Compressive Sensing Approach in Multicarrier Sparsely Indexing Modulation Systems

作     者：Mostafa Salah Osama A.Omer Usama S.Mohamed Mostafa Salah;Osama A.Omer;Usama S.Mohamed;Dept.of Electrical Engineering, Sohag University;Dept.of Electrical Engineering, Aswan University;Dept.of Electronics & Comm.Engineering, Arab Academy for Science Technology and Maritime Transport;Dept.of Electrical Engineering, Assiut University

作者机构：Dept. of Electrical Engineering Sohag University Sohag Egypt Dept. of Electrical Engineering Aswan University Aswan 81542 Egypt Dept. of Electrical Engineering Assiut University Assiut Egypt Dept. of Electronics & Comm. Engineering Arab Academy for Science Technology and Maritime Transport Aswan 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2017年第14卷第11期

页      面：151-166页

核心收录：

学科分类：11[军事学] 0810[工学-信息与通信工程] 1105[军事学-军队指挥学] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0839[工学-网络空间安全] 08[工学] 081002[工学-信号与信息处理] 110503[军事学-军事通信学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：indexed modulation combinatorial modulation double sparsity critical sparsity sparsely indexed modulation OFDM-IM 

摘      要：recently the indexed modulation(IM) technique in conjunction with the multi-carrier modulation gains an increasing attention. It conveys additional information on the subcarrier indices by activating specific subcarriers in the frequency domain besides the conventional amplitude-phase modulation of the activated subcarriers. Orthogonal frequency division multiplexing(OFDM) with IM(OFDM-IM) is deeply compared with the classical OFDM. It leads to an attractive trade-off between the spectral efficiency(SE) and the energy efficiency(EE). In this paper, the concept of the combinatorial modulation is introduced from a new point of view. The sparsity mapping is suggested intentionally to enable the compressive sensing(CS) concept in the data recovery process to provide further performance and EE enhancement without SE loss. Generating artificial data sparsity in the frequency domain along with naturally embedded channel sparsity in the time domain allows joint data recovery and channel estimation in a double sparsity framework. Based on simulation results, the performance of the proposed approach agrees with the predicted CS superiority even under low signal-to-noise ratio without channel coding. Moreover, the proposed sparsely indexed modulation system outperforms the conventional OFDM system and the OFDM-IM system in terms of error performance, peak-to-average power ratio(PAPR) and energy efficiency under the same spectral efficiency.