Quality Of Service Of Primary Users Research Articles

Cooperative Delay-Constrained Cognitive Radio Networks: Delay-Throughput Trade-Off With Relaying Full-Duplex Capability

In this paper, the problem of maximizing the secondary user (SU) throughput under a primary user (PU) quality of service (QoS) delay requirement is studied. Moreover, the impact of having a full-duplex capability at the SU on the network performance is investigated compared to the case of a SU with half-duplex capability. We consider a cooperative cognitive radio (CR) network in which the receiving nodes have multi-packet reception (MPR) capabilities. In our proposed model, the SU not only benefits from the idle time slots (i.e. when PU is idle), but also chooses between sharing the channel or cooperating with the PU in a probabilistic manner. We formulate our optimization problem to maximize the SU throughput under a PU QoS, defined by a delay constraint; the optimization is performed over the transmission modes selection probabilities of the SU. The resultant optimization problem is found to be a non-convex quadratic constrained quadratic programming (QCQP) optimization problem, which is, generally, an NP-hard problem. We devise an efficient approach to solve it and to characterize the network stability region under a delay constraint set on the PU. Numerical results, surprisingly, reveal that the network performance when full-duplex capability exists at the SU is not always better compared to that of a half-duplex SU. In fact, we demonstrate that a full-duplex capability at the SU can, in some cases, adversely influence the network stability performance, especially if the direct channel conditions between the SU and the destinations are worse than that between the PU and the destinations. In addition, we formulate a multi-objective programming (MOP) optimization problem to investigate the trade-off between the PU delay and the SU throughput. Our MOP approach allows for assigning relative weights for our two conflicting performance metrics, i.e., PU delay and SU throughput. Numerical results also demonstrate that our cooperation policy outperforms conventional cooperative and non-cooperative policies presented in previous works.

Secrecy and throughput performance of an energy harvesting hybrid cognitive radio network with spectrum sensing

In this paper, we evaluate the secrecy outage performance and throughput of a hybrid cognitive radio network, where a secondary user (SU) accesses the primary spectrum either in underlay or overlay mode based on spectrum sensing decision. In underlay, the transmit power of the SU as well as the relay is limited by the maximum acceptable interference at primary user (PU) receiver as required by an PU outage constraint, a quality of service for PU. The secondary network employs a decode and forward relay which harvests energy from the radio frequency signal of SU following a time switching relaying protocol. We develop analytical expressions for secrecy outage considering the impact of sensing decision and sensing time. Impact of sensing time, imperfect channel state information of interfering link, energy harvesting time, acceptable interference threshold and PU outage constraint on the secrecy outage probability, as well as throughput of SU are investigated. Further, an interplay between throughput performance and secrecy outage of the network is highlighted.

Energy‐Efficient Cooperative Strategy in RF Energy Harvesting Cognitive Radio Network

Energy-efficient cooperative spectrum sharing has become a new trend based on financial and environmental considerations. We focus on a novel energy-efficient cooperative strategy in a Radio frequency (RF) energy harvesting cognitive radio network, where the Secondary user (SU) provides energy supply and relaying assist for the Primary user (PU) in exchange for the transmission opportunities. On the basis of energy and information cooperation, an Energy efficiency (EE) maximization non-convex problem for SU is formulated under the PU's Quality of service (QoS) requirement and energy-causality constraint. With the aid of Dinkebalch's method and convex optimization technique, a joint time and power allocation scheme is proposed. Numerical results show that the proposed scheme achieves higher SU's EE and better PU's QoS guarantee compared to the scheme in which the SU only provides energy for the PU's transmission.

Antenna selection and adaptive power allocation for IA‐based underlay CR

In underlay spectrum sharing cognitive radio (CR), the secondary users (SUs) share the spectrum with the primary users (PUs) in such a way that the interference caused by the SUs should be less than the interference temperature (IT) threshold. Interference Alignment (IA) is considered as a novel interference management technique for CR networks (CRN) which eliminates the interference at the PUs and also the interference among the SUs. However, most of the iterative solutions for IA aimed at removing the interference between the users, does not take into account the QoS (Quality of Service) of the PUs and SUs. Also the achievable rate of PUs by employing IA is less than that of the maximum achievable rate in a MIMO (Multiple input multiple output) system with no interference. In this paper we first present an Antenna Selection (AS) scheme to significantly improve the QoS of PUs and then we have proposed an adaptive power allocation (PA) scheme which aims at optimum PA in view of the proportional fairness among SUs. Numerical results are derived for comparing the proposed schemes in terms of outage performance of PUs and SUs. Simulation results show the effectiveness of the proposed methods in terms of SNR.

