CA2516525A1 - Interference canceling matched filter (icmf) - Google Patents
Interference canceling matched filter (icmf) Download PDFInfo
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- CA2516525A1 CA2516525A1 CA 2516525 CA2516525A CA2516525A1 CA 2516525 A1 CA2516525 A1 CA 2516525A1 CA 2516525 CA2516525 CA 2516525 CA 2516525 A CA2516525 A CA 2516525A CA 2516525 A1 CA2516525 A1 CA 2516525A1
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- 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
- H04L25/0202—Channel estimation
- H04L25/0224—Channel estimation using sounding signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/345—Interference values
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
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- 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—Space-time coding
- H04L1/0631—Receiver arrangements
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- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Noise Elimination (AREA)
- Mobile Radio Communication Systems (AREA)
Description
INTER!'ER~1CE CANCELxt~TG IdATC~D FILTER (If~dF) Fi~ld a~ tb~ Iavantivxr The present invention relates to wireless communications systems, such as cellular communications systems, and, more particularly, to filtering xeceived wireless signals to reduce unwanted interference, e.g., as required by the Down Link Advanced Receiver Performance (DARP) capable receivers standa;.dized by the 3GPP.
Backgrt~und of the Invention The present invention relates to wireless Communications systems, such as cellular communications systems, and, mare particularly, to filtering received wireless signals to reduce unwanted interference.
one type of interference filter used in wireless communications systems is the interference canceling matched filter (ICMF). AN ICMF performs "blind" interference cancellation (BZC), as it does not need the knowledge of the channel response of the interferers. Yet, the channel response of the wanted or desired signal still has to be known or be estimated. Further detai7.s of the ICMF may be found in an article by Slock et a1_ entitled "An Interference Canceling Multichannel Matched Fi.lter,"
Globecom Nov. 1996. Moreover, the potential application of ICMFs to Global System for Mobile Communication (GSM) Single Antenna Interference Cancellation (SAZC) is discussed in and article to 5lock et al. entitled "Cochannel Interference Cancellation Within the Current GSM Standard," IEEE
International Conference on Universal personal Communications, 1996.
Hr3.s~f Desar~~tfoa of the Dxawi~s FIGS. 1A and 1~ are schematic block diagrams of a GSM
receiver ~.n accordance with the prior art and a aARP-capable ICMF GSM receiver in accordance with the present invention, respectively.
FIG. 2 is a schematic black diagram of the ICMF and channel estimator of FIG. 1B illustrated in greater detail.
FIG_ ~ is a schematic block diagram of the Wiener filter of FzG. 2 illustrated in greater detail.
FIG. 9 is a graph of simulated performance results for the DARP-capable ICMF GSM receiver of FIG. 1E.
Detailed Deacri tioi7 Of th6 IayetLtiori The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which g~referred embodiments of the invention are shown_ This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Referring initially to FIG. 1A, a conventional GSM
receiver 20 zncludes a derotator 21 into which a received GSM signal is input, a matched filter 22 connected to the output of the derotator, a channel estimator 23 also connected to the output of the derotatox and to the matched filter, and a Vitexbi equalizer 24 connected to the outputs of the matched filter and channel estimator.
By way of comparison, an DARP-capable GSM receiver 30 in accaxdance with the present invention is now described with reference to FTG. 18, The DARP-capable G5M receiver 30 illustratively includes an ICMF 32 connected to the output
Backgrt~und of the Invention The present invention relates to wireless Communications systems, such as cellular communications systems, and, mare particularly, to filtering received wireless signals to reduce unwanted interference.
one type of interference filter used in wireless communications systems is the interference canceling matched filter (ICMF). AN ICMF performs "blind" interference cancellation (BZC), as it does not need the knowledge of the channel response of the interferers. Yet, the channel response of the wanted or desired signal still has to be known or be estimated. Further detai7.s of the ICMF may be found in an article by Slock et a1_ entitled "An Interference Canceling Multichannel Matched Fi.lter,"
Globecom Nov. 1996. Moreover, the potential application of ICMFs to Global System for Mobile Communication (GSM) Single Antenna Interference Cancellation (SAZC) is discussed in and article to 5lock et al. entitled "Cochannel Interference Cancellation Within the Current GSM Standard," IEEE
International Conference on Universal personal Communications, 1996.
