. Since these decisions are not "protected" based on a standard approach — the reader is referred to the by coding, they are prone to errors. In this study, we explore πch literature [ 1 1 ][ 19], [21][22], [32][35] for a thorough a soft decision technique to minimize the effect of decision ertreatment of this subject. The spacetime equalizer and the rors The optimum soft decision can be computed by averaging decoder both performs SISO sequence estimation to compute all the possible transmit symbols weighted by their APP's [39] the a posteriori probability ( PP) of the transmit data symbols. This sequence estimation is done using the BahlCockeJe lmekRaviv (BCJR) forward backward algorithm. In the Xk = ∑ sP[x_{k} = x\y] (18) following, we descπbe the basic principle of the iterative i€.Y detection/decoding process. where X includes all the complexvalued 8PSK constellation
Using the BCJR algomhm. the MAP processor in the points. Since P{x_{k} = x\y] can be obtained along with the comspacetime equalizer with τn^{μ} states (m is the signal constelputation of the APP P[c \y], this soft decision approach can be lation size, e.g., = 8 for 8PSK, and μ = 1 in our case) implemented with nearly no additional cost in complexity Simcomputes the APP P[c,tj/] of the kt coded bit c based on ilarly, we apply the same technique to compute soft decision the observation y, where y is the equalizer output sequence outputs in LSTII. corresponding to all the data symbols in a received block (see Fig. 2), and the a priori information provided by the decoder (this is not available in the first "turbo" iteration). The logarithm V PERFORMANCE RESULTS \(c ) = log_{c}(P[c_{k}\y}) of this APP can be regarded as the sum A Performance Criteria and System Assumptions of two terms
We now present performance results of the layered spacetime concepts descπbed so far. The performance mea¬
Mc_{k}) = λ"(c_{k}) + λ'(c_{k}) (17) sure is the blockerror rate (BLER) over Rayleigh fading. The results are obtained through Monte Carlo simulation. The where λ^{p}{c ) = log_{e}(F[c*]) is the logarithm of the a prior inBLER is averaged over up to 40000 channel realizations. Each formation provided by the decoder, and A^{e} ( c_{k} ) is called the "ex block contains 400 information bits (before coding). tπnsic" information. In each "turbo" iteration, the spacetime
In comparing the performance results to channel capacity, equalizer subtracts λ^{p}(c ) from the newly computed value of we follow the convention of a number of previous works (e.g , λ(c_{f}c ) to obtain the extrinsic information λ'{c_{k}) [see Fig. 1(a) [9], [23]) to compare the computed BLER with the "outage caand (b)] The entire sequence {X'(c_{k} ) } is demterleaved and forpacity" [1 L i.e.. the probability that a specified bit rate is not warded to the decoder. supported by the channel capacity. This is a vague companson,
Similarly. the decoder computes the logAPP since the Shannon limit refers to the highest enorfree bit rate v(c_{k}) = \og_{c} {P[c_{k}\{X'{c_{k}) }]) based on the demterleaved possible for long encoded blocks but it does not specify how extnnsic information provided by the spacetime equalizer, long the blocks should be. Nevertheless, such a companson and subtract λ'(c ) from it to obtain extnnsic information should still be meaningful as long as the block length and BLER υ'(c ). The extnnsic mformation is then interleaved and are specified. This is similar to the way a biterror rate of 10^{5} forwarded to the equalizer as the new a priori information is commonly used as the "error free" reference for an additive X^{p}{c ) for the next "turbo" iteration. white Gaussian noise (AWGN) channel.
The interleaver considered in this study is a pseudorandom In order to assess the best performance achievable, we asinterleaver, i.e., we generate a pseudorandom permutation of sume that the channel characteπstics can be perfectly estimated numbers from 1 to /. where / is the block length, and then use at the receiver Similarly, the choices of 1D processing and this permutation as a fixed interleaver. coding techniques are important to deliver the best possible
In combining the branch metπc obtained from the equalizer performance. We try to optimize these choices while keeping output with the branch metnc obtained from the soft input them as practical as possible. Except for the use of array provided by the decoder, the MAP processor in the spacetime processing and iterative MAP algonthms, all the radio link equalizer must compute the α priori information for each 8PS techniques assumed in this study are "legacycompatible" with symbol x_{k} from the three soft inputs (X^{p}(c_{3k} ), X^{p}(r_{ik+ 1} ), the EDGE standard (note also that vast research interest in turbo λ^{p}(c. _{+} ) ) ^{We} assume that this is done by way of summing coding has made simplified MAP algoπthms available [21 ], the three soft inputs as if the three coded bits were transmuted [221 that are not much more complex than the conventional from independent sources (these soft inputs are actually not Viterbi algoπthm) None of these