Terahertz-Band MIMO-NOMA: Adaptive Superposition Coding and Subspace Detection
Hadi Sarieddeen, Asmaa Abdallah, Mohammad M. Mansour, Mohamed-Slim, Alouini, Tareq Y. Al-Naffouri

TL;DR
This paper introduces adaptive spatial tuning and low-complexity detection techniques for THz-band MIMO-NOMA systems, significantly improving data recovery and reducing error rates and complexity in ultra-massive MIMO scenarios.
Contribution
It proposes novel spatial tuning and channel puncturing methods for efficient data detection in THz MIMO-NOMA, extending to multi-user scenarios with minimal performance loss.
Findings
Channel puncturing reduces BER by over an order of magnitude at high SNR.
Proposed methods achieve approximately 90% complexity reduction.
Successive interference cancellation remains effective with minimal performance impact.
Abstract
We consider the problem of efficient ultra-massive multiple-input multiple-output (UM-MIMO) data detection in terahertz (THz)-band non-orthogonal multiple access (NOMA) systems. We argue that the most common THz NOMA configuration is power-domain superposition coding over quasi-optical doubly-massive MIMO channels. We propose spatial tuning techniques that modify antenna subarray arrangements to enhance channel conditions. Towards recovering the superposed data at the receiver side, we propose a family of data detectors based on low-complexity channel matrix puncturing, in which higher-order detectors are dynamically formed from lower-order component detectors. We first detail the proposed solutions for the case of superposition coding of multiple streams in point-to-point THz MIMO links. We then extend the study to multi-user NOMA, in which randomly distributed users get grouped into…
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Taxonomy
TopicsAdvanced Wireless Communication Techniques · Advanced Wireless Communication Technologies · Advanced MIMO Systems Optimization
