Peak to average power ratio based spatial spectrum sensing for cognitive radio systems

The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval

Adaptive OFDM System Design For Cognitive Radio

Recently, Cognitive Radio has been proposed as a promising technology to improve spectrum utilization. A highly flexible OFDM system is considered to be a good candidate for the Cognitive Radio baseband processing where individual carriers can be switched off for frequencies occupied by a licensed user. In order to support such an adaptive OFDM system, we propose a Multiprocessor System-on-Chip (MPSoC) architecture which can be dynamically reconfigured. However, the complexity and flexibility of the baseband processing makes the MPSoC design a difficult task. This paper presents a design technology for mapping flexible OFDM baseband for Cognitive Radio on a multiprocessor System-on-Chip (MPSoC)

Performance Estimation of Improved Cooperative Spectrum Sensing in Cognitive Radio

The applications of wireless communication are growing day by day; utilization of the spectrum is one of the prime challenges. Cognitive radio is the new era of wireless communication and acts as an immerging solution to the problem. It senses, analyzes and, allocates the vacant frequency band to secondary users (cognitive Radios). Energy detection (E.D.) has been accepted as the most suitable spectrum sensing technique due to its lower complexity, simplicity and majorly because of its blind detection.  But the performance of the E.D. is limited by low SNR,  shadowing, and multipath fading, so there is a tradeoff between complexity and performance in this conventional Energy detection technique. In this paper improved version of E.D. –Improved Energy Detection (IED)is used as a significant method for the case of cooperative sensing scenario. The proposed framework is also analyzed and compared for the case of different SNR and decision fusion rules. The Simulation result shows that the proposed framework gives excellent performance compared to conventional energy detection (CED) technique with lower complexity which meets the real-time requirement of cooperative spectrum sensing in wireless communication