Cross Layer Modeling And Performance Analysis For Cognitive Radio Networks

With the rapid growth in demand for wireless communications, the spectrum resources become scarce. According to Federal Communications Commission, the assigned spectrum is not being used at a specific time and geographic location. These idle spectrums are called spectrum holes. With the help of the cognitive radio technology, the secondary users (unlicensed users) can access these spectrum holes without affecting the primary users (licensed users). As a result, the utilization of the spectrum is improved and the current situation of spectrum resource scarcity has been alleviated. So the cognitive radio technology has become a hotspot in the research of the wireless communication technology.In cognitive radio network, it must be ensured that the primary user's Quality of Service is not affected, in addition, the secondary user's Quality of Service of basic communication should be guaranteed. Around these two points, the model based on the queuing theory for the relationship between the call level and packet level is put forward. Through this model, the formulas for the call level performance (PU call blocking probability, SU call blocking probability and spectrum utilization) and packet level performance (SU packet loss ratio, packet delay and throughput) are derived. Meanwhile, an algorithm to maximize the throughput is proposed. The main contributions of this thesis are as follows:1) Build the CLM (Cross Layer Markov) Model to describe the relationship between the call level and packet level. To the best of our konwledge, so far all the studies are focused on the performance analysis of call level or packet level, while no study considers the relationship between the two layers. In this thesis, the CLM model based on the queuing theory for the relationship between the call level and packet level is established and the relationship between the two layers are analyzed quantitatively.2) Analyze the performance of the cognitive radio network with reliable spectrum sensing through the CLM model. Four network models are introduced, which are categorized by user's policy, including discarding, buffering, discarding according to the position in the queue and discarding with fixed-probability. The performances of the call level and packet level are compared. Simulation results show that the network with fixed-probability discarding policy can achieve the best performance.3) Analyze the performance of the cognitive radio network with unreliable spectrum sensing throughput the CLM model. In the cognitive radio network, the spectrum sensing error is represented by the misdetection probability and the false alarm probability. By building the CLM model for the cognitive radio network with unreliable spectrum sensing, the relationship of the misdetection probability and the false alarm probability with the performance parameters is established. Simulation results show that the misdetection brings greater influence to the performance of the network than false alarm.4) Proposed an algorithm that maximizes the throughput. In order to eliminate the performance deterioration of the secondary user when the traffic load of the primary user is high, a channel reservation scheme is proposed. In addition, an algorithm that maximizes the throughput is designed. To guarantee both the Quality of Service of the secondary user and the primary user, the algorithm can yield a maximum throughput by finding the optimized number of reserved channel and discarding probability.