techniques are claimed independent when conditioned on the observed waveform ot the to be optimum Yet. our results indicate that nearcapacity entire data burst) This is a suboptimai method, which is known performance is achievable when combining them through the to cause a ' random modulation^{'} performance degradation coded lavered spacetime architectures which appeared to perform slightly better than other generators we tested) Both schemes assume the use of bitinterleaved 8PSK with Gray mapping The turbo coding scheme has an additional interleaver within the encoder which uses another pseudorandomly generated permutation The receiver structure is consistent with what we have descπbed so far Note, however that we assume a minimum number of filter taps (only one feedforward tap per branch and no feedback filter) whenever there is no delay spread assumed, although the MAP processor in the DDFSE is always used for iterative detection decoding as de scnbed in Section IV B For the turbo coding scheme, "one iteration ' means a full cvcle of three processes 1 ) MAP processing in DDFSE 2) turbo decoding by the first decoder, and 3) turbo decoding by the second decoder
Fig 3(a) shows the performance of the two coding schemes in an AWGN channel First we note that the performance of convolutional cod g also benefits from iterative processing This is due to the suboptimal nature of the decoding scheme, l e the 'random modulation effect descπbed earlier, which can be improved through iterative decoding Fig 3(a) shows that most of the improvement is achieved within two decoding cycles For turbo coding, the performance still improves even after five iterations, but saturates quickly after ten iterations At 10^{3} BLER (approximately equivalent to 10^{"}° bitenor rate), turbo coding outperforms convolutional coding by about 2 2 dB, and the required SNR is within only 2 4 dB of the 0dB Shannon limit for a spectral efficiency of 1 bps/Hz (8PSK with rate 1/3 codmg)
However, when we look at the average BLER performanceAverage SNR (dB) over quasistatic flat fading channels in Fig 3(b), the benefit
(b) of turbo coding (with ten iterations) over convolutional coding (with two iterations) is reduced to only about 05 dB at any value
Fig 3 Performance of bnuiterleaved 8 PSK with rate 1/3 convolutional and of the average SNR and for all the assumed numbers of receive turbo coding over (a) AWGN channel and (b) quasistatic flat Rayleigh fading channels with V receive diversity antennas diversity antennas This is not surpπsing for two reasons First it is well known that the average BLER is determined mostly by the probability of fading events that results in high BLER s
B Choosing the Coding Scheme If we look at the relative performance at a BLER of, say above
We consider a bitinterleaved coded modulation scheme 10% in Fig 3(a) the difference between the two coding schemes using 8PSK with Gray mapping and rate 1/3 coding is indeed less than 1 dB Second the performance of convoluSquareroot Nyquist filtering with 30% rolloff is assumed at the tional coding over fading channels is already within about 2 dB transmitter and receiver Bitinterleaved coded modulation has of the capacity bound — the capacity bound in this case is debeen shown [36], [37] to outperform traditional trelliscoded fined as the probability that the combined output SNR of all modulation in fast fading channels (where time diversity can diversity branches is below the 0dB Shannon lirmt Thus, there be exploited through sufficient interleaving) and it can be is not much room for fuπher improvement improved upon by considering a better mapping technique Based on the fact that the performances of the two coding that permits a large Euclidean distance without sacπficmg the schemes are quite similar in quasi static fading channels we maximum Hamming distance of the baseline coding scheme will only consider convolutional coding in the remainder of this [38] In this paper, though, since quasistatic fading is our paper basic assumption, the code by itself must be able to withstand deep fades In pπnciple, any code that performs well in an C Lavered SpaceTime Performance AWGN channel is considered a good candidate — turbo codes We first look at the performance of the two coded lavered are among the strongest candidates that come to mind spacetime approaches over a flat Rayleigh fading channel
Fig 3(a) and (b) provide a performance companson between Fig 4 shows the different capacity bounds for this channel two rate 1/3 coding schemes one using a 64state convolutional assuming V = 2 1 and 8 where V is the number ot transmit code with (octal) generators ( d G_{2} G_{3} ) = ( 155 117 123) and receive antennas Again although we plot the results as (the same code as proposed for EDGE [20)) and the other using block eπor rate the capacity bound is defined as the probaa turbo code with two identical 16state recursive encoders simbility that the specified spectral efficiency R (R = V in this ilar to the scheme oπgmally proposed by Beπou and Glavieux case) is not supported bv each of the differentlv defined channel [ 12] (the results here assume generators ( Ci G_>) = (23 31 ) capacities C denotes the Shannon capacity bound given bv (4)
