Orthonormal pilot-based channel estimation with low complexity phase shift optimization and coverage enhancement for IRS-assisted B5G communication

Abstract

Beyond fifth-generation (B5G) technology features millimeter wave (mmWave) to ensure low latency and high capacity while enabling multiple-input and multiple-output (MIMO) facilities. MMWave signals are attenuated over short distances, resulting in a smaller coverage area. The B5G network relies on Intelligent Reflecting Surfaces (IRS) for reducing mmWave attenuation. IRS increases mmWave coverage and reduces obstruction risks by introducing phase shifts on incident beams. Complete channel state information (CSI) is required to estimate phase shifts in IRS and precoding. A novel orthonormal pilot matrix with a low-complexity channel estimation method is proposed in this context. The proposed channel estimation method achieved maximum accuracy with limited pilot sequences. A low-complexity phase shift optimization technique is also presented in this study using estimated channel information. On the other hand, the use of the desired number of reflective elements is highlighted to maximize coverage. On the basis of received signal strength and outage probability, two approaches are presented for determining the number of reflective elements. The derived closed-form expression of outage probability (OP) seems simple. It shows close agreement with the theoretical model. Results show that the proposed model provides better achievable rates than conventional IRS models.