Abstract:
Interference in a received orthogonal frequency division multiplexing (OFDM) symbol, modulated according to selected constellation points s k , is reduced. The symbol includes a set of pilot signals and a set of data signals y k , where k is a number of consecutive subcarriers used for the pilot and the data signals. The pilot signals are thresholded to detect interfering pilot signals, which are then erased. Channels Ĥ k  are estimated using remaining pilot signals. The set of data signals are decoded based on the estimated channels Ĥ k , and, for each bit b i  in the set of data signals, a logarithmic likely ratio (LLR) 
             log   ⁢         ∑         s   k     :     b   i       =   0               ⁢     1              y   k     -         H   ^     k     ⁢     s   k              2             ∑         s   k     :     b   i       =   1               ⁢     1              y   k     -         H   ^     k     ⁢     s   k              2                 
is determined. The LLR is an indicator of the likely interference.

Description:
FIELD OF THE INVENTION 
     This invention relates generally to wireless communications, and more particularly to encoding and decoding orthogonal frequency division multiplexing (OFDM) signals subject to partial-band and partial-time interference. 
     BACKGROUND OF THE INVENTION 
     The number of wireless communication modalities sharing the same frequency band continues to increase. This means that simultaneous transmissions are more likely to interfere with each other, particularly if an interfering transmitter is close to an intended receiver. This decreases the reliability of the wireless communications. 
     Interference rejection has been used to protect against partial-band and partial-time interference. Two known methods can reject interference: erasure and clipping. For the erasure, the receiver detects whether a signal sample is corrupted by interference, and erases the sample with a zero. For the clipping, the sample is replaced with a neighboring uncorrupted sample. 
     Another approach uses message passing and models interference as equivalent Gaussian noise. The existence of interference is detected, and its variance is estimated. Then, the log-likelihood ratio (LLR) of received symbols can be determined based on the estimated interference variance. Soft-iterative decoding is conducted using the LLRs as input to channel decoder to resolve the interference. 
     OFDM networks are used for high data-rate transmission in multipath channels, e.g., networks according to the IEEE 802.11a and 802.11g (WiFi) standards. Those networks use a fast-Fourier transform (FFT) to convert inter-symbol-interference (ISI) time-domain channels into parallel frequency-domain channels. Thus, symbols are transmitted without ISI in the frequency domain. An OFDM symbol includes a set of data signals and a set of pilot signals, each on a different subcarrier. Known symbols are transmitted using the set of pilot signals to estimate the channels for the set of data signals. 
     Partial-band and partial-time interference (PBPTI) can corrupt the transmission of wideband OFDM signals. On the unlicensed radio spectrum, Bluetooth networks can coexist with OFDM networks. The frequency-hopping Bluetooth signals block the transmission of some subcarriers of wideband OFDM signals, thereby generating PBPTI for OFDM networks. The interference corrupts consecutive subcarriers and hops to different subcarriers over the transmission. 
     Most known methods require statistics of the channel and interference before any processing can be done on any portion of the received signal. For example, a hypothesis test can be used for interference detection. Also, when the channel statistics, e.g., the power-delay profile, are known, time-domain channel estimation method can be used. Compared to the frequency-domain channel estimation approaches, the time-domain method estimates a smaller number of unknown channel coefficients. Thus, it is more resilient to interference than the frequency-domain method. When the interference statistics are known, interference can be treated as noise with a known variance. Its log-likelihood ratio (LLR) can be determined, and soft iterative decoding can be used to recover the data. 
     When the channel and interference statistics are not known at the receiver, estimating all required parameters using prior art methods can be prohibitively complex. The invention solves this problem. 
     In addition to PBPTI, OFDM networks are vulnerable to fast-varying channel conditions. It is desired to provide OFDM networks and methods for joint wireless channel estimation and PBPTI detection with reduced interference. 
     SUMMARY OF THE INVENTION 
     Embodiments of the invention provide a method for reducing PBPTI in an OFDM network. A transmitter uses low-density parity check (LDPC) codes and random pilot allocation to reduce interference. 
     A receiver performs threshold detection on a set of pilot signals to dynamically estimate the channel and detect interference, and channel estimation with pilot rejection, and soft iterative decoding without estimating interference spectrum. The receiver in our invention does not require the statistics of the channels and the interference before processing the received signal. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows an example of PBPTI in an OFDM network according to embodiments of the invention; 
         FIG. 2  is a block diagram of a transmitter for LDPC encoding, random pilot signals assignment according to embodiments of the invention; 
         FIG. 3  is a schematic of constructing random pilot allocation according to embodiments of the invention; 
         FIG. 4  is a block diagram of a receiver performing interference detection, wireless channel estimation, soft iterative decoding, and decision feedback according to embodiments of the invention; 
         FIG. 5  is a schematic of interference detection using both pilot signals and data signals according to embodiments of the invention; 
