volume | PIER Journals

Abstract

Wireless communication has revolutionized modern connectivity, with millimeter-wave (mm-Wave) technology emerging as a key component of next-generation networks due to its ability to deliver fast data rates and large capacity. Hybrid precoding is an important approach in mm-Wave MIMO systems for optimizing spectral efficiency, and it relies largely on accurate channel state information (CSI). The sparse characteristic of mm-Wave channels allows compressive sensing (CS) methods to be used for efficient channel estimation, considerably lowering pilot overhead and computational complexity. This study describes a novel hybrid precoding technique designed for reliable multi-user situations. The proposed two-stage framework uses SVD-based equal-gain transmission (EGT) for analog precoding and a Kalman filter for baseband precoding to effectively reduce inter-user interference. Numerical assessments show that the EGT-Kalman precoding method is comparable with standard strategies like zero-forcing (ZF) and MMSE precoding in terms of spectral efficiency. Furthermore, the pilot overhead is calculated, indicating the efficiency of the suggested technique in reducing training requirements while maintaining performance. This study highlights the promise of adaptive precoding techniques in developing mm-Wave communication systems by providing resilient performance in stable multi-user scenarios while tackling the challenges of sparse channel estimation.

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Dr. Pillala Venkata Muralikrishna

Dr. Teppala Venkata Ramana