Classifications

• • H—ELECTRICITY
  • H01—ELECTRIC ELEMENTS
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  • H01Q1/12—Supports; Mounting means
  • H01Q1/22—Supports; Mounting means by structural association with other equipment or articles
  • H01Q1/24—Supports; Mounting means by structural association with other equipment or articles with receiving set
  • H01Q1/241—Supports; Mounting means by structural association with other equipment or articles with receiving set used in mobile communications, e.g. GSM
  • H01Q1/246—Supports; Mounting means by structural association with other equipment or articles with receiving set used in mobile communications, e.g. GSM specially adapted for base stations
• • H—ELECTRICITY
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  • H01Q21/06—Arrays of individually energised antenna units similarly polarised and spaced apart
  • H01Q21/08—Arrays of individually energised antenna units similarly polarised and spaced apart the units being spaced along or adjacent to a rectilinear path
• • H—ELECTRICITY
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• • H—ELECTRICITY
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  • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
  • H04B1/12—Neutralising, balancing, or compensation arrangements
  • H04B1/123—Neutralising, balancing, or compensation arrangements using adaptive balancing or compensation means
  • H04B1/126—Neutralising, balancing, or compensation arrangements using adaptive balancing or compensation means having multiple inputs, e.g. auxiliary antenna for receiving interfering signal
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  • H04B7/18515—Transmission equipment in satellites or space-based relays
• • H—ELECTRICITY
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  • H04B7/18532—Arrangements for managing transmission, i.e. for transporting data or a signalling message
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• • H—ELECTRICITY
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• • H—ELECTRICITY
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• • H—ELECTRICITY
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  • H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
• • H—ELECTRICITY
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  • H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
  • H04W84/022—One-way selective calling networks, e.g. wide area paging
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• • H—ELECTRICITY
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  • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
  • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
  • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
• • 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
  • H04L1/007—Unequal error protection
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  • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
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  • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
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  • H04L25/03178—Arrangements involving sequence estimation techniques
  • H04L25/03248—Arrangements for operating in conjunction with other apparatus
  • H04L25/03299—Arrangements for operating in conjunction with other apparatus with noise-whitening circuitry
• • H—ELECTRICITY
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• • H—ELECTRICITY
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  • H04W74/00—Wireless channel access
  • H04W74/08—Non-scheduled access, e.g. ALOHA
• • H—ELECTRICITY
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  • H04W84/00—Network topologies
  • H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
  • H04W84/04—Large scale networks; Deep hierarchical networks
  • H04W84/042—Public Land Mobile systems, e.g. cellular systems
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W84/00—Network topologies
  • H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
  • H04W84/04—Large scale networks; Deep hierarchical networks
  • H04W84/06—Airborne or Satellite Networks

Definitions

• Wireless applications include private land mobile radio (e.g., police, dispatch), cellular, PCS, satellite, wireless local loop, and others.
• Most wireless systems include an FDMA component, in which an available frequency spectrum is divided into multiple frequency bands, each corresponding to a different carrier frequency.
• FDMA component in which an available frequency spectrum is divided into multiple frequency bands, each corresponding to a different carrier frequency.
• ACI adjacent channel interference
• bandpass filtering is used to separate FDMA channels, and each FDMA channel is processed and demodulated separately thereafter.
• the filtering function is not perfect, adjacent channel interference is inevitably contained within the filtered signal.
• adjacent channel interference was ignored or treated as noise in the channel demodulation process.
• radio frequency (RF) processing techniques for compensating for adjacent channel interference have been proposed.
• the reconstructed signal can then be passed through a bandpass filter centered at the carrier of interest and subtracted from the received signal to remove the adjacent channel interference.
• a bandpass filter centered at the carrier of interest and subtracted from the received signal to remove the adjacent channel interference.
• analog signal processing using filters and mixers adds undesirable cost and size to a radio receiver, and since the analog components vary with the manufacturing process, such receivers provide a relatively unpredictable range of performance.
• subtracting a signal at radio frequency requires highly accurate carrier reconstruction and time alignment, as an error as small as half a cycle at radio frequency can cause the adjacent channel signal to double rather than diminish.
• such use of the adjacent channel carrier (phase and frequency) and envelope (amplitude) implicitly assumes that the radio channels are not dispersive.
• the symbol rate is sufficiently high that the radio transmission medium must be modeled to include time dispersion which gives rise to signal echoes.
• the proposed technique is not always practical for use in many present day applications.
