Spectrum Sensing and Data Transmission in a Cognitive Relay Network Considering Spatial False Alarms

Abstract —In this paper, the average probability of the symbol error rate (SER) and throughput are studied in the presence of joint spectrum sensing and data transmission in a cognitive relay network, which is in the environment of an optimal power allocation strategy. In this investigation, the main component in calculating the secondary throughput is the inclusion of the spatial false alarms, in addition to the conventional false alarms. It has been shown that there exists an optimal secondary power amplification factor at which the probability of SER has a minimum value, whereas the throughput has a maximum value. We performed a Monte-Carlo simulation to validate the analytical results. Keywords —Cognitive Network, Conventional False Alarms, Probability of Symbol Error Rate, Spatial False Alarms, Spectrum Sensing 1. I NTRODUCTION With the explosive growth of wireless communication systems, such as wireless local area networks (WLANs), mobile cellular networks, ad-hoc and sensor networks, etc., the demand for the radio spectrum has rapidly increased and thus, the wireless spectrum has become a scarce commodity. The traditional schemes of fixed spectrum allocation have been shown to be inadequate in addressing such quickly evolving wireless technologies. Recent measurement studies [1] have demonstrated that many frequency bands licensed to operators are employed in scattered fashion over vast geographical areas and are idle most of the time (commonly known as spectrum holes). Cognitive radio (CR) systems have been proposed as a promising solution to inefficient spectrum management and scarcity of the radio spectrum. It is defined as an intelligent wireless communication system [2] that is aware of the surrounding environment and utilizes the methodology of understanding-by-building to learn from the environment. The spectrum detection technique (also referred to as spectrum sensing) enables CR networks to adapt to the environment by detecting spectrum holes. The most efficient way to detect the spectrum holes is to detect the presence of primary users (PUs) [3,4]. However, in reality, it is difficult for a CR to obtain a direct measurement of the channel between a primary receiver and a transmitter. Therefore, the most recent work focuses on the primary transmitter detection method, which is based on the local observations of secondary users (SUs). Starting from the idea of enabling devices to use any available spectrum [5,6], the concept of