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An optimal Secrecy Sum Rate (SSR) maximization model is developed for effective Multiple-Input Multiple-Output-Non-Orthogonal Multiple Access (MIMO-NOMA) uplink transmission by solving the interference management and complexity issues. In order to decompose the channels, a Singular Value Decomposition (SVD) model is utilized. It offers insightful information about the properties of the channel, facilitating effective user grouping, power distribution, and resource allocation. The main objectives of this work are to maximize the SSR, Base Station (BS) capacity, and throughput of MIMO-NOMA. These factors are maximized by tuning the power allocation matrices of far user and near user using the Cock-Hen-Chicken Optimizer (CHC). This method is helpful for providing effective communication when the system has more number of channels and users. The capability of maximizing the SSR via the recommended model is validated with existing techniques to ensure the superiority of the recommended model.

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An Energy Efficient Secure Optimal Secrecy Sum Rate Maximization Mechanism for MIMO-NOMA Uplink Transmission in 6G Networks Using a Heuristic Approach

  • 会议论文

  • 发表日期：

    2026年

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  • P. Vineela,
  • C. V. RaviKumar

摘要

An optimal Secrecy Sum Rate (SSR) maximization model is developed for effective Multiple-Input Multiple-Output-Non-Orthogonal Multiple Access (MIMO-NOMA) uplink transmission by solving the interference management and complexity issues. In order to decompose the channels, a Singular Value Decomposition (SVD) model is utilized. It offers insightful information about the properties of the channel, facilitating effective user grouping, power distribution, and resource allocation. The main objectives of this work are to maximize the SSR, Base Station (BS) capacity, and throughput of MIMO-NOMA. These factors are maximized by tuning the power allocation matrices of far user and near user using the Cock-Hen-Chicken Optimizer (CHC). This method is helpful for providing effective communication when the system has more number of channels and users. The capability of maximizing the SSR via the recommended model is validated with existing techniques to ensure the superiority of the recommended model.