• the present invention fulfills the above-described and other needs by providing a multi-signal cancelling demodulator in which signals are demodulated using information obtained during demodulation of other, adjacent signals.
• the cancelling demodulator of the present invention provides superior adjacent channel interference rejection.
• the cancelling demodulation can be conducted in either serial or parallel fashion.
• two channels are demodulated simultaneously in iterative fashion. Detected information obtained at each step in the iterative process is used as a priori information for demodulation in the following step.
• the stronger of two received signals is demodulated, and the resulting detected information is used as a priori information for demodulation of the weaker of the two received signals.
• the present invention teaches novel techniques for transforming symbols detected in one frequency band to corresponding symbols in adjacent frequency bands.
• the transformations are based in part on the carrier spacing existing between adjacent channels.
• the inter-channel transformations can also be applied in the context of channel estimation.
• FIG. 5 depicts an alternative embodiment of the baseband processor of Figure
• Figure 6 depicts a channel estimator according to the present invention.
• Figure 7 depicts an exemplary embodiment of the channel estimator of Figure 6.
• Figure 8 depicts an alternative embodiment of the channel estimator of Figure 6.
• Figure 1 depicts a radiocommunications system 100 in which the teachings of the present invention can be utilized.
• the communications system 100 includes first and second transmitters 101, 102, first and second transmit antennas 111, 112, a receive antenna 115, a radio processor 120 and a baseband processor 125.
• a first input symbol stream s is coupled to an input of the first transmitter 101, and an output of the first transmitter 101 is coupled to the first transmit antenna 111.
• a second input symbol stream i is coupled to an input of the second transmitter 102, and an output of the second transmitter 102 is coupled to the second transmit antenna 112.
• the first and second transmitters 101 , 102 map the digital input symbol streams s, i, respectively, to signal representations which are appropriate for the transmission medium existing between the transmitters 101,102 and the receiver 120.
• this mapping typically includes modulation and pulse shaping prior to transmission via the antennas 111, 112.
• the first transmitter 101 uses a first carrier frequency f a (corresponding to a first transmission frequency band a), while the second transmitter 102 uses a second carrier frequency f b (corresponding to a second transmission frequency band b).
• the transmitted signals pass through the transmission medium and are received at the receive antenna 115.
• the radio processor 120 converts the received antenna signal to first and second baseband sample sequences r a , r b , corresponding to the first and second carrier frequencies f a ,f b , respectively.
• the conversion to baseband is typically accomplished by filtering, amplifying, mixing, sampling and quantizing the received signals. For spread-spectrum systems, despreading is also included, either before or after the sampling and quantization operations.
• the baseband samples are typically complex, including both an in-phase (I) and quadrature (Q) component, though the invention is applicable to systems utilizing other types of samples as well.
• the radio processor 120 provides sufficient, or more than sufficient, statistics for detecting the transmitted symbols.
• the baseband processor 125 Given the received baseband signals r a , r b , the baseband processor 125 provides estimates of the transmitted symbol values. Soft, or reliability information may also be provided as is known in the art.
• Figure 2 depicts a conventional two-channel baseband processor 200 which can be used in the system 100 of Figure 1. As shown, the conventional baseband processor 200 includes first and second single-channel demodulators 201, 202. The first received baseband signal r a is coupled to an input of the first single-channel demodulator 201, and the second received baseband signal r b is coupled to an input of the second single- channel demodulator 202.
• the first and second single-channel demodulators 201, 202 provide estimates s, ⁇ of the first and second input symbol streams s, i (transmitted in the first and second frequency bands a, b), respectively.
• the first and second single- channel demodulators 201, 202 provide the estimates s, / ' using well known signal detection techniques. As described above, however, there is no inter-channel interaction between the two demodulation chains. As a result, the conventional processor 200 is not robust against adjacent channel interference.
• Figure 4 depicts a first embodiment of a two-channel baseband processor 400 according to the present invention.
• the processor 400 includes first and second summing devices 401, 402, first and second single-channel demodulators 411, 412, first and second reconstruction-in-other-band devices 421, 422, and a channel estimator 450.
• the first baseband signal r a is coupled to an additive input of the first summing device 401 and to a first input of the channel estimator 450.
• the second baseband signal r b is coupled to an additive input of the second summing device 402 and to a second input of the channel estimator 450.
• the channel estimator 450 provides four channel response estimates c a , C b , D a , d b which are coupled to first inputs of the first single-channel demodulator 411, the first reconstruction-in-other-band device 421, the second reconstruction-in-other-band device 422, and the second single- channel demodulator 412, respectively.