         FIG. 6  is a schematic of pilot erasure combined with linear interpolation of least-square (LS) frequency-domain channel estimation according to embodiments of the invention; 
         FIG. 7A  is a block diagram of determining resilient LLRs according to embodiments of the invention; 
         FIG. 7B  is a block diagram of determining dynamic LLRs according to embodiments of the invention; 
         FIG. 8  is a block diagram of decision feedback process to improve channel estimation according to embodiments of the invention; and 
         FIG. 9  is a schematic to obtain new pilot channels from the feedback data and previous interpolated channels. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Embodiments of the invention describe a method for reducing PBPTI in an OFDM network. 
       FIG. 1  shows example OFDM signal blocks  101 . In this example, partial-band and partial-time interference (PBPTI) interference  102  corrupts four consecutive subcarriers k. The interference appears in OFDM symbol time instances 1, 2, 4, 5, 7. The existence of this interference is unknown at a transmitter and a receiver. Also, the PBPTI corrupts different subcarriers at different time instances. 
     Because the parameters of the interference, e.g., existence, location, power, coherent bandwidth, and spectrum of the interference, are unknown, the interference can corrupt signals on both the pilot and the data subcarriers. 
     Interference detection, channel estimation and data detection are needed to improve the performance of networks affected by PBPTI. The invention reduces this type of interference, without have knowledge of the channel and interfere prior to processing the signal. 
       FIG. 2  shows a portion of a transmitter for baseband signal processing. Input binary information bits  201  are encoded by a LDPC block code  202 . A random interleaver  203  is used to reduce PBPT interference. The output binary bits are modulated using conventional mapping  204  to constellation points (s k ), e.g., BPSK, QPSK, 16-QAM and 64-QAM. 
     Modulated symbols  222  are embedded to data subcarriers of OFDM symbols given the data subcarrier indexes  221 . Pilot signals are also inserted to pilot subcarriers of OFDM symbol using the pilot subcarrier indexes  220 . The generated OFDM symbols  223  are converted to time-domain through inverse fast-Fourier transform (IFFT)  208 , followed by adding cyclic prefix (CP)  209  to the beginning of OFDM symbols. The resulting signals  210  are transmitted on subcarriers of radio wireless channels, subject to the PBPTI. 
     The pilot indexes  220  are generated in the pilot index generator  206 . The data index generator  207  selects the subcarrier indexes that are not in the pilot indexes  220  to generate the data indexes  221 . 
       FIG. 3  shows a dynamic process to generate the pilot indexes  220 . First, N F  indexes with equal spacing  301  are generated. These fixed pilot signals are unchanged for different OFDM symbols and provide a minimum spacing between any two pilot subcarriers. Then, N R  indexes with random spacing  302  are generated. The random pilot signals reduce interference that corrupts the same subcarriers during the transmission of different OFDM symbols. The fixed indexes  301  and random indexes  302  are added to generate the set of pilot signals  220  to be transmitted. 
     The ratio between the number of random pilot signals and that of fixed pilot signals, i.e., N R /N F , describes the randomness of the pilot indexes. When the ratio is zero, only fixed pilot signals are used. When the ratio is equal to infinity, only random pilot signals are used. The invention considers random pilot signals, fixed pilot signals, and combinations thereof. 
       FIG. 4  shows baseband signal processing at a receiver. The cyclic prefix is removed  402  from the received signals  401 . The output signals are transformed to frequency domain using FFT  403 . The frequency signals include of two parts: the set of pilot signals  404  and the set of data signals  405 . 
     Interference can be detected by comparing the relative power of each received pilot signal on a subcarrier to the estimated AWGN variance  414 . The output from interference detection  408  is composed of two parts: estimated corrupted pilot indexes  415  and estimated corrupted data indexes  416 . The corrupted pilot signals are erased  406 . The remained pilot signals in the set are used to estimate  407  the channels on pilot subcarriers, which are used in turn to estimate channels  427  on data subcarriers. 
     The set of received data signals  405  are equalized  410  using the estimated data channels. The log-likelihood ratio (LLR) of data subcarriers is determined  409  using estimated channels, equalized data, estimated AWGN variance, and estimated corrupted data indexes. 
     The LLRs of bits received in different OFDM symbols are concatenated and deinterleaved  411 . Soft iterative decoding using a message passing procedure to decode the LDPC encoded OFDM waveforms. 
     The decoded bits can be feedback to improve channel estimation. The posterior LLR of each decoded bit can be obtained from the output of the LDPC decoder  413 . Part of the bits with high posterior LLR can be selected  424  to be added to pilot signals. The channels of newly added pilot signals, previously on data subcarriers, can be updated  423  to combine with the previously interpolated data channels  421 . Then, more pilot channels can be used to estimate data channels. The quality of channel estimation is thus improved to correctly decode more data. 
     The embodiments of the invention provide the following features and advantages. Interference detection uses all pilot and data signals in the respective sets on the various subcarriers. Pilot erasure is used for channel estimation. LLR determination is used to resolve unknown interference spectrum, and decision feedback of the LLR improves channel estimation. 
     Interference Detection 
     The set of pilot signals  404  and the set of data signals  405 , in the frequency domain, can be expressed as
 
