Sparse Vector Coding-Based Multi-Carrier NOMA for In-Home Health Networks

• Published in: IEEE journal on selected areas in communications Vol. 39; no. 2; pp. 325 - 337
• Main Authors: Zhang, Xuewan, Yang, Liuqing, Ding, Zhiguo, Song, Jian, Zhai, Yunkai, Zhang, Di
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical monitoring; capacity; Channel estimation; Coding; Encoding; Health care networks; In-home health network; Internet of Things; Monitoring; Networks; NOMA; non-orthogonal multiple access; Nonorthogonal multiple access; sparse vector coding; Static VAr compensators; symbol error rate
• ISSN: 0733-8716; 1558-0008
• DOI: 10.1109/JSAC.2020.3020679

In-home health networks greatly rely on the massive connected monitoring devices. Compared to orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) can connect more monitoring devices and enhance the spectrum efficiency (SE) performance, which makes it an ideal solution to in-home health networks. However, conventional NOMA (C-NOMA) is mostly constrained to single-carrier scenario. The problem of multi-carrier NOMA lies in the inter-carrier interference (ICI) from neighboring carriers. In this article, we propose a sparse vector coding-based NOMA (SVC-NOMA) to suppress the ICI. We give closed-form expressions of capacity and symbol error rate (SER) performances for both C-NOMA and SVC-NOMA within the considered multi-carrier scenario. Simulation results demonstrate that compared to C-NOMA, SVC-NOMA has better capacity and SER performances. In addition, we find from our results that there is a trade-off between SVC-NOMA's ICI suppression ability and the system capacity performance.