• Outputs of the first and second summing devices 401, 402 are coupled to second inputs of the first and second single-channel demodulators 411, 412, respectively.
• the first single-channel demodulator 411 provides a first output estimate s of the first input symbol stream s
• the second single-channel demodulator 412 provides a second output estimate f of the second input symbol stream /.
• the first and second estimates s, i are also coupled to second inputs of the first and second reconstruction- in-other-band devices 421, 422, respectively.
• a carrier spacing ⁇ 0 corresponding to the separation in radians per symbol period between the first and second carrier frequencies fj,f 2 , is coupled to a third input of each of the first and second reconstruction-in-other-band devices 421, 422.
• Outputs of the first and second reconstruction-in-other-band devices 421, 422 are coupled to subtractive inputs of the second and first summing devices 402, 401, respectively.
• the first and second summing devices 401, 402 are initially inhibited so that the first and second received baseband signals r a , r b pass straight through to the first and second single-channel demodulators, respectively.
• the first and second single-channel demodulators 411, 412 detect the first and second digital symbol streams s, i using known techniques.
• the first reconstruction- in-other-band device 421 uses the first detected symbol stream s to provide an estimate of the first signal s as it would appear in the second baseband (i.e., an estimate of adjacent channel interference in the second baseband due to the first signal s).
• the first and second summing devices 401, 402 are enabled.
• the first summing device 401 subtracts the second reconstructed signal (corresponding to the second signal as it would appear in the first band a) from the first received baseband samples r a
• the second summing device 402 subtracts the first reconstructed signal (corresponding to the first signal s as it would appear in the second band b) from the second received baseband samples r b .
• the first and second single-channel demodulators 411, 412 then use the outputs of the first and second summing devices 401, 402 to again estimate the first and second digital symbol streams s, i. Since an estimate of the adjacent channel interference in each band has been removed, the succeeding symbol estimates will be superior to the previous symbol estimates.
• the above described process can be repeated as appropriate. For example, the process can be repeated until a number of detected symbol values that change from iteration to iteration becomes constant or reaches some acceptable maximum allowable level. Knowledge of which symbols alternate in each iteration can be used afterward to erase those symbols or to adjust corresponding soft values, thereby improving any subsequent diversity combining or error correction decoding.
• the first and second single-channel demodulators 411, 412 can employ coherent or noncoherent detection methods. Additionally, the demodulators 411, 412 can include various forms of equalization, including linear, decision feedback, MLSE, or
• the demodulators 411, 412 can include Rake combining.
• the number of channel coefficients K, , K 2 for each signal s, i can be different.
• each channel response in equation (1) is modeled using just two coefficients without loss of generality.
• equation (1) represents a simplified model which can be expanded to account for additional adjacent channel interferers, thermal noise, etc.
• a model analogous to that of equation (1) can be provided for the second received baseband signal r b .
• the effective channel coefficients for the interfering signal spin, or rotate, with time n.
• Such rotation is highly undesirable for purposes of performing channel estimation, which assumes that channel coefficients vary slowly, if at all, with time.
• the despun, or unrotated coefficients D a may then be estimated, for example, by correlating the received signal samples with a spun-up or twisted (i.e., rotated) symbol sequence ( ⁇ ).
• ⁇ a spun-up or twisted symbol sequence
• Such a technique has been applied in a different context for estimating channel coefficients and a frequency error in a communications system subject to frequency inaccuracies. See, for example, Swedish Patent Application No. 8703796, issued April 2, 1989 to Raith, which is incorporated herein by reference.
• the reconstruction-in- other-band units 411, 412 can provide adjacent-band estimates of the symbol streams s, i using equation (5).
• the in-band estimates s, f are provided by the single-channel demodulators 411, 412 as described above, and the carrier spacing ⁇ 0 will be known for each given system.
• the carrier spacing ⁇ 0 can be estimated to compensate for transmitter and/or receiver frequency error.
• the channel parameter estimates c a (k), D a (k) can be obtained using either the previously mentioned correlation approach or the novel techniques described below with respect to Figures 6,
• Figure 5 depicts an alternative embodiment of a two-channel baseband processor 500 according to the present invention.
• the processor 500 includes a determine-strongest device 505, first and second single-channel demodulators 511, 512, a summing device 515 and a reconstruction-in-other-band device 520.
• the first and second received baseband signals r a , r b are coupled to first and second inputs of the determine-strongest device 505.
