Dynamic Scheduling for Delay Guarantees for Heterogeneous Cognitive Radio Users

We study an uplink multi secondary user (SU) system having statistical delay constraints, and an average interference constraint to the primary user (PU). SUs with heterogeneous interference channel statistics, to the PU, experience heterogeneous delay performances since SUs causing low interference are scheduled more frequently than those causing high interference. We propose a scheduling algorithm that can provide arbitrary average delay guarantees to SUs irrespective of their statistical channel qualities. We derive the algorithm using the Lyapunov technique and show that it yields bounded queues and satisfy the interference constraints. Using simulations, we show its superiority over the Max-Weight algorithm.Comment: Asilomar 2015. arXiv admin note: text overlap with arXiv:1602.0801

Performance Analysis of Secondary Users in Cognitive Radio Networks

Cognitive radio technology is to improve the inefficient usage of limited spectrum resources when wireless networks coexist. Using this technology, the unlicensed users (secondary users) can opportunistically access the frequency band of licensed users (primary users). There are different kinds of cognitive radio networks. This thesis focuses on the interweave cognitive radio network, where the secondary users are only allowed to access the spectrum holes, i.e., the idle parts of the licensed spectrum band. The main task is to analyze the opportunistic dynamic spectrum allocation method based on selecting the largest available spectrum hole, where the goal is to have the maximum possible transmission rate for secondary users. The objective of this work is to give the service provider an estimation about the load of secondary users in different numbers of channels and various kinds of traffics in primary networks. The work starts with the investigation on the spectrum allocation for secondary users in a network of single-channel primary users. In our analysis, we propose a theoretical model to calculate the probability distribution of the length of the largest available spectrum hole. The contribution of this part is the modeling and performance analysis of the existing conventional method, which selects the largest available spectrum hole. The main contribution is the calculation of the conditional probability of having maximum consecutive idle channels under the condition of a given number of total channels and various number of busy channels. For any given number of channels, this conditional probability gives us the number of consecutive idle channels the secondary user can have, if we know the probability distribution of busy channels taken by primary users. The theoretical model works for any given number of total channels in the licensed frequency band, with numerical and simulation results confirming the precision of the proposed model. Later, we continue our study on the spectrum allocation in a cognitive radio network of multichannel primary users, where the secondary user temporarily takes the largest available spectrum hole. For the performance analysis, we basically need to solve two problems. First, we need to find the probability distribution of busy channels taken by primary users. Second, we need to determine the length of the largest available spectrum hole under the condition of primary users taking different channels. In the case of primary users taking multiple channels, the calculation of the conditional probability of having maximum consecutive idle channels under the condition of a given number of total channels and various number of busy channels, is approximately valid, especially in low-traffic networks. As such, the main contribution in this part is finding the probability distribution of busy channels taken by primary users. The solution scenario is based on a multidimensional Markov chain, with numerical and simulation results verifying the accuracy of the proposed model. Finally, an approximate one-dimensional Markov chain is also proposed to simplify the complicated multidimensional solution. We provide an approximate estimation for the load of the secondary user to avoid the calculation of the complex multidimensional Markov chain. The procedure significantly decreases the complexity, although we lose some information. The main concern in the one-dimensional approximation is to find the departure rates from each state of busy channels. It is actually the main challenge of this part and by approximation we provide the solution. At the end, the performance of the proposed model was validated by numerical and simulation results