Average SNR (dB) Average SNR (dB)
Ftg. . Capacity bounds for quasistatic flat Rayleigh fading channels with .V _{Fig}. 5. Layered spacetime performance of LSTI with two transmit and two transmit and Λ^{"} receive antennas. C: Shannon capacity, C_{F} : Foschini (original) receive antennas (.V = 2 ). Quasistatic flat Rayleigh fading channel, bound, and  _{1}1 : capacity bound for LSTII.
[which is equivalent to the generalized Foschini bound CF. Λ/F in ( 1 1 )], C_{f} denotes the original Foschini bound (with the ZF constraint) in (3), and CLSTΠ is the capacity bound for LSTII in (9) (however, the results for C.sτ11 are obtained simply by averaging the probability that R = 1 is not suppoπed by each processing layer). Note that CLST _{11} can indeed provide approximately a diversity order of N; this is attributed largely to the use of layer ordering as discussed earlier. Note also that all the bounds show an improvement with increasing JV. This means that the capacity actually increases more than linearly with the number of transmit and receive antennas. However, there is a diminishing improvement as N increases to a much larger number.
Fig. 5 shows the simulation results for LSTI with 2 transmit Average SNR (dB) and 2 receive antennas (i.e., N — 2). Three sets of results are provided, assuming: 1) soft decisions; 2) hard decisions; and 3) Fig. 6. Layered spacetime performance of LSTI with four transmit and four coπect decisions in each layer (note that the DDFSE always uses receive antennas (.V = 4). Quasistatic flat Rayleigh fading channel. tentative decisions and provides soft outputs to the decoder). We see that, although soft decisions offer some improvernent over hard decisions, the impact of decision enors is still quite noticeable. Fig. 6 shows similar results for N = 4. Here, the impact of decision errors is not as significant as the previous results, and turbo processing and soft decisions help to reduce much of this impact. With three iterations, the effect of decision enors almost completely disappears when using soft decisions. Decision enors have a lesser effect for a larger ;V because of the greater diversity order available through anay processing and layer ordering.
In Fig. 7, we compare the results using soft decisions and six "turbo" iterations with the Shannon capacity bound. For N = 4 and 8, the performance of LSTI is within 2.53 dB of the capacity bound at 10% BLER (and about 33.5 dB at 1% BLER).
Since the BLER may vary as a function of the block size,^{3} it Average SNR (dB) is also important to consider the processing loss by discounting the loss due to the inefficiency of modulation and coding. As Fig. 7. Layered spacetime performance of LSTI for .V = 2. 4. and 8. Soft decisions. 6 iterations. Quasistatic flat Rayleigh fading channel.'As an example, when we double the block size, the required average SNR is 0.20.4 dB greater than the results shown here. However, this difference in average SNR applies uniformly to all results, with or without layered spacetime shown in Fig. 3(b). there is already a gap of about 2 dB between processing the performance of our coding scheme and the Shannon limit. U over 4. Son
From the above results, we conclude that, for N = 4 and 8, LSTI outperforms LSTII by a margin of 0.5 dB (at 10% the suboptimum spacetime equalizer structure we assume, as BLER) to 3 dB (at 1% BLER). For N = 2, the performance of LSTI is greatly affected by decision errors (note that, even in already discussed in Section IVA. this case. LSTI still performs as well as LSTII at 10% BLER), whereas LSTII can reach a lower BLER at high average SNR. VI. CONCLUSION Based on these results, the layered spacetime approach is not highly recommended for N = 2. As mentioned earlier, By deriving the generalized Shannon capacity formula and spacetime coding is a better alternative to achieve a spectral suggesting a layered spacetime architecture that attains a tight efficiency of 2 bps/Hz. For instance, a 64state spacetime lower bound on the capacity achievable. Foschini has laid a coded QPSK can perform to within 2 dB of the Shannon significant theoretical foundation for improving the wireless capacity bound [23]. channel capacity through multipieeiement array technology. We have shown that Foschini's lower bound is actually the true Shannon bound when the output SNR of the spacetime
D. FrequencySelective Channels processing in each layer is represented by the corresponding
