Optimizing Spectral Efficiency: An SNV Scheme for IoT-Enabled CF mMIMO Networks

Future wireless networks are expected to achieve uniform quality of service (QoS) and seamless connectivity across vast coverage areas. Cell-free (CF) massive multiple-input, multiple-output (mMIMO) networks emerge as a promising solution to achieve these goals by minimizing signal interference and enhancing network performance. However, the existing research contributions in CF mMIMO networks face significant challenges related to signal overhead, network load, and computation complexity on the fronthaul, resulting in unscalability. Considering these limitations, we propose a novel space division multiple access (SDMA)-based network virtualization (SNV) scheme to maximize the uplink/downlink spectral efficiency in the Internet of Things (IoT)-enabled CF mMIMO networks. Our system architecture leverages multiple IoT-enabled wireless access points (APs) equipped with various antennas, establishing independent communication links to serve user equipment (UEs) simultaneously. The integration of stream-based encoding and minimum mean square error estimation enables UEs to receive accurate data, improve channel capacity, and minimize the computation complexity on fronthaul. Our extensive simulation results demonstrate that the proposed scheme significantly outperforms current state-of-the-art schemes while ensuring scalability for CF mMIMO networks.