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198202 https://hdl.handle.net/2286/R.2.N.198202 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2024 70 pages Masters Thesis Academic theses Text eng Thakkar, Raj Dharmendra Bliss, Dr. Daniel Chakrabarti, Dr. Chaitali Akoglu, Dr. Ali Arizona State University Partial requirement for: M.S., Arizona State University, 2024 Field of study: Computer Engineering In cognitive radio, spectrum sensing is indeed critical for identifying “spectrumholes,” which are underused frequency bands in the licensed spectrum. By detecting these unused bands, cognitive radios can enhance spectrum efficiency, allowing sec- ondary users to transmit without interfering with primary users. Energy Detection is a popular choice for spectrum sensing in cognitive radio applications due to its simplicity and relatively low computational requirements. Despite not requiring prior knowledge of the signal structure, it can efficiently distinguish between occupied and unoccupied channels by measuring the energy in a frequency slot. The implementation of Multi-antenna Energy Detection is particularly interesting, as multi-antenna setups can significantly improve detection accuracy, leveraging spatial diversity to overcome signal fading and interference. By configuring this on a DAP architecture, we optimized for parallelism and scalability, which are essential in high-throughput signal processing. Finite Impulse Response (FIR) filters play a crucial role in digital signal processing (DSP) due to their inherent stability and versatility. Because an FIR filter’s impulse response is finite and settles to zero after a certain point, it ensures stability, which is often essential in applications where signal integrity and predictability are paramount. The n-Tap FIR filter using the Direct Form method aligns well with the DAP setup. A 16-tap FIR filter allows for sufficient frequency selectivity in filtering applications, and the Direct Form implementation is straightforward, making it compatible with hardware-friendly architectures like systolic arrays. Additionally, the DAP’s 8 × 8 PE structure is well-suited for FIR filtering, as each tap of the filter can be mapped to the PEs for efficient computation, supporting scalability without significant overhead. This thesis explores advanced and compelling aspects of Multi antenna Energy Detection, particularly in spectrum sensing and FIR filtering using systolic arrays—a fascinating approach to optimizing performance in signal processing tasks. Communication Domain Adaptive Processor Energy Detect Finite Impulse Response Signal Processing Systolic Array Wireless communication Implementation of Multi-antenna Energy Detection and 16-Tap FIR on Domain Adaptive Processor