This thesis investigates the performance of hybrid receiver architectures in the LongTerm Evolution (LTE) uplink, focusing on Angle of Arrival (AoA) estimation and data
link quality enhancement. To address the high hardware complexity and power consumption of fully-digital architectures, we evaluate hybrid beamforming structures that reduce
the number of Radio Frequency (RF) chains while preserving system performance. The
study is conducted under two main scenarios compliant with 3GPP standards. In the first
scenario, we assess AoA estimation accuracy using the MUSIC algorithm and Demodulation Reference Signals (DMRS), comparing a fully-digital 8-antenna receiver with a
hybrid 8-antenna/4-RF-chain architecture. In the second scenario, we evaluate link quality metrics (BER, BLER, and Throughput) for partially-connected and fully-connected
hybrid structures, employing an adaptive analog combining matrix updated dynamically
via Sounding Reference Signals (SRS).
The investigation focuses on quantifying the trade-off between hardware simplification
and performance degradation, particularly under realistic fading channel conditions (ETU
and EPA profiles). To reach this target, we implement and analyze both fixed and adaptive hybrid combining strategies, demonstrating that a 50% reduction in RF chains yields
an AoA estimation RMSE between 0.1 and 0.75 degrees, representing a 98% improvement
over aggressive 2-chain configurations. Furthermore, adaptive SRS-based weight optimization enables the fully-connected hybrid architecture to achieve throughput saturation at
significantly lower SNR levels compared to the fully-digital baseline.
The results confirm that standard-compliant hybrid architectures, leveraging existing
LTE reference signals without protocol modifications, offer a practical and cost-effective
solution for upgrading 4G base stations. This work provides a validated framework for
balancing spectral efficiency, hardware complexity, and power consumption in modern