Tang, J; Zhao, Y; Feng, W; Zhao, X; Zhang, XY; Liu, M; Wong, KK; (2021) Cross-Layer Optimization for Industrial Internet of Things in NOMA-based C-RANs. IEEE Internet of Things Journal 10.1109/JIOT.2021.3138461. (In press).

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Abstract

This paper investigates non-orthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficency (EE) by jointly optimizing the power allocation, analog and digital precoding, which turns out to be an intractable non-convex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with hybrid precoding (HP) scheme can achieve higher SE and EE than traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme.

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