Hr3.s~f Desar~~tfoa of the Dxawi~s FIGS. 1A and 1~ are schematic block diagrams of a GSM
receiver ~.n accordance with the prior art and a aARP-capable ICMF GSM receiver in accordance with the present invention, respectively.
FIG. 2 is a schematic black diagram of the ICMF and channel estimator of FIG. 1B illustrated in greater detail.
FIG_ ~ is a schematic block diagram of the Wiener filter of FzG. 2 illustrated in greater detail.
FIG. 9 is a graph of simulated performance results for the DARP-capable ICMF GSM receiver of FIG. 1E.
Detailed Deacri tioi7 Of th6 IayetLtiori The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which g~referred embodiments of the invention are shown_ This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Referring initially to FIG. 1A, a conventional GSM
receiver 20 zncludes a derotator 21 into which a received GSM signal is input, a matched filter 22 connected to the output of the derotator, a channel estimator 23 also connected to the output of the derotatox and to the matched filter, and a Vitexbi equalizer 24 connected to the outputs of the matched filter and channel estimator.
By way of comparison, an DARP-capable GSM receiver 30 in accaxdance with the present invention is now described with reference to FTG. 18, The DARP-capable G5M receiver 30 illustratively includes an ICMF 32 connected to the output
2 of the deratatar 21, and a channel estimator 33 also connected to the output of the deratation stage and to the ICMF. As schematically illustrated in the drawing, the ICMF
32 and Channel estimator 33 may advantageously be inserted into the typical G5M receiver configuration in place of the matched filter 22 and corresponding channel estimator 23 without the need to change the standard derotator 21 and Viterbi equalizer 24, as will lie appreciated more fully from the discussion below.
Generally speaking, the present IC:dF SAZC approach uses the input data as though there were several "virtual" input antennas. It then uses traditional beam-forming techniques to combine the virtual antennas to improve the signal-to-interference-noise ratio (SINK) far the desired signal.
Considered alternately, the SAIL ZGMF 32 functions as an adaptive space-time filter.
More particularly, the premise behind the SAIC zCMF 32 is that by exploiting oversampling and the BPSK nature of the GMSK signal, a virtual antenna array can be established.
Once the virtual antenna array and the knowledge of the channel response of the wanted signal is established, Conventional beamforming technology can be used for the interference cancellation. The underlying assumption far the beamforming is that the interference is spatially orland temporally correlated and it arrives at different paths from the wanted signal. This assumption is statistically true in the GSM fading environment.
The beamforming algorithm used in the ICMF 32 i,s based on the Generalized Sidelobe Canceller (GSC3 in the Griffiths et al. article entitled "An Alternative Approach to Linearly Constrained Adaptive Beamforming," IEEE Trans. Antennas Propag., vol AP-30, pp 27-39, Jan. 1982, Referring now to FIG, 2, the SRIC IGMF 32 and channel estimation stage 33 are
32 and Channel estimator 33 may advantageously be inserted into the typical G5M receiver configuration in place of the matched filter 22 and corresponding channel estimator 23 without the need to change the standard derotator 21 and Viterbi equalizer 24, as will lie appreciated more fully from the discussion below.
Generally speaking, the present IC:dF SAZC approach uses the input data as though there were several "virtual" input antennas. It then uses traditional beam-forming techniques to combine the virtual antennas to improve the signal-to-interference-noise ratio (SINK) far the desired signal.
Considered alternately, the SAIL ZGMF 32 functions as an adaptive space-time filter.
More particularly, the premise behind the SAIC zCMF 32 is that by exploiting oversampling and the BPSK nature of the GMSK signal, a virtual antenna array can be established.
Once the virtual antenna array and the knowledge of the channel response of the wanted signal is established, Conventional beamforming technology can be used for the interference cancellation. The underlying assumption far the beamforming is that the interference is spatially orland temporally correlated and it arrives at different paths from the wanted signal. This assumption is statistically true in the GSM fading environment.
