Quality Of Service For Secondary Users Research Articles

Link Connectivity and Coverage of Underwater Cognitive Acoustic Networks under Spectrum Constraint.

Extensive attention has been given to the use of cognitive radio technology in underwater acoustic networks since the acoustic spectrum became scarce due to the proliferation of human aquatic activities. Most of the recent studies on underwater cognitive acoustic networks (UCANs) mainly focus on spectrum management or protocol design. Few efforts have addressed the quality-of-service (QoS) of UCANs. In UCANs, secondary users (SUs) have lower priority to use acoustic spectrum than primary users (PUs) with higher priority to access spectrum. As a result, the QoS of SUs is difficult to ensure in UCANs. This paper proposes an analytical model to investigate the link connectivity and the probability of coverage of SUs in UCANs. In particular, this model takes both topological connectivity and spectrum availability into account, though spectrum availability has been ignored in most recent studies. We conduct extensive simulations to evaluate the effectiveness and the accuracy of our proposed model. Simulation results show that our proposed model is quite accurate. Besides, our results also imply that the link connectivity and the probability of coverage of SUs heavily depend on both the underwater acoustic channel conditions and the activities of PUs.

Optimizing Cooperative Cognitive Radio Networks Performance With Primary QoS Provisioning

We consider the problem of optimizing the performance of a cooperative cognitive radio user subject to constraints on the quality-of-service (QoS) of the primary user (PU). In particular, we design the probabilistic admission control parameter of the PU packets in the secondary user (SU) relaying queue and the randomized service parameter at the SU under non-work-conserving (non-WC) and WC cooperation policies. In the non-WC policy, two constrained optimization problems are formulated; the first problem is maximizing the SU throughput while the second problem is minimizing the SU average delay. In both problems, a constraint is imposed on the maximum allowable average delay of the PU. We show the equivalence of the two problems and develop a low-complexity line search algorithm to find the optimal parameters. Subsequently, the idea of optimizing the SU average delay is developed for the more complex WC policy, for its superior resource utilization and performance. Due to the sheer complexity of this optimization problem, we formulate another problem whose solution yields a suboptimal upper bound on the optimal SU delay. Afterwards, a practical WC-policy-based algorithm is designed in order to closely approach the optimal value of the SU delay. We show, through numerical results, that the proposed cooperation policies represent the best compromise between enhancing the SU QoS and satisfying the PU QoS requirements. Furthermore, the superior performance of the suboptimal WC policy over the non-WC policy is illustrated. Finally, the merits of the WC-policy-based algorithm are demonstrated through extensive simulations.

A Framework for Packet Delay Analysis of Point-to-Multipoint Underlay Cognitive Radio Networks

This paper presents a queueing analytical framework for the performance evaluation of the secondary user (SU) packet transmission with service differentiation in a point-to-multipoint underlay cognitive radio network. The transmit power of the SU transmitter is subject to the joint outage constraint imposed by the primary user receivers (PU-Rxs) and the SU maximum transmit power limit. The analysis considers a queueing model for secondary traffic with multiple classes, and different types of arrival and service processes under a non-preemptive priority service discipline. The SU quality of service (QoS) is characterized by a packet timeout threshold and target bit error rate. Given these settings, analytical expressions of the packet timeout probability and average transmission time are derived for opportunistic and multicast scheduling. Moreover, expressions of the average packet waiting time in the queue and the total time in the system for each class of traffic are obtained. Numerical examples are provided to illustrate the secondary network performance with respect to various parameters such as number of PU-Rxs and SU receivers, SU packet arrival process, QoS requirements, and the impact of interference from the primary network to the secondary network.

Clustering and Cooperative Beamforming in Green Cognitive Radio Networks with Relays

A relay assisted cooperative beamforming technique can efficiently improve the spectral efficiency and can reduce the interference to primary users in a cognitive underlay systems. Our objective is to reduce the total power cost of Secondary Users (SU) while limiting the interference in the direction of Primary Users (PU). Kmean algorithm which is a partition based clustering algorithm is used here as the clustering algorithm. While considering flexible cooperation as general scheme, we collectively optimize the clustering and the beamforming to lower the overall power consumption while fulfilling the secondary users quality of service and satisfying the primary users interference temperature limits. An iterative algorithm called generalized Benders decomposition method is used to find an optimal solution. The indirect transmission mode of relays is considered in this work. The relays are equipped with directional antennas which will reduce the interference to the PU and meet the power cost requirement of SU under the assumptions that the clusters are non-overlapping and fixed. Thus spectral efficiency can be increased. Through simulations, we analyzed the advantages of algorithms and showed the benefits of the relays in cognitive wireless networks.