Finally, we present an example of performance results for fre"matched filter" bound. We then provided two coded layered quencyselective fading channels. This example assumes N = 4 spacetime approaches as an embodiment of this concept. For and the use of soft decisions for both LSTI and LSTII. Fig.9(a) a large number of transmit and receive antennas, coding across and (b) show the results for the TU and HT profiles, defined in the layers provides a better performance than independent Tables I and II. Again, we only show results with two "turbo" itcoding within each layer. However, with two transmit and two erations for LSTH because little improvement can be achieved receive antennas, the former is heavily affected by decision with more iterations in this case. For both deiay profiles, the pererrors and. therefore, provides a poorer performance than the formance at 10% BLER is within 3 dB of the Shannon bound latter. for LSTI with six iterations, and within 4 dB for LSTII with The underlying coding and signal processing techniques used two iterations. At a lower BLER. the loss relative to the bound in this study are based on practical but suboptimal approaches. is greater for HT than for TU. This is due to the limitation of Yet. such subopti ality can be greatly compensated for by it erative processing. Overall, our coded layered spacetime apFurthermore, using the matrix identity [40] proaches can achieve a performance within about 3 dB of the Shannon bound at 10% BLER. about 2 dB of which is a loss (27) due to the practical coding scheme we assume. Thus, not only det(A) is the layered spacetime architecture exactly what the Shannon where 4_{a}dj is called the adjugate matrix of matrix A, we can limit has prescribed in a theoretical sense, but it also provides rewrite (26) as an attractive general methodology for improving and achieving the wireless channel capacity. dj
H •' _ = ^«d) HI
(28) det(A) ^{_ n} det(i3) l + r„(/) ^{'}
APPENDIX By replacing det( ) in the above equation using (21 ), we obtain
PROVING THE EQUIVALENCE OF FOSCHINI BOUND AND SHANNON CAPACITY B««i5r; det(A) n (29)
Using the mathematical induction method, we will prove that (4) and ( 11) are identical. In order to do so, we must show that fc IIl^{(1 + r}*^{(}/^{))}
We then show in the following that, given (21), (19) is also true diversity order, including the effects of both multiple antennas
For convenience, let = det[b_{l}, . ir;. ...
+ det a _{r}.:, _{nl}(f) y s,_{1}K^{l} and 3 = S„ιK^{1}. (25) H' , (34)
" Kt(/)
 tiot[6ι. ^{• ■ •} • *;. ^{■ ■} We can rewrite (24) as
_{L} ff«ι(/) det[H'_{n}. H'
Λ'H = ι + r.(/) ^{'} (26) = <lct[6ι. • ■ Similarly, we can expand the result of (34) with respect to the [ 16] C Douillard. C. B. M. Jezequel. A. Picart. P. Didier. and A. Glavieux second column, the third column, and so on (except for the _{7}th "Iterative correction of intersymbol interference: Turbo equalization. Eur Trans Telecommun . vol. 6. pp. 50751 1. Sept. 1995 column). Eventually, we obtain [ 17] A Picart. P. Didier, and A. Glavieux. "Turbodetection: A new approach to combat channel frequency selectivity." in Proc IEEE ICC^{'}97. Mon rreal. Quebec. Canada. June 1997, pp. 14981502. column [ 18] D Raphaeli and Y. Zarai. "Combined turbo equalization and turbo de det(j4_{j} ) = det [6ι . b_{2}, , H . b_{M}\ = det(B_{}}) coding." IEEE Commun Lett . vol. 2. pp. 107109. Apr. 1998.
[ 19] J. GarciaFπas and J. D Villasenor. "Combined blind equalization anc (35) turbo decoding." in Proc IEEE ICC'99. Communication Theory Mini Conference. Vancouver. BC. Canada. June 1999. pp. 5257. which proves (31 ). The proof of ( 19) is therefore complete. [20] S. L. Anyavisitakul. J. H. Winters, and N. R. Sollenberger. "Joint equalization and interference suppression for high data rate wireless systems,' in Proc. IEEE VTC 99. Houston. TX. May 1999. pp. 700706.
ACKNOWLEDGMENT [21 ] P. Jung. "Novel low complexity decoder for turbo codes." Electron. Lett vol. 31. no. 2. pp. 8687. Jan. 1995.
The author wishes to thank G. J. Foschini for reviewing the [22] A. J. Viterbi. "An intuitive justification and a simplified implementatior information theory part of the oπginal manuscπpt of this paper of the MAP decoder for convolutional codes." IEEE J. Select. Area: and suggesting several improvements, and for the enormous inCommun.. vol. 16, pp. 260264. Feb. 1998.
(231 V. Tarokh. N. Seshadn. and A. R. Calderbank. "Spacetime codes foi spiration he provided by inventing the layered spacetime conhigh data rate wireless communications: Performance analysis and code cept. The author also benefited from discussions with K. R. construction," IEEE Trans Inform Theory, vol. 44, pp. 744765. Mar Narayanan. I. Lee. and X. Li. Finally, the author thanks the 1998.
[24] A. F. Naguib. V. Tarokh. N. Seshadn. and A. R. Calderbank. "A anonymous reviewers for valuable comments and suggestions. spacetime coding modem for highdatarate wireless communications." IEEE Select Areas Commun.. vol. 16. pp. 1459—1478. Oct
REFERENCES 1998.
[251 ^{v} Tarokh. A. F. Naguib. N. Seshadn. and A. R. Calderbank. "Combined
[ 11 G. J. Foschini and M. J. Gans. "On limits of wireless communication array processing and spaceu e coding," IEEE Trans. Inform. Theory in a fading environment when using multiple antennas." Wireless Pers. vol. 45. pp. 11211 128. May 1999 Commun . vol. 6. no. 3. pp. 311335. Mar. 1998. [26] J. G. Proakis. Digital Communications. 2nd ed. New York: McGraw
[2] W. C. Jakes Jr.. Ed.. Microwave Mobile Communications. New York: Hill. 1989. Wiley. 1974. [27] A. DuelHallen and C. Heegard. "Delayed decisionfeedback sequence
