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.
Although asynchronous unchannel-coded PNC has been studied previously, only suboptimal decoding algorithms were considered. Refs. @cite_29 and @cite_15 argued that the largest BER performance penalty is 3 dB for BPSK modulation (for both phase and symbol asynchronies). However, this conclusion is based on suboptimal decoding.
@cite_29 @cite_15
2076284780 2047187801 2161057417 2688805433
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. Physical-layer network coding (PNC) is an attractive technique because it can significantly enhance the throughput of a wireless network with a relatively simple implementation, as compared with conventional network coding (NC) schemes. In this paper, the authors first investigate PNC with frequency shift keying (FSK) through the derivation of its bit-error rate (BER) and capacity, as well as the impact of imperfect synchronization to the overall performance. Based on the discussions on PNC with 2FSK, the authors then further expand the analysis to PNC with M -ary FSK (MFSK). Theoretical results indicate that the BER performance of PNC with 2FSK is a bit worse than that of PNC with 2PSK. As the constellation dimension M increases, the BER performance of PNC with M -ary FSK improves at the expense of bandwidth efficiency degradation. This paper proposes majority-based tracking forecast memories (MTFMs) for area efficient high throughput ASIC implementation of stochastic Low-Density Parity-Check (LDPC) decoders. The proposed method is applied for ASIC implementation of a fully parallel stochastic decoder that decodes the (2048, 1723) LDPC code from the IEEE 802.3an (10GBASE-T) standard. The decoder occupies a silicon core area of 6.38 mm2 in CMOS 90 nm technology, achieves a maximum clock frequency of 500 MHz, and provides a maximum core throughput of 61.3 Gb s. The decoder also has good decoding performance and error-floor behavior and provides a bit error rate (BER) of about 4 × 10-13 at Eb N0=5.15 dB. To the best of our knowledge, the implemented decoder is the most area efficient fully parallel soft -decision LDPC decoder reported in the literature. This paper presents the first network-coded multiple access (NCMA) system prototype operated on high-order modulations up to 16-QAM. NCMA jointly exploits physical-layer network coding (PNC) and multiuser decoding (MUD) to boost throughput of multipacket reception systems. Direct generalization of the existing NCMA decoding algorithm, originally designed for BPSK, to high-order modulations, will lead to huge performance degradation. The throughput degradation is caused by the relative phase offset between received signals from different nodes. To circumvent the phase offset problem, this paper investigates an NCMA system with multiple receive antennas at the access point, referred to as MIMO-NCMA . We put forth a low-complexity symbol-level NCMA decoder that, together with MIMO, can substantially alleviate the performance degradation induced by relative phase offset. To demonstrate the feasibility and advantage of MIMO-NCMA for high-order modulations, we implemented our designs on software-defined radio. Our experimental results show that the throughput of QPSK MIMO-NCMA is double that of both BPSK NCMA and QPSK MUD at SNR = 10 dB. For higher signal-to-noise ratios at which 16-QAM can be supported, the throughput of MIMO-NCMA can be as high as 3.5 times that of BPSK NCMA. Overall, this paper provides an implementable framework for high-order modulated NCMA.