Min-max Decoding Error Probability Optimization in RIS-Aided Hybrid TDMA-NOMA Networks
One of the primary objectives for future wireless communication networks is to facilitate the provision of ultra-reliable and low-latency communication services while simultaneously ensuring the capability for vast connection. In order to achieve this objective, we examine a hybrid multi-access sche...
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | One of the primary objectives for future wireless communication networks is
to facilitate the provision of ultra-reliable and low-latency communication
services while simultaneously ensuring the capability for vast connection. In
order to achieve this objective, we examine a hybrid multi-access scheme inside
the finite blocklength (FBL) regime. This system combines the benefits of
non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA)
schemes with the aim of fulfilling the objectives of future wireless
communication networks. In addition, a reconfigurable intelligent surface (RIS)
is utilized to facilitate the establishment of the uplink transmission between
the base station and mobile devices in situations when impediments impede their
direct communication linkages. This paper aims to minimize the worst-case
decoding-error probability for all mobile users by jointly optimizing power
allocation, receiving beamforming, blocklength, RIS reflection, and user
pairing. To deal with the coupled variables in the formulated mixed-integer
non-convex optimization problem, we decompose it into three sub-problems,
namely, 1) decoding order determination problem, 2) joint power allocation,
receiving beamforming, RIS reflection, and blocklength optimization problem,
and 3) optimal user pairing problem. Then, we provide the sequential convex
approximation (SCA) and semidefinite relaxation (SDR)-based algorithms as
potential solutions for iteratively addressing the deconstructed first two
sub-problems at a fixed random user pairing. In addition, the Hungarian
matching approach is employed to address the challenge of optimizing user
pairing. In conclusion, we undertake a comprehensive simulation, which reveals
the advantageous qualities of the proposed algorithm and its superior
performance compared to existing benchmark methods. |
---|---|
DOI: | 10.48550/arxiv.2310.11750 |