Digital Beamforming at the Receiver for Transmit Power Reduction in Dense IoT Networks
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Date
2026
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Abstract
The rapid growth of IoT devices and 5G networks demands wireless systems capable of
serving massive numbers of low-power devices simultaneously. This thesis investigates
digital beamforming at the base station receiver to reduce transmit power in dense IoT
uplink networks based on Massive MIMO technology.
Three receiver beamforming strategies are compared: Maximum Ratio Combining
(MRC), Minimum Mean Square Error (MMSE), and a Particle Swarm Optimization (PSO)
based approach. MATLAB simulations are conducted under correlated Rayleigh fading
channel conditions for varying antenna counts, user numbers, and CSI estimation errors.
Results demonstrate that the PSO-based beamformer consistently outperforms classical
methods, maintaining stable performance even under imperfect channel state information
(CSI), establishing it as a robust solution for dense IoT networks under realistic
conditions.