Collaborative spectrum sensing optimisation algorithms for cognitive radio networks

The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance

Low Complexity Energy-Efficient Collaborative Spectrum Sensing for Cognitive Radio Networks

Clustering approach is considered a management technology that arranged the distributed cognitive radio users into logical groups to improve the sensing performance of the network. A lot of works in this area showed that cluster-based spectrum sensing (CBSS) technique efficiently tackled the trade-off between performance and overhead issue. By employing the tree structure of the cluster, a multilevel hierarchical cluster-based spectrum sensing (MH-CBSS) algorithm was proposed to compromise between the gained performance and incurred overhead. However, the MH-CBSS iterative algorithm incurs high computational requirements. In this thesis, an energy-efficient low computational hierarchical cluster-based algorithm is proposed which reduces the incurred computational burden. This is achieved by predetermining the number of cognitive radios (CRs) in the cluster, which provides an advantage of reducing the number of iterations of the MH-CBSS algorithm. Furthermore, for a comprehensive study, the modified algorithm is investigated over both Rayleigh and Nakagami fading channels. Simulation results show that the detection performance of the modified algorithm outperforms the MH-CBSS algorithm over Rayleigh and Nakagami fading channels. In addition, a conventional energy detection algorithm is a fixed threshold based algorithm. Therefore, the threshold should be selected properly since it significantly affects the sensing performance of energy detector. For this reason, an energy-efficient hierarchical cluster-based cooperative spectrum sensing algorithm with an adaptive threshold is proposed which enables the CR dynamically adapts its threshold to achieve the minimum total cluster error. Besides, the optimal threshold level for minimizing the overall cluster detection error rate is numerically determined. The detection performance of the proposed algorithm is presented and evaluated through simulation results

Multi-user Diversity Systems with Application to Cognitive Radio

abstract: This thesis aims to investigate the capacity and bit error rate (BER) performance of multi-user diversity systems with random number of users and considers its application to cognitive radio systems. Ergodic capacity, normalized capacity, outage capacity, and average bit error rate metrics are studied. It has been found that the randomization of the number of users will reduce the ergodic capacity. A stochastic ordering framework is adopted to order user distributions, for example, Laplace transform ordering. The ergodic capacity under different user distributions will follow their corresponding Laplace transform order. The scaling law of ergodic capacity with mean number of users under Poisson and negative binomial user distributions are studied for large mean number of users and these two random distributions are ordered in Laplace transform ordering sense. The ergodic capacity per user is defined and is shown to increase when the total number of users is randomized, which is the opposite to the case of unnormalized ergodic capacity metric. Outage probability under slow fading is also considered and shown to decrease when the total number of users is randomized. The bit error rate (BER) in a general multi-user diversity system has a completely monotonic derivative, which implies that, according to the Jensen's inequality, the randomization of the total number of users will decrease the average BER performance. The special case of Poisson number of users and Rayleigh fading is studied. Combining with the knowledge of regular variation, the average BER is shown to achieve tightness in the Jensen's inequality. This is followed by the extension to the negative binomial number of users, for which the BER is derived and shown to be decreasing in the number of users. A single primary user cognitive radio system with multi-user diversity at the secondary users is proposed. Comparing to the general multi-user diversity system, there exists an interference constraint between secondary and primary users, which is independent of the secondary users' transmission. The secondary user with high- est transmitted SNR which also satisfies the interference constraint is selected to communicate. The active number of secondary users is a binomial random variable. This is then followed by a derivation of the scaling law of the ergodic capacity with mean number of users and the closed form expression of average BER under this situation. The ergodic capacity under binomial user distribution is shown to outperform the Poisson case. Monte-Carlo simulations are used to supplement our analytical results and compare the performance of different user distributions.Dissertation/ThesisM.S. Electrical Engineering 201

SPECTRUM SHARING IN COGNITIVE RADIO NETWORKS WITH QUALITY OF SERVICE AWARENESS

The goal of this thesis is to study performance of cognitive radio networks in terms of total spectrum utilization and throughput of secondary networks under perfect and imperfect sensing for Additive White Gaussian Noise (AWGN) and fading channels. The effect of imperfect sensing was studied by applying non-collaborative and collaborative sensing techniques using energy detecting and square law combining techniques, respectively. Spectrum allocation for heterogeneous networks in cognitive radio networks was discussed and a new sharing algorithm that guarantee Quality of Service (QoS) for different secondary users’ applications was proposed. The throughput degradation of secondary users due to the activities of the primary users was explored by varying the arrival rate of the primary users in a given spectrum band. Computer simulation showed that increasing the primary user’s activity will increase the total spectrum utilization but decreases the secondary users’ throughput simultaneously. The effect of the received Signal to Noise Ratio (SNR) of the primary user on the cognitive radio network performance is studied in which, a high SNR of primary users led to a higher throughput of secondary network in AWGN channels compared to Nakagami fading channels. The effect of applying cooperative sensing is also presented in this thesis. As we increased the number of cooperating sensors, the network throughput increased which proves the advantage of applying cooperative sensing. A spectrum allocation algorithm for heterogeneous network model is developed to study the QoS assurance of secondary users in cognitive radio networks. The system performance of the heterogeneous network was investigated in terms of the total spectrum utilization. It is found that, higher number of secondary users, better channel’s condition and low required QoS of applications would increase the spectrum utilization significantly. vii In this thesis, the proposed allocation algorithm was applied to the heterogeneous cognitive radio model and its performance was compared to the First Come First Served (FCFS) algorithm in both AWGN and fading channels. The proposed algorithm provided a higher average SNR and spectrum utilization than FCFS algorithm and guaranteed the QoS requirement for applications of secondary users. The effect of imperfect sensing on the system performance was investigated, and it was shown that, as the probability of detection increases the total applications’ data rate increases significantly. The proposed algorithm guaranteed the QoS requirement for each application of secondary users. The effect of imperfect sensing on the system performance was investigated, and it was shown that, as the probability of detection increases the total data rate increases significantly

Cooperative medium access control based on spectrum leasing

Based on cooperative spectrum leasing, a distributed “win–win” (WW) cooperative framework is designed to encourage the licensed source node (SN) to lease some part of its spectral resources to the unlicensed relay node (RN) for the sake of simultaneously improving the SN’s achievable rate and for reducing the energy consumption (EC). The potential candidate RNs carry out autonomous decisions concerning whether to contend for a cooperative transmission opportunity, which could dissipate some of their battery power, while conveying their traffic in light of their individual service requirements. Furthermore, a WW cooperative medium-access-control (MAC) protocol is designed to implement the proposed distributed WW cooperative framework. Simulation results demonstrate that our WW cooperative MAC protocol is capable of providing both substantial rate improvements and considerable energy savings for the cooperative spectrum leasing system