Performance Evaluation of Joint Admission and Eviction Controls of Secondary Users in Cognitive Radio Networks

In recent years, cognitive radio (CR) has been proposed to promote the efficient utilization of the spectrum by exploiting the spectrum holes. The fundamental issue in CR networks is the efficient utilization of radio resources. Call admission control (CAC), which controls the number of calls based on the available resources and bandwidth, is an important functionality to ensure the quality of service (QoS). Thus, in this paper, a new call admission and eviction control of secondary users (CAEC) is proposed. The proposed CAEC is a combination of three variant schemes. The main objective of this proposed scheme is to make admission and evictions decisions jointly in order to improve the spectrum utilization efficiency and ensure the QoS for secondary users (SUs) and to provide better balance between the required SU’s QoS and primary users’ protection. Performance evaluation of the proposed scheme with its variants is studied and compared with other two previous schemes, known as basic CAC (BCAC) and queue-based CAC (QCAC), in terms of the QoS requirements, such as useful utilization and loss probability. Results show that the proposed CAEC achieves higher admitted traffic for SUs than BCAC and QCAC. In addition, it ensures higher system utilization without degrading the primary users’ performance.

Efficient transceiver beamforming in multiple‐input–multiple‐output cognitive radio network

Owing to the ability of improving spectrum utilisation and quality-of-service (QoS) in wireless communications, multiple-input–multiple-output (MIMO) cognitive radio (CR) network has been identified as an excellent choice for the next generation communication. To protect primary users (PUs) from excessive interference while ensuring a meaningful QoS of secondary users (SUs), one key challenge of such system is the joint design of transceiver beamforming for SUs. In this study, the authors investigate the beamforming in MIMO CR network, and two optimisation problems in terms of the minimisation of the total transmission power and the maximisation of the smallest received signal-to-interference-plus-noise ratio (SINR) are considered. The problems can be formulated as indefinite quadratic optimisation programs which are known to be non-convex NP-hard. Hence, a distributed algorithm based on semi-definite programming and minimum-mean-squared-error is proposed to achieve the optimal beamforming weight vector. The findings of this study demonstrated that the proposed algorithm outperforms the existing ones with respect to the total transmitted power and SUs SINR.

Performance analysis of coordinated cognitive radio networks under fixed-rate traffic with hard delay constraints

Due to the unpredictable nature of channel availability, carrying delay-sensitive traffic in cognitive radio networks (CRNs) is very challenging. Spectrum leasing of radio resources has been proposed in the so called coordinated CRNs to improve the quality of service (QoS) experienced by secondary users (SUs). In this paper, the performance of coordinated CRNs under fixed-rate with hard-delay-constraints traffic is analyzed. For the adequate and fair performance comparison, call admission control strategies with fractional channel reservation to prioritize ongoing secondary calls over new ones are considered. Maximum Erlang capacity is obtained by optimizing the number of reserved channels. Numerical results reveal that system performance strongly depends on the value of the mean secondary service time relative to the mean primary service time. Additionally, numerical results show that, in CRNs without spectrum leasing, there exists a critical utilization factor of the primary resources from which it is not longer possible to guarantee the required QoS of SUs and, therefore, services with hard delay constraints cannot be even supported in CRNs. Thus, spectrum leasing can be essential for CRN operators to provide the QoS demanded by fixed-rate applications with hard delay constraints. Finally, the cost per capacity Erlang as function of both the utilization factor of the primary resources and the maximum allowed number of simultaneously rented channels is evaluated.

Interference Management in Cognitive Radio Systems With Feasibility Detection

In this paper, we consider a cognitive radio system with N secondary user (SU) pairs sharing a spectrum with a pair of primary users (PUs). The SU power allocation problem is formulated as a capacity maximization problem under PU and SU quality of service (QoS) and SU peak power constraints. We show that our problem formulation is a geometric program and can be solved with convex optimization techniques. We examine the effect of PU transmissions in our formulations. Solutions for both low- and high-signal-to-interference-and-noise ratio (SINR) scenarios are provided. We show that including PU capacity in the optimization problem in some circumstances leads to increased PU performance while not significantly degrading SU capacity. In a practical wireless communication system, accurate channel state information (CSI) is not often available; hence, we formulate power allocation problems with both perfect and imperfect CSI and analyze the performance loss incurred due to imperfect CSI. Furthermore, we present a novel method of detecting and removing infeasible SU QoS constraints from the SU power allocation problem that results in considerably improved SU performance. Cumulative distribution functions of capacity for various Rayleigh fading channels are presented.