• a first output of the determine-strongest device 505 is coupled to an input of the first single-channel demodulator 511, and a second output of the determine-strongest device 505 is coupled to an additive input of the summing device 515.
• the determine-strongest device determines which of the transmitted signals is largest in some sense.
• the strongest signal can be obtained by measuring the relative power in each received baseband sample stream.
• the strongest signal can be determined by comparing a sum of squared magnitudes of channel estimates for the first signal in the first band with a sum of squared magnitudes of channel estimates of the second signal in the second band.
• Baseband samples corresponding to the band of the strongest received signal are provided as input to the first single-channel demodulator 511, which then detects symbol values corresponding to the strongest received signal.
• the detected values are in turn provided as input to the reconstruction-in-other- band device 520, which uses the carrier offset ⁇ 0 to reconstruct the strongest signal in the band corresponding to the weakest signal.
• the reconstructed signal is then subtracted from the baseband samples corresponding to the weakest signal in the summing device 515.
• the resulting signal is provided as input to the single-channel demodulator 512, which detects symbols corresponding to the weakest signal. Since the strongest received signal is inherently resilient to adjacent channel interference, and since an estimate of adjacent channel interference is removed from the weakest received signal, the detected symbols provided by the embodiment of Figure 5 are more accurate as compared to those provided by prior art systems.
• the single channel demodulators 511, 512 and the reconstruction-in-other-band device 520 operate as described above with respect to Figure 4.
• the reconstruction-in-other-band devices 421, 422, 520 of the embodiments of Figures 4 and 5 utilize complex channel coefficient estimates.
• the determine-strongest device 505 can utilize channel coefficient estimates, and the single-channel demodulators 411, 412, 511, 512 will utilize channel coefficient estimates when coherent detection is employed.
• the coefficient estimates can be scaled to account for noise in the estimation process.
• the present invention teaches that accurate channel estimates can be obtained using carrier * offset information in combination with the model provided above.
• a channel estimation device 600 includes a two-band channel estimator 610.
• x is a vector containing the channel coefficient estimates
• S is a matrix containing symbol values s( ⁇ ) and /'( «)
• r is a vector containing received samples for the first baseband sample stream r a ( ⁇ ).
• a third channel parameter estimate C b output by the third single-channel estimator 813 (corresponding to the first signal s in the second band b) is coupled to a first input of the second reconstruction-in-same-band device 822.
• the carrier spacing ⁇ 0 is coupled to a second input of the second reconstruction-in-same-band device 822, and symbol values for the second signal / are coupled to a third input of the second reconstruction-in-same-band device 822.
• An output of the second reconstruction-in- same-band device 822 is coupled to a subtractive input of the second summing device 802, and an output of the second summing device 802 is coupled to an input of the fourth single-channel estimator 814.
• the fourth single-channel estimator 814 provides a fourth channel parameter estimate d b corresponding to the second signal / as received in the second band b.
• the first summing device then subtracts the reconstructed signal from the first received baseband signal r a to provide a canceled signal which represents an estimate of the interfering signal / as received in the first band a.
• the second single-channel estimator 812 uses the canceled signal to provide the second channel estimate D a corresponding to the second signal i in the first band a. Operation of the second single-channel estimator 812 is analogous to operation of the first single-channel estimator 811 as described above.
• the approach of demodulating the stronger of two adjacent channel signals and then using the result to assist demodulation of the weaker of the two signals works well when the signals are of significantly different levels.
• the generalization of this approach is to sort the signals received in a raster of adjacent frequency channels into signal strength order, and to demodulate them in order strongest to weakest.
• the apparent problem of needing a first signal s to decode a second signal /, and conversely needing the second signal i to decode the first signal s, can also be solved using the Viterbi algorithm, also known as Maximum Likelihood Sequence Estimation (MLSE).
• MLSE Maximum Likelihood Sequence Estimation
• One method of applying MLSE is to assume all possible results for the second signal i in turn and to determine a separate estimate for the first signal s in association with each assumption for the second signal i. Then, for each separate estimate of the first signal s, an estimate for the second signal / is determined with the constraint that the estimate for the second signal / must logically be the same as that originally assumed in obtaining the corresponding estimate for the first signal s.
• the estimate for the second signal / is obtained in the form of a likelihood measure or "metric" that estimates or assumes that the second signal / is correct.
• the likelihood metrics for each of the separate second-signal assumptions and associated first-signal estimates are then compared and the best likelihood value is selected for the joint decision of the first signal s and the second signal /.