[31 D. C. Cox. "Universal digital portable radio communications." Proc. estimation." IEEE Trans. Commun , vol. 37. pp. 428436. May 1989 IEEE. vol. 75. pp. 436477. Apr. 1987. [28] S. L. Anyavisitakul and I. Lee, "The equivalence of two unified solu¬
[4] R. A. Monziπgo and T. W Miller. Introduction to Adaptive Artions for optimum spacetime processing," IEEE Trans. Commun . to rays. New York: Wiley. 1980. be published.
[51 J. H. Winters. J. Salz, and R. D. Gitlm. "The impact of antenna diver[29] S. Anyavisitakul and L. J. Greenstein. "Reducedcomplexity equalizasity on the capaciry of wireless communications systems." IEEE Trans. tion techniques for broadband wireless channels." IEEEJ. Select Areas Commun.. vol. 42. pp. 17401751. Apr. 1994. Commun.. vol. 15, pp. 515. Jan. 1997.
[6] S. L. Anyavisitakul. J. H. Winters, and 1. Lee, "Optimum spacetime [30] P. A. Voois. I. Lee. and J. M. Cioffi. "The effect of decision delay in processors with dispersive mterference: Unified analysis and required finitelength decision feedback equalization." IEEE Trans. Inform filter span. ' IEEE Trans. Commun.. vol. 47, pp. 10731083. July 1999. Theory, vol. 42. pp. 618621. Mar. 1996
[7] G. J. Foschini. "Layered spacetime architecture for wireless commu[31] S. Haykin. Adaptive Filter Theory Englewood Cliffs. NJ' Prentice nication in a fading environment when using multiple antennas." Bell Hall. 1991. Labs Tech. J.. vol. 1. no. 2. pp. 4159. Autumn 1996. [32] L. R. Bahl. J. Cocke. F. Jelinek. and J. Raviv. "Optimal decoding of linear
[81 S. Verdu. Multiuser Detection. Cambridge. U.K.: Cambridge U iv. codes for minimizing symbol error rate." IEEE Trans. Inform. Theon, Press. 1998. vol. IT20. pp. 284287. Mar. 1974.
[9 G. J. Foschini. G. D. Golden. R. A. Valenzuela. and P. W Wolaniansky, [33] J. Hagenauer. E. Offer, and L. Papke. "Iterative decoding of bina . "Simplified processing for high spectral efficiency wireless communicablock and convolutional codes." IEEE Trans Inform. Theory, vol. 42 tion employing multielement arrays." IEEE J. Select. Areas Commun.. pp. 429445. Mar. 1996. vol. 17. pp. 18411852. Nov. 1999. [34] S. Benedetto. D. Divsalar. G. Montorsi. and F. Pollara. "Softoutput de[ 10) R. van Nobelen. N. Seshadn. J. Whitehead. and S. Timiπ. "An adaptive coding algoπthms for continuous decoding of parallel concatenated conradio link protocol with enhanced data rates for GSM evolution." IEEE volutional codes." in Proc IEEE ICC 96. Dallas. TX, June 1996. pp Pers Commun . vol. 6. pp. 5463. Feb. 1999. 1 121 17 [ I I ] C. Berrou. A. Glavieux. and P. Thitimajshima. "Near Shannon limit [35] R. J. McEliece. D. J. C. MacKay. and J.F. Cheng. Turbo decoding as errorcorrection coding and decoding: Turbo codes." in Proc. IEEE an instance of Pearl's "belief propagation^{"} algonthm." IEEE J Select ICC93. Geneva. Switzerland. May 1993. pp. 10641070. Areas Commun . vol. 16. pp 140152. Feb. 1998 [12] C. Benou and A. Glavieux. "Near optimum error correcting coding and [36] E. Zehavi. '8PSK trellis codes for a Rayleigh channel." IEEE Trans decoding: Turbo codes." IEEE Trans Commun . vol.44. pp. 12611271. Commun.. vol. 40. pp. 873883. May 1992. Oct. 1996 [37] G. Caire. G. Taπcco. and E. Biglien. "Bitinierleaved coded modula[ 13] S. Benedetto and G. Montorsi. "Unveiling turbo codes: Some results tion." IEEE Trans. Inform Theory, vol 44. pp. 927946. May 1998 on parallel concatenated coding schemes." IEEE Trans Inform. Theory. [38) X. Li and J Ritcey. "Trelliscoded modulation with bn interleaving and vol. 42. pp. 409428. Mar. 1996. iterative decoding," IEEE Trans Commun . vol. 17. pp. 715724. Apr [ I4 S Benedetto. D Divsalar. G. Montorsi. and F Pollara. "Serial concate1999. nation of interleaved codes: Design and performance analysis." IEEE [39] S. Anyavisitakul and Y Li. Joint coding and decision feedback Trans. Inform Theory, vol. 44. pp 409429. Apr. 1998 equalization tor broadband wireless channels." IEEE J Select Areas [ I 5 K. R. Narayanan and G. L. Stuber. "A senal concatenation approach to Commun . vol 16. pp. 16701678. Dec 1998 iterative demodulation and decodine." IEEE Trans Commun . vol 47. [40 G Siring. Linear Λt ehra and Its Applnaiions Orlando. FL. Harcourt pp. 956961. July 1999 Brace Jovanovich. 1980 1/19013 ^{r}
According to the present invention, the receiver can select a set of antenna elements, including their number and / or identity, from among a larger group of antenna elements in order, among other things, to improve performance of the system without increasing the extent of radiofrequency circuitry. One process for selecting antenna elements is to utilize equation 4 above as a measure of quality for the particular set of antenna elements being evaluated. That evaluation can occur for each permutation or combination of antenna elements in order to select the subset with optimum performance (as determined, for instance, by selecting the subset with greatest value calculated according to equation 4). This can occur at whatever desired points in time, including periodically.
Claims
Priority Applications (2)
Application Number  Priority Date  Filing Date  Title 

