Shamasundar, B and Chockalingam, A (2019) Capacity Analysis and Structured Sparse Detection of Generalized Media-based Modulation. In: 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019, 15 - 19 April 2019, Marrakesh.
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Abstract
Media-based modulation (MBM) is an attractive channel modulation scheme with rate, performance, and hardware advantages. In this paper, we are concerned with two important aspects of MBM. The first one is on the capacity of MBM and the other is on low-complexity detection of high-rate MBM signals using structured spare recovery techniques. We derive closed-form expression for the capacity of generalized MBM (GMBM). The main idea in the capacity analysis is to recognize that MBM uses two alphabets to convey information, namely, the source alphabet (e.g., QAM/PSK) and the channel alphabet (fade coefficients). This observation allows us to show that the capacity is achieved when the mutual information is maximized over the source-channel product alphabet. We then propose a greedy structured sparse recovery algorithm for the detection of GMBM signal vectors. The proposed algorithm is a two-stage algorithm in which support recovery is done in greedy manner first, followed by data detection in the nonzero positions. Simulation results show that the proposed algorithm achieves good performance at low complexity even when the system is highly underdetermined.
Item Type: | Conference Paper |
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Publication: | IEEE Wireless Communications and Networking Conference, WCNC |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Recovery; Signal detection, capacity; channel alphabet; Closed-form expression; Low-complexity detections; Mutual informations; Recovery techniques; Structured sparsities; Two-stage algorithm, Modulation |
Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering Others |
Date Deposited: | 30 Nov 2022 09:43 |
Last Modified: | 30 Nov 2022 09:43 |
URI: | https://eprints.iisc.ac.in/id/eprint/78335 |
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