The beamforming algorithm used in the ICMF 32 i,s based on the Generalized Sidelobe Canceller (GSC3 in the Griffiths et al. article entitled "An Alternative Approach to Linearly Constrained Adaptive Beamforming," IEEE Trans. Antennas Propag., vol AP-30, pp 27-39, Jan. 1982, Referring now to FIG, 2, the SRIC IGMF 32 and channel estimation stage 33 are
3 now described in further detail. The ICMf 32 includes a main branch 40 of the virtual antenna array, a signal blacking branch 41 of the array, and a 2D ~i.e., virtual spatial and temporal) adaptive Wiener filter a2_ The virtual antenna array results from the oversampling of the received signal and the separation of the real (I) and imaginary (Q) parts of the signal. In the illustrated emtaodiment, the signal y~R(k) is the "on sample" real signal component, yoi (3e) i s the on sample .maginary signal component, yxR(k) is the "off" or "over" ,:,ample real signal component, and ylx(k) is the off sample imaginary signal component. As will be appreciated by those skilled in the art, the ovArsampled samples y~x(k)r Ysx(k1 may be treated as independent channels of antennae. The rationale behind the separation of the I/Q parts is due to the nature of the GMSK
modulation. After derotation, the GMSK signal may be treated as a BPSH signal, and hence the I and Q channels are considered independent to some extent (although the intersymbol interference (ISI) compromises this assumption somewhat).
In a GSG beamformer, the main branch is a conventional receiver filter, In the ICMF 32, the main branch 4o is a mufti-channel matched filter including respective filters 43a-43d for each of the signal components yoa(k). yo=(x).
yix(k), and y1=(k), and a summer 4~1 for summing the outputs of the filter blocks. The output xo(k) of the main branch 44 (i.e., the summer 44 output) contains both the wanted or desired signal and the undesired interference. The wanted signal is enhanced in the main branch 40 becau$e of the summation of the phase-aligned s~.gnal of the matched tiJ.ter output, as will be appreciated by those skilled in the art.
The signal blocking branch 4I implements a transformation that generates a group of sub-channels xl(k), x2(k), and x3(k) including only the interference. Mare particularly, the signal blocking branch 41 implements a blocking transformation using a plurality of signal blocking filters 45s~-45f and summers 46a-45c and corresponding to a transformation matrix T(z~ defined as follows:
Hor ~z) - NoR U) 0 0 ~'~z) _ din ~z) 0 " j~oR (z) 0 ( 1 ) ~~r~Z) Q Q -Hox~y) Generally speaking, the blocking algorithm finds the null space in the observation space of the array. Assuming there are N virtual antennae, the dimension of the null space would be N I since there is only one wanted signal (i.e. , the dimension of the signal space is one) . It should be noted that other approaches may be used to form different transformation matrices, if desired, as will be appreciated by those skilled in the art.
Turning now to the adaptive space-time Wiener filter 42, space-time two-dimensional processing is used because, relative to the sampling rate, the interference is broadband. Using time domain filtering will compensate for the delays caused by the signal blocking filters 45a-45f and phase-align the interference with the output of the main branch 40. The Wiener filter 42 illustratively includes a Wiener filter estimator 4? receiving as inputs the output xfl(k) of the main branch 40 and the outputs xi(k), x2(k), and x3(k) of the signal blocking branch 41. A Wiener filter 48 receives the outputs il(k), xz(k), and x3(k) of the signal blocking branch 41 as well as the output W of the Wiener filter estimator 47. Furthermore, a summer subtracts the Output of the Wienex filter 48 Pram the output xo(k) of the main branch 40 to provide the final filtered signal, u(k).