US15298299P true  19990909  19990909  
US60/152,982  19990909 
Applications Claiming Priority (1)
Application Number  Priority Date  Filing Date  Title 

AU73581/00A AU7358100A (en)  19990909  20000908  Turbo detection of spacetime codes 
Publications (1)
Publication Number  Publication Date 

WO2001019013A1 true WO2001019013A1 (en)  20010315 
Family
ID=22545285
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

PCT/US2000/024641 WO2001019013A1 (en)  19990909  20000908  Turbo detection of spacetime codes 
Country Status (2)
Country  Link 

AU (1)  AU7358100A (en) 
WO (1)  WO2001019013A1 (en) 
Cited By (21)
Publication number  Priority date  Publication date  Assignee  Title 

US6542556B1 (en)  20000331  20030401  Nokia Mobile Phones Ltd.  Spacetime code for multiple antenna transmission 
WO2003049397A2 (en) *  20011203  20030612  Qualcomm Incorporated  Iterative detection and decoding for a mimoofdm system 
FR2841068A1 (en) *  20020614  20031219  Comsis  Decoding linear spacetime codes in multipleantenna wireless transmission system, used in digital radio data distribution over local wireless network, uses matrices to remove interference caused by multiple propagation across ionosphere 
GB2394389A (en) *  20021015  20040421  Toshiba Res Europ Ltd  SISO equaliser and SISO decoder connected in feedback relationship, and suitable for receiving signals from multiple antennae transmitters 
US6748024B2 (en)  20010328  20040608  Nokia Corporation  Nonzero complex weighted spacetime code for multiple antenna transmission 
EP1453262A1 (en) *  20030228  20040901  Mitsubishi Denki Kabushiki Kaisha  Iterative MMSE detection 
US6865237B1 (en)  20000222  20050308  Nokia Mobile Phones Limited  Method and system for digital signal transmission 
EP1529347A1 (en) *  20020703  20050511  The Directv Group, Inc.  Method and apparatus for layered modulation 
EP1589685A1 (en) *  20040422  20051026  France Telecom  Iterative chip equalization and multiuser detection for CDMA communications systems on MIMO channels 
GB2416967A (en) *  20040729  20060208  Toshiba Res Europ Ltd  Turbo equalization in MIMO systems using the BCJR algorithm 
US7046737B2 (en)  19971223  20060516  Cingular Wireless Ii, Llc  Nearoptimal lowcomplexity decoding of spacetime codes for wireless applications 
US7120200B2 (en)  19970916  20061010  Cingular Wireless Ii, Llc  Transmitter diversity technique for wireless communications 
US7209522B1 (en)  20021212  20070424  Marvell International Ltd.  Blast MIMO signal processing method and apparatus 
US7274752B2 (en)  19980917  20070925  Cingular Wireless Ii, Llc  Maximum ratio transmission 
US7477703B2 (en)  20000222  20090113  Nokia Mobile Phones, Limited  Method and radio system for digital signal transmission using complex spacetime codes 
WO2011028413A1 (en) *  20090902  20110310  Qualcomm Incorporated  Unified iterative decoding architecture using joint llr extraction and a priori probability 
US8031800B2 (en)  20001222  20111004  Amosmet Investments Llc  Transmitting digital signal 
US8514984B2 (en)  20090902  20130820  Qualcomm Incorporated  Iterative decoding architecture with HARQ combining and soft decision directed channel estimation 
US8890722B2 (en)  20100420  20141118  Qualcomm Incorporated  Method and apparatus for soft symbol determination 
US8989320B2 (en)  20090902  20150324  Qualcomm Incorporated  Hardware simplification of sicMIMO decoding by use of a single hardware element with channel and noise adaptation for interference cancelled streams 
US9065516B2 (en)  19971031  20150623  At&T Mobility Ii, Llc  Low complexity maximum likelihood detection of concatenated space codes for wireless applications 

2000
 20000908 AU AU73581/00A patent/AU7358100A/en not_active Abandoned
 20000908 WO PCT/US2000/024641 patent/WO2001019013A1/en active Application Filing
NonPatent Citations (4)
Title 

BAUCH, NAGUIB: "MAP equalization of spacetime coded signals over frequency selective channels", IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, 21 September 1999 (19990921)  24 September 1999 (19990924), Piscataway, US, pages 261  265 vol.1, XP002152500, ISBN: 0780356683 * 
DASHAN SHIU, KAHN: "Layered spacetime codes for wireless communications using multiple transmit antennas", IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 6 June 1999 (19990606)  10 June 1999 (19990610), Piscataway, US, pages 436  440, XP002152497 * 
DASHAN SHIU, KAHN: "Scalable layered spacetime codes for wireless communications: performance analysis and design criteria", IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, 21 September 1999 (19990921)  24 September 1999 (19990924), 1999, Piscataway, NJ, USA, IEEE, USA, pages 159  163, XP002152499, ISBN: 0780356683 * 
TAROKH ET AL.: "Combined array processing and spacetime coding", IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 45, no. 4, May 1999 (19990501), New York, US, pages 1121  1128, XP002152498, ISSN: 00189448 * 
Cited By (44)
Publication number  Priority date  Publication date  Assignee  Title 

