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Noncoherent Multiple Symbol Detection for Continuous Phase Modulation in Physical-layer Network Coding |
DANG Xiaoyu① LIU Zhaotong① LI Baolong② LI Qiang① |
①(College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)
②(College of Information Science and Engineering, Southeast University, Nanjing 210096, China) |
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Abstract Physical-layer Network Coding (PNC) with Continuous Phase Modulation (CPM) attractes much attention due to its high efficiency in the throughput and the spectrum. Most present research on the detection of CPM-PNC signals is based on the assumption that signals transmitted from the two nodes arrivd at the relay haue perfect carrier synchronization or the carrier-phase offset is known. In practical applications, however, the carrier-phase offset is unavoidable and hard to estimate accurately. In this paper, a noncoherent multiple symbol detection algorithm for CPM-PNC signals is proposed to solve this problem. The proposed algorithm, which is based on the maximum likelihood principle, fully exploits the inherit memory of CPM signal and makes decision on the middle symbol by observing a group of symbols. Simulation results show that the performance of the proposed CPM-PNC noncoherent multiple symbol detection algorithm is superior. In addition, as the observation length gets larger, the performance of the proposed algorithm increases significantly and approaches that of CPM-PNC optimal coherent detection. When BER is 10-4, compared with observation length of 1 symbol, the algorithm with observation length of 5 symbols achieves 6.7 dB performance gain.
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Received: 04 June 2015
Published: 14 January 2016
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Fund: The National Natural Science Foundation of China (61172078, 61201208), The State Education Ministry Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, The Fundamental Research Funds for the Central Universities (NS2014038), The Foundation of Graduate Innovation Center in NUAA (kfjj20150404) |
Corresponding Authors:
DANG Xiaoyu
E-mail: dang@nuaa.edu.cn
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