Constellation Mapping for Physical-Layer Network Coding with M-QAM Modulation

The denoise-and-forward (DNF) method of physical-layer network coding (PNC) is a promising approach for wireless relaying networks. In this paper, we consider DNF-based PNC with M-ary quadrature amplitude modulation (M-QAM) and propose a mapping scheme that maps the superposed M-QAM signal to coded symbols. The mapping scheme supports both square and non-square M-QAM modulations, with various original constellation mappings (e.g. binary-coded or Gray-coded). Subsequently, we evaluate the symbol error rate and bit error rate (BER) of M-QAM modulated PNC that uses the proposed mapping scheme. Afterwards, as an application, a rate adaptation scheme for the DNF method of PNC is proposed. Simulation results show that the rate-adaptive PNC is advantageous in various scenarios.Comment: Final version at IEEE GLOBECOM 201

Symbol error rate analysis for M-QAM modulated physical-layer network coding with phase errors

Recent theoretical studies of physical-layer network coding (PNC) show much interest on high-level modulation, such as M-ary quadrature amplitude modulation (M-QAM), and most related works are based on the assumption of phase synchrony. The possible presence of synchronization error and channel estimation error highlight the demand of analyzing the symbol error rate (SER) performance of PNC under different phase errors. Assuming synchronization and a general constellation mapping method, which maps the superposed signal into a set of M coded symbols, in this paper, we analytically derive the SER for M-QAM modulated PNC under different phase errors. We obtain an approximation of SER for general M-QAM modulations, as well as exact SER for quadrature phase-shift keying (QPSK), i.e. 4-QAM. Afterwards, theoretical results are verified by Monte Carlo simulations. The results in this paper can be used as benchmarks for designing practical systems supporting PNC. © 2012 IEEE

Improvement in Performance of Wireless Relay Nodes Using Physical Layer Network Coding

Recent advancements in high data rate networks have led to a growing interest in improving performance of wireless relay networks through the use of Physical Layer Network Coding (PLNC) technique. In the PLNC technique, the relay node exploits the network coding operation that occurs naturally when the two electromagnetic (EM) waves are superimposed on one another to directly decode the modulo-2 sum of the transmitted symbols. In this thesis, we will present an optimal power control algorithm for performance improvement in wireless relay nodes implementing physical layer network coding. We shall also present a sub-optimal power control algorithm and compare its performance with the optimal power control algorithm. Our approach will first derive the probability of error for the amplitude-controlled system using Maximum Likelihood detection and then minimize the probability of error using amplitude control functions as variables to derive the optimal power control functions. We shall start by considering the thresholds of the system to be the maximum of the independent received amplitudes to derive the probability of error equations and then extend it to a variable threshold system, where the threshold is a function of independent received amplitudes. We then derive an optimal power control algorithm for a single channel Rayleigh system and implement this power control algorithm independently on the terminals to achieve a sub-optimal power control algorithm. Our results show that the proposed optimal power control algorithm boosts the performance of the PLNC system significantly compared to the no power control system. We also show that there are no significant differences between the performances of optimal power control and the sub-optimal power control algorithms. We further show that the performance of the system is not degraded much when the amplitudes of the terminals deviate from the optimal amplitudes