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The rapid advancements in 5G technologies have created an unprecedented need for efficient spectrum utilization to support increasing data traffic and diverse communication services. In this context, accurate and reliable spectrum sensing is essential. This study explores wideband spectrum sensing strategies, comparing non-cooperative cognitive radio (CR) techniques with cooperative methods across multiple subbands. A novel cooperative wideband spectrum sensing framework was developed, incorporating a K-outof-N fusion rule at the fusion center to make optimal decisions by selecting an appropriate K for a given number of cooperating CRs. This approach addresses noise uncertainty, a common challenge in traditional non-cooperative energy detection methods, particularly in 5G environments under Additive White Gaussian Noise (AWGN) conditions, assumed to be identically and independently distributed (i.i.d.). However, while cooperative sensing significantly improves detection in low signal-to-noise ratio (SNR) scenarios with higher false alarm rates (between 0.5 and 1), our findings reveal that it does not consistently outperform non-cooperative methods at very low false alarm rates (0.01 and 0.1) under poor SNR conditions. These findings highlight the need for further research to enhance cooperative sensing strategies for various operational environments. 

With the proliferation of 5G networks, evaluating security vulnerabilities is crucial. This paper presents an implemented 5G standalone testbed operating in the mmWave frequency range for research and analysis. Over-the-air testing validates expected throughputs up to 5Gbps downlink and 1Gbps uplink, low latency, and robust connectivity. Detailed examination of captured network traffic provides insights into protocol distribution and signalling flows. The comparative evaluation shows only 0.45% packet loss on the testbed versus 2.7% in prior simulations, proving improved reliability. Thetestbed achieved a throughput of up to 5Gbps downlink and 1Gbps uplink with minimal latency, meeting expected 5G network benchmarks. The results highlight the efficacy of the testbed for security assessments, performance benchmarking, and progression towards 6G systems. This paper demonstrates a robust platform to facilitate innovation in 5G and beyond through practical experimentation. 

The advent of 5G technologies has ushered in unprecedented demands for efficient spectrum utilization to accommodate a surge in data traffic and diverse communication services. In this context, accurate and reliable spectrum sensing is crucial. We investigated wideband spectrum sensing strategies by comparing non-cooperative cognitive radio (CR) approaches with cooperative methods across multiple sub-bands. Our research led to the development of a sophisticated cooperative wideband spectrum sensing framework that incorporates a K-out-of-N fusion rule at the fusion center to make optimal decisions, selecting an appropriate K for a given number of cooperating CRs. This method aims to combat the noise uncertainty typically affecting traditional non-cooperative energy detection methods in 5G environments under Additive White Gaussian Noise (AWGN) conditions, assumed to be identically and independently distributed (i.i.d). However, our findings indicate that while cooperative sensing significantly improves detection in scenarios with poor signal-to-noise ratios (SNRs) and higher false alarm rates (between 0.5 and 1), it does not consistently outperform non-cooperative methods at very low false alarm rates (0.01 and 0.1). This finding suggests the limited effectiveness of the cooperative sensing method under certain conditions, underscoring the need for further research to optimize these strategies for diverse operational environments. 

With the proliferation of 5G networks, evaluating security vulnerabilities is crucial. This paper presents an implemented 5G standalone testbed operating in the mmWave frequency range for research and analysis. Over-the-air testing validates expected throughputs up to 5Gbps downlink and 1Gbps uplink, low latency, and robust connectivity. Detailed examination of captured network traffic provides insights into protocol distribution and signalling flows. The comparative evaluation shows only 0.45% packet loss on the testbed versus 2.7% in prior simulations, proving improved reliability. The results highlight the efficacy of the testbed for security assessments, performance benchmarking, and progression towards 6G systems. This paper demonstrates a robust platform to facilitate innovation in 5G and beyond through practical experimentation.For access to the code, data, and experimental results, visit our GitHub repository(https://github.com/Didilish/5G-SA-Testbed-Analysis)