A key issue in physical-layer network coding (PNC) is how to deal with the asynchrony between signals transmitted by multiple transmitters. That is, symbols transmitted by different transmitters could arrive at the receiver with symbol misalignment as well as relative carrier-phase offset. A second important issue is how to integrate channel coding with PNC to achieve reliable communication. This paper investigates these two issues and makes the following contributions: 1) We propose and investigate a general framework for decoding at the receiver based on belief propagation (BP). The framework can effectively deal with symbol and phase asynchronies while incorporating channel coding at the same time. 2) For unchannel-coded PNC, we show that for BPSK and QPSK modulations, our BP method can significantly reduce the asynchrony penalties compared with prior methods. 3) For QPSK unchannel-coded PNC, with a half symbol offset between the transmitters, our BP method can drastically reduce the performance penalty due to phase asynchrony, from more than 6 dB to no more than 1 dB. 4) For channel-coded PNC, with our BP method, both symbol and phase asynchronies actually improve the system performance compared with the perfectly synchronous case. Furthermore, the performance spread due to different combinations of symbol and phase offsets between the transmitters in channel-coded PNC is only around 1 dB. The implication of 3) is that if we could control the symbol arrival times at the receiver, it would be advantageous to deliberately introduce a half symbol offset in unchannel-coded PNC. The implication of 4) is that when channel coding is used, symbol and phase asynchronies are not major performance concerns in PNC.
Ref. @cite_4 mentioned without proof that there is a maximum 6 dB BER performance penalty for QPSK modulation when @math and @math . To the best of our knowledge, no quantitative results and concrete explanation have been given for the general @math and @math case.
@cite_4
1801517207 2132881059 2135842153 2061867767
This paper considers automatic gain control (AGC) and quantization for multiple-input multiple-output (MIMO) wireless systems. We examine the effect of clipping and quantization on capacity and bit error rate (BER). We find that even quite low resolution quantizers can perform close to the capacity of ideal unquantized systems. Results are presented for BPSK and M-ary QAM, and for 2times2, 3times3, and 4times4 MIMO configurations. We find that in each case less than 6 quantizer bits are required to achieve 98 of unquantized capacity for SNRs above 15 dB The sum rate capacity of the multi-antenna broadcast channel has recently been computed. However, the search for efficient practical schemes that achieve it is still ongoing. In this paper, we focus on schemes with linear preprocessing of the transmitted data. We propose two criteria for the preceding matrix design: one maximizing the sum rate and the other maximizing the minimum rate among all users. The latter problem is shown to be quasiconvex and is solved exactly via a bisection method. In addition to preceding, we employ a signal scaling scheme that minimizes the average bit-error-rate (BER). The signal scaling scheme is posed as a convex optimization problem, and thus can be solved exactly via efficient interior-point methods. In terms of the achievable sum rate, the proposed technique significantly outperforms traditional channel inversion methods, while having comparable (in fact, often superior) BER performance Orthogonal Frequency Division Multiplexing (OFDM) uses pilot tones to estimate the channel's frequency response and perform equalization. It is commonly known that jamming pilot tones is more efficient than broadband attacks against an entire OFDM signal. This paper builds on this idea and introduces the pilot nulling attack, which is considerably more efficient than simple pilot jamming, by driving received pilot energy as close to zero as possible. This paper presents our channel and equalizer model, and then undertakes an analysis of OFDM under these attacks, verifying the assessment through simulation. For a target bit error rate of 0.4, QPSK underlying modulation, and pilot tone density of 1 8, we discover that pilot jamming is roughly 2 dB more efficient than barrage jamming, and pilot nulling is roughly 7.5 dB more efficient than barrage jamming. In all cases, pilot nulling is capable of fully denying the target signal at 4 dB of signal-to-jamming ratio by driving the QPSK bit error rate to 0.5. For LDPC decoding, a class of weighted bit-flipping algorithms is much simpler than a belief propagation algorithm. This work proposes a modified Gradient Descent Bit-Flipping algorithm based on Reliability Ratio with an adaptive threshold to address trade-off between performance and latency. From numerical results, the proposed algorithm achieves lower latency without an expense of performance. It yields average iteration reduction of 15–27 over SNR range from 2.5 dB to 4.5 dB. In addition, it provides better decoding performance gains, i.e. 0.05–0.25 dB over low-to-medium SNR range between 1.5 dB and 4 dB comparing to previous schemes.