The structure of the two-dimensional Wiener filter 48 having an oversampling ratio of two is now described with reference to FIG. 3. The filter 4~ inc~.udes a respective branch ~Oa-5Qc fox each of the sub-channel outputs xi(k), x2(k), and ,x~(k) of the signal blocking branch 41. Each branch 50a-50a includes a plurality of parallel gain multiplier stages 52 each having an input and an output, and all of the outputs are connected to a summer 53. Moreover, a respective delay stage 51 is connected bstween the inputs oz Eaoh adjacent pazr of gain multiplier stages 52 such that the delays stages are series-connected to one another as shown. The outputs of the branch summers S3 are in t urn summed by a summer 54, which provides the output of the Wiener filter 48, In general, the solution of the 2D Wiener f~.lter is W
with the length of (N-1) ~i:
W~(BxB)-~B"a, (2) where Q=~xo~~-~). xotM). - , xo(Iv')~r.
and xo(k) is the output of the main branch 40. R is the number of symbols in a burst, and M is the number o~ taps of the filter in the time domain, where x~ (~ _ ]) ... xi (~) , .. . . , xH_~ t~ .-1) . . . xN_~ (a) $ - xi (,M) .. . xi (1) . .. .. xN_i (.~) . .. x~,_~ (~) _ ( 9 ) x~ (~) . .. x~ (X' - M + 1) - . ... xN_~ W ) ... xN_~ (g ' M ~-1) Furthermore, x"(k)'s are the output of the signal blocking branch 41.
The channel estimation stage 33 estimates the channel impulse response (CIR) of the wanted signal. This may be done in accordance with various techniques that will be readily appreciated by those skilled in the art and therefore z~equires no further discussion herein.
Applicants simulated the receiver 30 and have noted improvements with respect to the prior art receiver 20 for known desired signals CIR using t.Ze ICMF SAIL approach in accordance with the present invention. The results of vj~ee simulations are shovrn in the graph cf FIG, 9. The block error rate of the dARP~capable GSM receiver 30 was collected and compared with that of the conventional receiver 2Q. The logical channel used in the simulation is CS-1. fhe fading channel is TU50km/h-195DMHz and the int~rference configuration is DTS-I as proposed in GP-042829, Change Request - 95.005 CR 092 Rev 2., 3GPP TSG~GERAN Meeting # 22, GP-042829, Nov_ 2009. An oversampling ratio of 1 (I~ = 2) and 2 (N = 4) and the temporal filter length of M = 1, 2, and 3 were used in the simulations as shown. Generally speaking, the DARP-capable GSM receiver 30 demonstrated up to 5 dB
improvement under the simulation (CS-1, TU50km/h-1950MHz, DTS-1), provided that the channel impulse response of the wanted signal was known.
To provide the necessary accuracy to achieve the DARP
requirements, Applicants theorize without wishing to be bound thereto that certain channel estimation snhanCements may be used. Twa such enhancements may include: (1) CIR
improvement with the constant modulus property of the interference taken znto consideration: and (2) using subspace fitting based channel estimation methods such as those reported in the Liang et al, article entitled "A Tuo-Stage Hybrid Approach far CCI/ISI Reduction with Space-Time Processing," IEEE Communications Letters, pp. 163--165, Nav_ 1997, and the Klang et al. article entitJ.ed "Structured semi-Blind interference Rejection in Dispersive Multichannel Systems," IEEE Transactions on Signal Processing, Volume 50, Issue 8, August 2002. Generally sQeaking, the approaches in (2) take into account the interference in the optimization target, and these methods use an eigenvalue or singular decomposition computation.
Some advantages of the SF~IC ICMF apgroach outlined shave include its relative sim~.li~:ity (i.e,, rela~.ivel~r 104J
computational complexity) and robustness (5..e., it makes very fe4r assemptions about the scux~ce of the interference) , In addition, this approach allows the existing GSrI Viterbi equalizer structure to be used, as the solution is integrated as a pre-processing step on the input data, as discussed further above.
Many modifications arid other embodiments of the invention will come to the mind of one skilled in the art having the benefit of the teachings presented in the foregoing descriptions and the associated drawings.
'Iherefare, it is understood that the invention is not to be limited to the specific embodiments disclosed, and that modifications and emlaodiments are intended to be included within the scope of the invention.
modulation. After derotation, the GMSK signal may be treated as a BPSH signal, and hence the I and Q channels are considered independent to some extent (although the intersymbol interference (ISI) compromises this assumption somewhat).