US9203499B2 (en)  19970916  20151201  At&T Mobility Ii Llc  Transmitter diversity technique for wireless communications 
US9749032B2 (en)  19970916  20170829  At&T Mobility Ii Llc  Transmitter diversity technique for wireless communications 
US7120200B2 (en)  19970916  20061010  Cingular Wireless Ii, Llc  Transmitter diversity technique for wireless communications 
US9065516B2 (en)  19971031  20150623  At&T Mobility Ii, Llc  Low complexity maximum likelihood detection of concatenated space codes for wireless applications 
US7046737B2 (en)  19971223  20060516  Cingular Wireless Ii, Llc  Nearoptimal lowcomplexity decoding of spacetime codes for wireless applications 
US7526040B2 (en)  19971223  20090428  At&T Mobility Ii Llc  Nearoptimal lowcomplexity decoding of spacetime codes for fixed wireless applications 
US8179991B2 (en)  19971223  20120515  At&T Mobility Ii Llc  Nearoptimal lowcomplexity decoding of spacetime codes for fixed wireless applications 
US7362823B2 (en)  19980917  20080422  Cingular Wireless Ii, Llc  Maximum ratio transmission 
US7274752B2 (en)  19980917  20070925  Cingular Wireless Ii, Llc  Maximum ratio transmission 
US6865237B1 (en)  20000222  20050308  Nokia Mobile Phones Limited  Method and system for digital signal transmission 
USRE43746E1 (en)  20000222  20121016  Amosmet Investments Llc  Method and radio system for digital signal transmission using complex spacetime codes 
US7477703B2 (en)  20000222  20090113  Nokia Mobile Phones, Limited  Method and radio system for digital signal transmission using complex spacetime codes 
US7355961B2 (en)  20000222  20080408  Nokia Corporation  Method and arrangement for digital signal transmission using layered spacetime codes 
US6542556B1 (en)  20000331  20030401  Nokia Mobile Phones Ltd.  Spacetime code for multiple antenna transmission 
US8031800B2 (en)  20001222  20111004  Amosmet Investments Llc  Transmitting digital signal 
US6748024B2 (en)  20010328  20040608  Nokia Corporation  Nonzero complex weighted spacetime code for multiple antenna transmission 
US6816557B2 (en)  20010328  20041109  Nokia Mobile Phones, Ltd.  Nonzero complex weighted spacetime code for multiple antenna transmission 
WO2003049397A2 (en) *  20011203  20030612  Qualcomm Incorporated  Iterative detection and decoding for a mimoofdm system 
US7154936B2 (en)  20011203  20061226  Qualcomm, Incorporated  Iterative detection and decoding for a MIMOOFDM system 
WO2003049397A3 (en) *  20011203  20040226  Qualcomm Inc  Iterative detection and decoding for a mimoofdm system 
KR100942401B1 (en)  20011203  20100217  퀄컴 인코포레이티드  Iterative detection and decoding for a mimoofdm system 
FR2841068A1 (en) *  20020614  20031219  Comsis  Decoding linear spacetime codes in multipleantenna wireless transmission system, used in digital radio data distribution over local wireless network, uses matrices to remove interference caused by multiple propagation across ionosphere 
WO2003107582A2 (en) *  20020614  20031224  Comsis  Method for decoding linear spacetime codes in a multipleantenna wireless transmission system, and decoder therefor 
WO2003107582A3 (en) *  20020614  20040415  Comsis  Method for decoding linear spacetime codes in a multipleantenna wireless transmission system, and decoder therefor 
EP1529347A4 (en) *  20020703  20071031  Directv Group Inc  Method and apparatus for layered modulation 
EP1529347A1 (en) *  20020703  20050511  The Directv Group, Inc.  Method and apparatus for layered modulation 
GB2394389A (en) *  20021015  20040421  Toshiba Res Europ Ltd  SISO equaliser and SISO decoder connected in feedback relationship, and suitable for receiving signals from multiple antennae transmitters 
GB2394389B (en) *  20021015  20050518  Toshiba Res Europ Ltd  Equalisation apparatus and methods 
US7209522B1 (en)  20021212  20070424  Marvell International Ltd.  Blast MIMO signal processing method and apparatus 
US7292658B2 (en)  20030228  20071106  Mitsubishi Denki Kabushiki Kaisha  Method and device for efficient decoding of symbols transmitted in a MIMO telecommunication system 
EP1453262A1 (en) *  20030228  20040901  Mitsubishi Denki Kabushiki Kaisha  Iterative MMSE detection 
EP1589685A1 (en) *  20040422  20051026  France Telecom  Iterative chip equalization and multiuser detection for CDMA communications systems on MIMO channels 
CN1973475B (en)  20040422  20110601  法国电信公司  Receiving method and system for communication through frequencyselective channels with multiple transmitting antennas and receiving antenas 
US7809045B2 (en)  20040422  20101005  France Telecom  Disjoint iterative chip equalization and multiuser detection for CDMA communication system on a MIMO channel 
WO2005114887A1 (en) *  20040422  20051201  France Telecom  Disjoint iterative chip equalisation and multiuser detection for cdma communication systems on a mimo channel 
GB2416967B (en) *  20040729  20070131  Toshiba Res Europ Ltd  Turbo equalization in a MIMO digital wireless wideband system 
GB2416967A (en) *  20040729  20060208  Toshiba Res Europ Ltd  Turbo equalization in MIMO systems using the BCJR algorithm 
CN102484564A (en) *  20090902  20120530  高通股份有限公司  Unified iterative decoding architecture using joint LLR extraction and a priori probability 
WO2011028413A1 (en) *  20090902  20110310  Qualcomm Incorporated  Unified iterative decoding architecture using joint llr extraction and a priori probability 
US8976903B2 (en)  20090902  20150310  Qualcomm Incorporated  Unified iterative decoding architecture using joint LLR extraction and a priori probability 
US8989320B2 (en)  20090902  20150324  Qualcomm Incorporated  Hardware simplification of sicMIMO decoding by use of a single hardware element with channel and noise adaptation for interference cancelled streams 
US8514984B2 (en)  20090902  20130820  Qualcomm Incorporated  Iterative decoding architecture with HARQ combining and soft decision directed channel estimation 
KR101409905B1 (en) *  20090902  20140619  퀄컴 인코포레이티드  Unified iterative decoding architecture using joint llr extraction and a priori probability 
US8890722B2 (en)  20100420  20141118  Qualcomm Incorporated  Method and apparatus for soft symbol determination 
Also Published As
Publication number  Publication date 

