Abstract

Abstract-Cellular networks rely heavily on downlink beamforming; however, calculating beamformers that maximize the weighted sum rate (WSR) under power constraints is an NP-hard problem. A weighted minimum mean square error (WMMSE) algorithm variant is suggested for a MU-MISO downlink channel in order to address this trade-off between complexity and performance. This variation avoids bisection searches, eigendata compositions, and matrix inversions—all of which are challenging to implement as conventional network layers. With a reduced complexity, the suggested network architecture outperforms the WMMSE algorithm truncated to the same number of iterations and adapts well to variations in the channel distribution. Many use cases for vehicles that demand high capacity, extremely low latency, and high reliability can be made possible by 5G. To facilitate this, 5G For a MU-MISO downlink channel, a variation of the weighted minimum mean square error (WMMSE) algorithm is proposed to address this trade-off between complexity and performance. This variation avoids complex network layer implementations such as matrix inversions, eigendata compositions, and bisection searches. The suggested network architecture generalizes well to changes in the channel distribution and performs comparably to the WMMSE algorithm truncated to the same number of iterations, but at a lower complexity. Numerous automotive use cases requiring high capacity, extremely low latency, and high reliability can be made possible by 5G. 5G suggests using highly directed mm Wave system deployment and dense small cell technology to support this. To reduce the cost of signaling, however, enabling vehicular communication necessitates strong mobility management strategies. KEYWORD: Millimetre wave communications, propagation, channel measurements, channel models, MIMO, hybrid precoding, non-orthogonal multiple access (NOMA), multiple access techniques, simultaneous wireless information and power transfer (SWIPT), RF energy harvesting.

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