In a GSG beamformer, the main branch is a conventional receiver filter, In the ICMF 32, the main branch 4o is a mufti-channel matched filter including respective filters 43a-43d for each of the signal components yoa(k). yo=(x).
yix(k), and y1=(k), and a summer 4~1 for summing the outputs of the filter blocks. The output xo(k) of the main branch 44 (i.e., the summer 44 output) contains both the wanted or desired signal and the undesired interference. The wanted signal is enhanced in the main branch 40 becau$e of the summation of the phase-aligned s~.gnal of the matched tiJ.ter output, as will be appreciated by those skilled in the art.
The signal blocking branch 4I implements a transformation that generates a group of sub-channels xl(k), x2(k), and x3(k) including only the interference. Mare particularly, the signal blocking branch 41 implements a blocking transformation using a plurality of signal blocking filters 45s~-45f and summers 46a-45c and corresponding to a transformation matrix T(z~ defined as follows:
Hor ~z) - NoR U) 0 0 ~'~z) _ din ~z) 0 " j~oR (z) 0 ( 1 ) ~~r~Z) Q Q -Hox~y) Generally speaking, the blocking algorithm finds the null space in the observation space of the array. Assuming there are N virtual antennae, the dimension of the null space would be N I since there is only one wanted signal (i.e. , the dimension of the signal space is one) . It should be noted that other approaches may be used to form different transformation matrices, if desired, as will be appreciated by those skilled in the art.
Turning now to the adaptive space-time Wiener filter 42, space-time two-dimensional processing is used because, relative to the sampling rate, the interference is broadband. Using time domain filtering will compensate for the delays caused by the signal blocking filters 45a-45f and phase-align the interference with the output of the main branch 40. The Wiener filter 42 illustratively includes a Wiener filter estimator 4? receiving as inputs the output xfl(k) of the main branch 40 and the outputs xi(k), x2(k), and x3(k) of the signal blocking branch 41. A Wiener filter 48 receives the outputs il(k), xz(k), and x3(k) of the signal blocking branch 41 as well as the output W of the Wiener filter estimator 47. Furthermore, a summer subtracts the Output of the Wienex filter 48 Pram the output xo(k) of the main branch 40 to provide the final filtered signal, u(k).
The structure of the two-dimensional Wiener filter 48 having an oversampling ratio of two is now described with reference to FIG. 3. The filter 4~ inc~.udes a respective branch ~Oa-5Qc fox each of the sub-channel outputs xi(k), x2(k), and ,x~(k) of the signal blocking branch 41. Each branch 50a-50a includes a plurality of parallel gain multiplier stages 52 each having an input and an output, and all of the outputs are connected to a summer 53. Moreover, a respective delay stage 51 is connected bstween the inputs oz Eaoh adjacent pazr of gain multiplier stages 52 such that the delays stages are series-connected to one another as shown. The outputs of the branch summers S3 are in t urn summed by a summer 54, which provides the output of the Wiener filter 48, In general, the solution of the 2D Wiener f~.lter is W
with the length of (N-1) ~i:
W~(BxB)-~B"a, (2) where Q=~xo~~-~). xotM). - , xo(Iv')~r.
and xo(k) is the output of the main branch 40. R is the number of symbols in a burst, and M is the number o~ taps of the filter in the time domain, where x~ (~ _ ]) ... xi (~) , .. . . , xH_~ t~ .-1) . . . xN_~ (a) $ - xi (,M) .. . xi (1) . .. .. xN_i (.~) . .. x~,_~ (~) _ ( 9 ) x~ (~) . .. x~ (X' - M + 1) - . ... xN_~ W ) ... xN_~ (g ' M ~-1) Furthermore, x"(k)'s are the output of the signal blocking branch 41.
The channel estimation stage 33 estimates the channel impulse response (CIR) of the wanted signal. This may be done in accordance with various techniques that will be readily appreciated by those skilled in the art and therefore z~equires no further discussion herein.