AU7358100A (en)  20010410 
Similar Documents
Publication  Publication Date  Title 

Janani et al.  Coded cooperation in wireless communications: spacetime transmission and iterative decoding  
Liew et al.  Spacetime codes and concatenated channel codes for wireless communications  
Duman et al.  Coding for MIMO communication systems  
Laot et al.  Lowcomplexity MMSE turbo equalization: a possible solution for EDGE  
Zhou et al.  Singlecarrier spacetime blockcoded transmissions over frequencyselective fading channels  
Barbero et al.  Extending a fixedcomplexity sphere decoder to obtain likelihood information for turboMIMO systems  
US8542765B2 (en)  Hierarchical coding with multiple antennas in a wireless communication system  
Roy et al.  Highrate communication for underwater acoustic channels using multiple transmitters and space–time coding: Receiver structures and experimental results  
Lee et al.  Iterative detection and decoding with an improved VBLAST for MIMOOFDM systems  
US20030138065A1 (en)  Power and confidence ordered low complexity soft turbomud with voting system  
Tonello  Spacetime bitinterleaved coded modulation with an iterative decoding strategy  
Wautelet et al.  MMSEbased fractional turbo receiver for spacetime BICM over frequencyselective MIMO fading channels  
EP1337082B1 (en)  Receiver and method for multiinput multioutput iterative detection using feedback of soft estimates  
Gong et al.  Spacefrequencytime coded OFDM for broadband wireless communications  
Ping et al.  A unified approach to multiuser detection and spacetime coding with low complexity and nearly optimal performance  
JP6096922B2 (en)  Check and irregular nonsystematic IRA code encoding and decoding system and method  
Lee et al.  Spacetime bitinterleaved coded modulation for OFDM systems  
El Gamal et al.  A new approach to layered spacetime coding and signal processing  
Sellathurai et al.  TurboBLAST for wireless communications: Theory and experiments  
EP1392017A1 (en)  A MIMO radio telecommunication system using multilevelcoded modulation operative by iterative determination of soft estimates, and a corresponding method  
Lin et al.  Improved spacetime codes using serial concatenation  
EP1542388A1 (en)  Improved communications apparatus and methods  
Sellathurai et al.  TURBOBLAST for highspeed wireless communications  
Shang et al.  Space–time block codes achieving full diversity with linear receivers  
Reynolds et al.  Lowcomplexity turboequalization for diversity channels 
Legal Events
Date  Code  Title  Description 

AK  Designated states 
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CR CU CZ DE DK DM DZ EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NO NZ PL PT RO RU SD SE SG SI SK SL TJ TM TR TT TZ UA UG UZ VN YU ZA ZW 

AL  Designated countries for regional patents 
Kind code of ref document: A1 Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN GW ML MR NE SN TD TG 

121  Ep: the epo has been informed by wipo that ep was designated in this application  
REG  Reference to national code 
Ref country code: DE Ref legal event code: 8642 

122  Ep: pct application nonentry in european phase  
NENP  Nonentry into the national phase in: 
Ref country code: JP 