Blind Signal Classification Analysis and Impact on User Scheduling and Power Allocation in Nonorthogonal Multiple Access

TL;DR

This paper investigates blind signal classification in NOMA systems to reduce signaling overhead, analyzes classification errors, and proposes an algorithm for joint user scheduling and power allocation that enhances spectral efficiency.

Contribution

It introduces a novel analysis of blind signal classification errors and develops a joint optimization algorithm for user scheduling and power allocation in NOMA.

Findings

Proposed scheme outperforms existing user scheduling methods.

Joint optimization improves sum-rate gain of NOMA over OMA.

Analysis of classification errors informs better system design.

Abstract

For a massive number of devices, nonorthogonal multiple access (NOMA) has been recognized as a promising technology for improving the spectral efficiency compared to orthogonal multiple access (OMA). However, it is difficult for a base station (BS) to provide all of the information about NOMA signals via a high layer owing to signaling overhead concerns. This paper studies blind signal classification, which determines whether or not the received NOMA signal requires successive interference cancellation (SIC) without a priori signal information. In this paper, two types of blind signal classification errors are analyzed: 1) the signal is classified as one that does not require SIC on the SIC user side and 2) the signal is classified as one for which SIC is necessary on the non-SIC user side. In addition, we formulate the joint optimization problem for user scheduling and power allocation, which maximizes the sum-rate gain of NOMA over OMA with constraints on the maximum classification error probability and minimum data rate. The proposed algorithm iteratively finds solutions for user scheduling and power allocation. Simulation results show that the proposed scheme outperforms existing user scheduling methods.