Applicants simulated the receiver 30 and have noted improvements with respect to the prior art receiver 20 for known desired signals CIR using t.Ze ICMF SAIL approach in accordance with the present invention. The results of vj~ee simulations are shovrn in the graph cf FIG, 9. The block error rate of the dARP~capable GSM receiver 30 was collected and compared with that of the conventional receiver 2Q. The logical channel used in the simulation is CS-1. fhe fading channel is TU50km/h-195DMHz and the int~rference configuration is DTS-I as proposed in GP-042829, Change Request - 95.005 CR 092 Rev 2., 3GPP TSG~GERAN Meeting # 22, GP-042829, Nov_ 2009. An oversampling ratio of 1 (I~ = 2) and 2 (N = 4) and the temporal filter length of M = 1, 2, and 3 were used in the simulations as shown. Generally speaking, the DARP-capable GSM receiver 30 demonstrated up to 5 dB
improvement under the simulation (CS-1, TU50km/h-1950MHz, DTS-1), provided that the channel impulse response of the wanted signal was known.
To provide the necessary accuracy to achieve the DARP
requirements, Applicants theorize without wishing to be bound thereto that certain channel estimation snhanCements may be used. Twa such enhancements may include: (1) CIR
improvement with the constant modulus property of the interference taken znto consideration: and (2) using subspace fitting based channel estimation methods such as those reported in the Liang et al, article entitled "A Tuo-Stage Hybrid Approach far CCI/ISI Reduction with Space-Time Processing," IEEE Communications Letters, pp. 163--165, Nav_ 1997, and the Klang et al. article entitJ.ed "Structured semi-Blind interference Rejection in Dispersive Multichannel Systems," IEEE Transactions on Signal Processing, Volume 50, Issue 8, August 2002. Generally sQeaking, the approaches in (2) take into account the interference in the optimization target, and these methods use an eigenvalue or singular decomposition computation.
Some advantages of the SF~IC ICMF apgroach outlined shave include its relative sim~.li~:ity (i.e,, rela~.ivel~r 104J
computational complexity) and robustness (5..e., it makes very fe4r assemptions about the scux~ce of the interference) , In addition, this approach allows the existing GSrI Viterbi equalizer structure to be used, as the solution is integrated as a pre-processing step on the input data, as discussed further above.
Many modifications arid other embodiments of the invention will come to the mind of one skilled in the art having the benefit of the teachings presented in the foregoing descriptions and the associated drawings.
'Iherefare, it is understood that the invention is not to be limited to the specific embodiments disclosed, and that modifications and emlaodiments are intended to be included within the scope of the invention.
Claims
1. A wireless communications device comprising:
a virtual antenna array receiving signal components of a wireless communications signal having a training sequence associated therewith;
a multi-channel impulse response estimator receiving the signal components from said virtual antenna array and estimating multi-channel impulse responses based upon the training sequence;
a main signal branch comprising a multi-channel matched filter for filtering signals from said virtual antenna array based upon the estimated multi-channel impulse responses to generate a main signal channel;
a signal blocking branch comprising a plurality of blocking filters for estimating at least one interference channel based upon the estimated multi-channel impulse responses and a blocking transformation; and a space-time filter for filtering the main signal channel based upon the at least one interference channel to remove co-channel interference therefrom.
a virtual antenna array receiving signal components of a wireless communications signal having a training sequence associated therewith;
a multi-channel impulse response estimator receiving the signal components from said virtual antenna array and estimating multi-channel impulse responses based upon the training sequence;
a main signal branch comprising a multi-channel matched filter for filtering signals from said virtual antenna array based upon the estimated multi-channel impulse responses to generate a main signal channel;
a signal blocking branch comprising a plurality of blocking filters for estimating at least one interference channel based upon the estimated multi-channel impulse responses and a blocking transformation; and a space-time filter for filtering the main signal channel based upon the at least one interference channel to remove co-channel interference therefrom.
