With the rapid growth in the field of wireless communication, effective spectrum utilization techniques are required. In the urban areas, which are rich with wireless communication devices, we will find some frequency bands that are only partially occupied and some other bands that are essentially unused. To avoid the underutilization of scarce radio spectrum, cognitive radio (CR) has been proposed as one effective solution to enhance the utilization of the radio spectrum. A CR system detects radio frequency (RF) channels that are vacant and switches into these unoccupied channels to enhance frequency spectrum utilization. The ability of CR systems to sense the availability of RF communication channels is governed by the use of the spectrum sensing technique. Therefore, spectrum sensing is a fundamental requirement in CR systems. In this thesis, we explore various techniques for spectrum sensing. We investigate the energy detection-based spectrum sensing for efficient hardware implementation. We utilize signal processing expertise such as window selection, window overlap, window size, transform size, averaging, and thresholding to develop a robust spectrum sensing module. We then model the energy detection-based spectrum sensing in Matlab. Its synthesizable model is developed in Verilog hardware description language. The architecture of the designed spectrum sensing module is implemented on a Xilinx Virtex-7 field-programmable gate array (FPGA) and its cycle-accurate bit-true hardware simulation results are verified against its fixed-point simulation results. An ASIC architecture of the designed spectrum sensing module is developed using a standard 45-nm CMOS technology.