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

Self Organizing strategies for enhanced ICIC (eICIC)

Small cells have been identified as an effective solution for coping with the important traffic increase that is expected in the coming years. But this solution is accompanied by additional interference that needs to be mitigated. The enhanced Inter Cell Interference Coordination (eICIC) feature has been introduced to address the interference problem. eICIC involves two parameters which need to be optimized, namely the Cell Range Extension (CRE) of the small cells and the ABS ratio (ABSr) which defines a mute ratio for the macro cell to reduce the interference it produces. In this paper we propose self-optimizing algorithms for the eICIC. The CRE is adjusted by means of load balancing algorithm. The ABSr parameter is optimized by maximizing a proportional fair utility of user throughputs. The convergence of the algorithms is proven using stochastic approximation theorems. Numerical simulations illustrate the important performance gain brought about by the different algorithms.Comment: Submitted to WiOpt 201