A Novel Hybrid SDMA-NOMA with Adaptive Index Modulation Framework for Enhanced Secrecy, Fairness, and Efficiency in 6G MIMO-NOMA Uplink Networks

Wireless networks of the sixth generation (6G) are developing fast, and it is imperative to develop new access schemes that could simultaneously provide high spectral efficiency, user fairness, massive interconnectivity, and reliable communication in varying channel conditions. Conventional Space Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA) due to the inefficient resource allocation and lack of adaptation ability in dense multi-user environments demonstrate poor performance. In this study, we present a framework named Hybrid SDMA-NOMA with Adaptive Index Modulation (H-SNIM) for uplink massive Multiple Input Multiple Output (MIMO) communications to solve these issues. For the optimization of the Secrecy Sum Rate (SSR) while maintaining user fairness considering transmit power and QoS constraints, the presented framework utilizes SDMA-based spatial multiplexing, NOMA power-domain multiplexing, adaptive index modulation using OFDM subcarriers, and dynamic power allocation. To transform the resultant non-convex problem into a convex problem that can be solved using convex optimization, the first order Taylor expansion technique has been used. A large MIMO system of 64 antennas working on a 28 GHz mmWave channel is considered for the extensive simulation in MATLAB. Based on the results of experiments, the proposed H-SNIM scheme performs better than OMA, SDMA, MIMO, MRC and ZF beamforming with spectral efficiency of 5.0 bps/Hz, energy efficiency of 2.0 Mbps/W, Jain’s fairness index of 0.85, sum-rate of 12 Mbps, and an outage probability of only 0.05. Compared to existing techniques, the proposed system has managed to decrease the Average Bit Error Rate (ABER) by 30% along with an improvement of secrecy sum rate by about 25%. It is clear from the results that H-SNIM has emerged as a robust and scalable framework for resource allocation in 6G mmWave MIMO networks.