 Y   k   =H   k   +n   k   +I   k   ,kεN   P ,
 
 Y   k   =H   k   s   k   +n   k   +I   k   ,kεN   D ,
 
where Y k , H k , s k , I k  denotes the received signal, the channel, data symbol constellation, the AWGN, and the interference on subcarrier k, respectively. The subcarrier indices for pilot signals are denoted N P , and N D  denotes the set of the subcarrier indices for data.
 
       FIG. 5  shows the idea of our interference detection and reduction. When the transmitter uses equal-energy constellations, e.g., BPSK and QPSK, the spectrum of transmit signal  223  is flat. The channel H K  changes very slowly because the number of multipath channels is smaller than the number of frequency-domain subcarriers. 
     The norm of the additive noise term n k  is comparatively smaller than that of the interference I k . Then, the norm of signal plus noise in the receive signals  502  does not change quickly over the frequency. 
     Because the receiver does not know the channel H k , H k  is assumed to be Gaussian distributed with a normalized variance of unity. For the subcarrier not corrupted by interference, i.e., I k =0, Y k  is Gaussian distributed with variance 1+σ 2 , where σ 2  denotes the variance of n k . For the subcarrier corrupted by interference, Y k  is Gaussian distributed with variance 1+σ 2 +ω k   2 , where ω k   2  denotes the variance of I k . 
     Because the PBPTI  503  has a higher power than the additive noise  503 , it can be detected by comparing the norm of Y k  to a predetermined threshold  505 . The pilot signals on subcarriers with magnitude higher than the threshold are detected as corrupted by interference. The pilot signals with magnitude lower than the threshold are detected as uncorrupted. 
     Pilot Erasure and Channel Estimation 
     As shown in  FIG. 6 , after erasing pilot signals  404  higher than the threshold  505 , the remained uncorrupted pilot signals  601  can be used to estimate channels. Prior channel estimation procedures can be used here. For example, when the receiver has no statistical information of the channels, least-square (LS) estimation of pilot channels can be performed. The channels on the data subcarriers  427  can be estimated by linear interpolation or triangular interpolation or since interpolation, to name a few. 
     Equalization and LLR Determination 
     The estimated data channels can be used to equalize the receive signal Y k    410  as  430   
                   Y   ~     k     =         Y   k     ⁢       H   ^     k   *                  H   ^     k          2         ,         kεN D .
 
     The equalized signal  430  is used to calculate LLR for each bit. 
     For the LLR determination, we provide two novel determinations that do not need the variance of interference ω k   2 . 
       FIG. 7A  shows an interference resilient LLR (ReLLR) method.  FIG. 7B  shows a dynamic LLR (DynLLR) method. 
     The ReLLR method only needs the equalized data signals  430 . To obtain the ReLLR  700  for bit b i , the receiver determines  701   
     
       
         
           
             
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     The above summation is over the constellation points s k  with constraint on bit b i  to be either 0 or 1, and where k is a number of subcarriers. 
     In other words, for a given constellation, the ReLLR for bit b i  can be determined using the following steps:
         1) partition the signal constellation into two sets, one set containing all the constellation symbols with bit b i =0, and the other set containing all the constellation symbols with bit b i =1; and   2) For each of the above two sets, form a metric that is equal to the sum of the inverse squared distances of the received signal y k  and the product of the estimated channel Ĥ k  and the constellation symbol in the set;   3) Take the logarithm of the ratio of the two metrics as computed in the above step. This quantity represents the ReLLR for the bit b i .       