• equation (5) provides the expected value of the received signal in terms of a current first-signal symbol s( ⁇ ), the previous first-signal symbol s(n-l), the current second-signal symbol (rotated) (ri) and the previous second-signal symbol i'(n-
• equation (9) provides the expected value of the received signal in the adjacent channel as a function of the same four symbols.
• the above process is the familiar Viterbi MLSE process as applied to the joint demodulation of two adjacent channel signals.
• the process progresses by demodulating signal samples received successively in time in two adjacent channels, although the method can be extended to more than two adjacent channels by expanding the number of retained "chains" of partially-decided symbols, known as the path history or Viterbi states.
• s ⁇ , s b , s c . . . refer to symbols transmitted on successive adjacent channels ⁇ , b, c . . ., c carving(0), c ⁇ ( ⁇ ) describe the influence of the current symbol s ⁇ ( ⁇ ) and the previous symbol s ⁇ (n- ⁇ ) on the signal r ⁇ (n) in channel ⁇ at instant n.
• the prime values describe the influence on the current channel of symbols transmitted in a higher frequency adjacent channel while the double prime values describe the influence on the current channel of symbols transmitted in a lower frequency adjacent channel.
• the signal value r b ( ⁇ ) received in that channel at instant n is seen to depend on six symbols, namely the two symbols s ⁇ ( ⁇ ), s ⁇ (n-l) in the lower adjacent channel, the two symbols s b ( ⁇ ), s b (n- ⁇ ) of the second channel b itself, and the two symbols s c ( ⁇ ), s c (n- ⁇ ) of the upper adjacent channel.
• the six symbols can take on any of two to the power six, or sixty-four, possible values, if each symbol is a binary symbol.
• the selected metric and s ⁇ (n-l) value is then stored in association with each of the thirty-two surviving hypotheses.
• MLSE processing then progresses to process the value r c ( ⁇ ) of the next frequency channel received at the same instant n. This is dependent on two symbols s n), s d (n- ⁇ ) not previously hypothesized. Adding those to the list expands the number of hypotheses from thirty -two to one hundred and twenty-eight (128).
• pairs of states differing only in their associated value of s b (n- ⁇ ) are compared and that one of the pair having the best metric is selected, along with the associated s b (n- ⁇ ) value.
• the number of states is reduced by two to sixty-four.
• the process continues to first expand the number of states by four and then to reduce it by two until the final channel in a series of adjacent channels is processed, which does not suffer from interference in a yet higher channel that can be dealt with by the method (i.e., any higher channel interference is of an unknown kind).
• the number of remaining states is then equal to two to the power of the number of channels, and each state is associated with one possible hypothesis for the symbols s a ( ⁇ ), s b (n-l) . . . together with associated decisions for symbols . ⁇ (n-l), s b (n-l) . . ..
• the number of states is small after processing only the first signal sample in the first channel r ⁇ (l), and thereafter doubles until a steady state is reached of M ⁇ ' 1)+1 for all channels processed except the last, for which the number of retained states is M ;( 1) as with time-sequential MLSE.
• j in the above is only equal to the number of contiguous adjacent channels (without a gap) that must be processed in this way.
• a gap is created, truncating the value of j, both when a channel contains a signal weaker than the others that can be ignored, or contains a signal stronger than the others that can be processed without knowledge of the adjacent channels.
• the stronger signals are thus processed ahead in the time dimension first and then subtracted out to create gaps in the frequency dimension which reduce the number of contiguous channels that might have to be processed using MLSE along the frequency dimension.
• ⁇ can be used to provide channel estimates for the demodulator embodiments of Figures 4 and 5.
• the baseband processor can receive samples corresponding to multiple antennas, beams, polarizations, or other types of receive channels.
• micro-diversity and/or macro-diversity can be used. Cancellation is typically best performed using detected symbols after diversity combining has been applied.
• Diversity combining can be, for example, metric combining or interference rejection combining.
• the present invention can be combined with other receiver techniques.
• per-survivor processing can be applied in which multiple sets of channel estimates are kept (corresponding to multiple possible detected symbol sequences).
• multiple cancellation operations can be performed (corresponding to different detected symbol sequences).
• a symbol-spaced example is given, those skilled in the art will appreciate that the present invention is also readily applied to fractionally-spaced reception.
• the channel estimation can be adaptive, for example in a D-AMPS system where the channels change with time within a TDMA slot.
• the receiver can perform further signal processing, such as de-interleaving, decoding of error correction or error detection codes, and decryption.
• coding and modulation are combined, and it will thus be appreciated that demodulation as used herein can include decoding.

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