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PERFORMANCE ANALYSIS OF 5G WIRELESS COMMUNICATION SYSTEMS

Area: Department of Digital Communication
Abstract: Fifth-generation (5G) wireless communication networks represent a foundational architectural paradigm shift, engineered to deliver multi-gigabit per second peak data rates, sub-millisecond end-to-end latency, ultra-high reliability, and massive device connectivity across heterogeneous radio frequency spectra. This empirical research paper presents an exhaustive, quantitative performance analysis of standalone 5G New Radio (NR) deployments operating across mid-band Sub-6 GHz (3.5 GHz, Band n78) and millimeter-wave (28 GHz, Band n258) frequency spectra. Leveraging an enterprise-grade hardware testbed coupled with extensive metropolitan field drive-test campaigns, we systematically evaluate physical and transport layer key performance indicators, including downlink and uplink throughput, user-plane latency, jitter, block error rate (BLER), spectral efficiency, beamforming gains under massive Multiple-Input Multiple-Output (MIMO) array configurations, and radio frequency energy efficiency. Empirical findings reveal that mm Wave carriers achieve a peak downlink throughput of 4.18 Gbps over 400 MHz bandwidths under Line-of-Sight (LOS) conditions, but suffer steep propagation attenuation beyond 140 meters, exhibiting a 78.4% throughput reduction under Non-Line-of-Sight (NLOS) conditions. On the other hand, Sub-6 GHz carriers build better coverage: 620 Mbps at 450 meters The Ultra-Reliable Low-Latency Communication (URLLC) slice reached a mean one-way latency of 0.84 ms with 99.999% packet delivery reliability, meeting the strictest musts of industrial automation. Also, as massive MIMO antenna arrays were scaled from 8x8 to 128x128 elements, a SINR gain of 15.8 dB and spectral efficiency gains from approximately 5.8 bps/Hz to 38.1 bps/Hz were observed respectively. Finally, the integration of dynamic AI-enabled sleep modes achieved upto a 68.2% cut in base station energy consumption across low-traffic regimes, setting foundational empirical thresholds for future evolutions
Author: Sachin Aggarwal¹, Dr. Bhawani Singh²
DOI: MJAP/05/2055
Page: 77-53
Paper Id: 2055
Publication Date: 25-Sep-2026
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