     The DynLLR method uses both the LLR determination as known in the prior art, and the ReLLR determination according to embodiments of the invention. The DynLLR method estimates data channels  427 , corrupted data indexes  416 , AWGN variance  414 , and equalized data  430 . 
     This method also does not need the variance of interference ω k   2 . For the data subcarriers that are corrupted, the bit LLR is determined using ReLLR  701   
                 L   ⁢           ⁢   L   ⁢           ⁢     R   ⁡     (     b   i     )         =     log   ⁢         ∑         s   k     :     b   i       =   0               ⁢     1                Y   ~     k     -     s   k            2             ∑         s   k     :     b   i       =   1               ⁢     1                Y   ~     k     -     s   k            2               ,         kεN DI  
 
     where N DI  denotes the set of corrupted data indexes. 
     The indexes of data subcarriers that are detected as uncorrupted  710  can be recovered from those that are detected as corrupted  416 . Then, for the data subcarriers that are detected as uncorrupted, the bit LLR is determined using exact LLR (ExcLLR)  702   
                 L   ⁢           ⁢   L   ⁢           ⁢     R   ⁡     (     b   i     )         =         log   ⁡     (         ∑         s   k     :     b   i       =   0               ⁢     exp   (       -              H   ^     k          2       ⁢                  Y   ~     k     ⁢     s   k            2       σ   2         )           ∑         s   k     :     b   i       =   1               ⁢     exp   (       -              H   ^     k          2       ⁢                  Y   ~     k     -     s   k            2       σ   2         )         )       ⁢   k     ⁢           ∈           ⁢     N   DC         ,         
where N DC  denotes the set of data indexes that are detected as uncorrupted,
 
     Decision Feedback and Channel Update 
     Decision feedback can be used to enhance the performance of decoding without requiring extra information. A decision feedback method according to one embodiment of the invention is used to improve channel estimation for OFDM networks with PBPTI. 
       FIG. 8  shows the feedback method. The output of LDPC decoder  413  includes the decoded bits and their posterior LLRs. The posterior LLR indicates the confidence to the corresponding decoded bits. 
     A selector  424  filters out the low reliable decoded bits. The output bits are re-interleaved  203  and modulated  204  using the same interleaver and constellation as used in the transmitter. The resulting symbols can be used to obtain new pilot subcarriers from data subcarriers as  801   
                   Y   ^     k     =           Y   k     ⁢     s   k   *                s   k          2       =       H   k     +         n   k     ⁢     s   k   *                s   k          2             ,         kεN DC ∪N FB .
 
     where N DC  denotes the index set that is detected as uncorrupted and N FB  denotes the index set that has high posterior LLR. 
     The previous estimated channels, obtained through interpolation of previous pilot signals, on corresponding data signals are combined with these new pilot signals Ŷ k  to update estimation on newly added pilot channels  802 . The estimation of new pilot channels is used to interpolate data channels  803 . 
       FIG. 9  schematically shows updating newly-added pilot channels  802 . The previous estimated channel  421  is obtained through linear interpolation of neighboring pilot signals. It is possible that the corresponding pilot released from feedback  801  has different value compared to the previous one. Note that these two estimates of the same channel have independent additive noise. 
     Combing both values can decrease the estimation error. Some methods of combination that can be used here are arithmetic mean of these two channels or linear combination to minimize mean square error (MMSE) of the resulting estimation error. 
     Effect of the Invention 
     PBPTI with unknown parameters severely degrades the performance of OFDM networks. Conventional interference reduction techniques first need to estimate statistical parameters of channels and interference, and require high computation complexity. 
     In contrast, the invention models interference as a time-frequency hopping Gaussian noise that corrupts consecutive frequency subcarriers and hops independently over OFDM symbols. 
     Our OFDM network uses low-density parity-check (LDPC) codes to resolve interference without estimating its spectrum beforehand. In contrast to conventional log-likelihood ratio (LLR) determination that requires the variance information of noise-plus-interference, a resilient LLR, independent of signal-to-interference-plus-noise ratio, is used to obtain prior LLRs for soft iterative decoding. 
     The bit-error-rate (BER) is improved approximately by 2˜3 dB compared with prior art methods where channel information and interference parameters are perfectly known. Decision feedback methods are also described to enhance channel estimation, and 0.5˜1 dB improvement can be obtained compared to an open-loop method. 
     Although the invention has been described with reference to certain preferred embodiments, it is to be understood that various other adaptations and modifications can be made within the spirit and scope of the invention. Therefore, it is the object of the append claims to cover all such variations and modifications as come within the true spirit and scope of the invention.