Priority Applications (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2516525 CA2516525A1 (en) | 2005-08-15 | 2005-08-15 | Interference canceling matched filter (icmf) |
| EP06775111A EP1925089A4 (en) | 2005-08-15 | 2006-08-15 | Interference canceling matched filter (icmf) and related methods |
| CN200680037224.3A CN101283510B (en) | 2005-08-15 | 2006-08-15 | Interference canceling matched filter (ICMF) and related methods |
| CA2619149A CA2619149C (en) | 2005-08-15 | 2006-08-15 | Interference canceling matched filter (icmf) and related methods |
| PCT/CA2006/001336 WO2007019688A1 (en) | 2005-08-15 | 2006-08-15 | Interference canceling matched filter (icmf) and related methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2516525 CA2516525A1 (en) | 2005-08-15 | 2005-08-15 | Interference canceling matched filter (icmf) |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA2516525A1 true CA2516525A1 (en) | 2007-02-15 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA 2516525 Abandoned CA2516525A1 (en) | 2005-08-15 | 2005-08-15 | Interference canceling matched filter (icmf) |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP1925089A4 (en) |
| CN (1) | CN101283510B (en) |
| CA (1) | CA2516525A1 (en) |
| WO (1) | WO2007019688A1 (en) |
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| CN101771638B (en) * | 2010-02-23 | 2013-01-30 | 华为终端有限公司 | Channel estimation method and device |
| CN101827051B (en) * | 2010-04-08 | 2013-06-05 | 华为终端有限公司 | Method and equipment for restraining interference |
| CN102158444A (en) * | 2011-03-04 | 2011-08-17 | 京信通信技术(广州)有限公司 | Oversampling interference rejection combining method and device |
| US9031526B2 (en) | 2012-06-19 | 2015-05-12 | Motorola Solutions, Inc. | Method and apparatus for in-channel interference cancellation |
| WO2015058361A1 (en) * | 2013-10-22 | 2015-04-30 | 华为技术有限公司 | Interference cancellation method and apparatus |
| CN105530078A (en) * | 2014-09-29 | 2016-04-27 | 联芯科技有限公司 | Communication packet burst detection method and communication packet burst detection device for receiver |
| CN106788803B (en) * | 2016-11-18 | 2020-09-15 | 北京锐安科技有限公司 | Method and device for measuring uplink DCH channel power in WCDMA system |
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| US6314147B1 (en) * | 1997-11-04 | 2001-11-06 | The Board Of Trustees Of The Leland Stanford Junior University | Two-stage CCI/ISI reduction with space-time processing in TDMA cellular networks |
| EP0964530A1 (en) * | 1998-06-05 | 1999-12-15 | Siemens Aktiengesellschaft | Radio communications receiver and interference cancellation method |
| DE60029740T2 (en) * | 2000-02-16 | 2007-10-18 | Lucent Technologies Inc. | Apparatus, system and method for collision resolution in a time critical radio communication system |
| US6760388B2 (en) * | 2001-12-07 | 2004-07-06 | Qualcomm Incorporated | Time-domain transmit and receive processing with channel eigen-mode decomposition for MIMO systems |
| EP1404046B1 (en) | 2002-09-26 | 2006-11-08 | Lucent Technologies Inc. | Equalizer with two space-time filters and with a selector for choosing the filter with the best symbol estimate |
| US7295636B2 (en) * | 2003-03-28 | 2007-11-13 | Texas Instruments Incorporated | Linear single-antenna interference cancellation receiver |
| US7801248B2 (en) | 2004-11-19 | 2010-09-21 | Qualcomm Incorporated | Interference suppression with virtual antennas |
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2005
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- 2006-08-15 EP EP06775111A patent/EP1925089A4/en not_active Withdrawn
- 2006-08-15 CN CN200680037224.3A patent/CN101283510B/en not_active Expired - Fee Related
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| CN101283510B (en) | 2012-05-02 |
| EP1925089A4 (en) | 2008-10-29 |
| WO2007019688A1 (en) | 2007-02-22 |
| EP1925089A1 (en) | 2008-05-28 |
| CN101283510A (en) | 2008-10-08 |
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