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.

Secrecy outage analysis in a hybrid cognitive relay network with energy harvesting

SummaryIn this paper, we investigate the physical layer security of a hybrid cognitive relay network using an energy harvesting relay in presence of an eavesdropper. In the hybrid scheme, a secondary user (SU) as well as a cognitive relay works either in underlay or in overlay mode. In underlay, the transmit power of the SU as well as the relay is limited by the maximum acceptable interference at primary user (PU) receiver as required by an outage constraint of PU, a quality of service for PU. The secondary network consists of a decode and forward relay that harvests energy from radio frequency signal of secondary transmitter as well as PU transmitter to assist the SU in forwarding the information signal to the destination. A time switching relaying protocol is used at the relay. We evaluate the secrecy outage probability of secondary relay network assuming that channel state information of the interfering links from both the SU and relay transmitter to PU receiver is imperfect. Our results reveal the impact of imperfect channel state information, energy harvesting time, tolerable interference threshold, and PU outage constraint on the secrecy outage probability of SU.

Cognitive spectrum management in dynamic cellular environments: A case-based Q-learning approach

This paper examines how novel cellular system architectures and intelligent spectrum management techniques can be used to play a key role in accommodating the exponentially increasing demand for mobile data capacity in the near future. A significant challenge faced by the artificial intelligence methods applied to such flexible wireless communication systems is their dynamic nature, e.g. network topologies that change over time. This paper proposes an intelligent case-based Q-learning method for dynamic spectrum access (DSA) which improves and stabilises the performance of cognitive cellular systems with dynamic topologies. The proposed approach is the combination of classical distributed Q-learning and a novel implementation of case-based reasoning which aims to facilitate a number of learning processes running in parallel. Large scale simulations of a stadium small cell network show that the proposed case-based Q-learning approach achieves a consistent improvement in the system quality of service (QoS) under dynamic and asymmetric network topology and traffic load conditions. Simulations of a secondary spectrum sharing scenario show that the cognitive cellular system that employs the proposed case-based Q-learning DSA scheme is able to accommodate a 28-fold increase in the total primary and secondary system throughput, but with no need for additional spectrum and with no degradation in the primary user QoS.

Transmit Precoding for Interference Exploitation in the Underlay Cognitive Radio Z-channel

This paper introduces novel transmit beamforming approaches for the cognitive radio (CR) Z-channel. The proposed transmission schemes exploit non-causal information about the interference at the SBS to re-design the CR beamforming optimization problem. This is done with the objective to improve the quality of service (QoS) of secondary users by taking advantage of constructive interference in the secondary link. The beamformers are designed to minimize the worst secondary user's symbol error probability (SEP) under constraints on the instantaneous total transmit power, and the power of the instantaneous interference in the primary link. The problem is formulated as a bivariate probabilistic constrained programming (BPCP) problem. We show that the BPCP problem can be transformed for practical SEPs into a convex optimization problem that can be solved, e.g., by the barrier method. A computationally efficient tight approximate approach is also developed to compute the near-optimal solutions. Simulation results and analysis show that the average computational complexity per downlink frame of the proposed approximate problem is comparable to that of the conventional CR downlink beamforming problem. In addition, both the proposed methods offer significant performance improvements as compared to the conventional CR downlink beamforming, while guaranteeing the QoS of primary users on an instantaneous basis, in contrast to the average QoS guarantees of conventional beamformers.

Cognitive radio intelligent-MAC (CR-i-MAC): channel-diverse contention free approach for spectrum management

Cognitive radio was introduced to fill up the imbalance between spectrum scarcity and spectrum underutilization. So to make such an ideology work, a network which can utilize all the available channel in the best efficient manner, without causing any harmful interface to primary user (PU) and maintaining the Quality of Service (QoS) for cognitive user (CU) is required. In both Mesh as well as ad-hoc networks, effective utilization of the white-spaces by the CUs maintaining the QoS for both primary and CU is a challenging task due to the frequent and instant change in their channel status. In this paper an intelligent-MAC (i-MAC) for cognitive radio (CR) using two transceivers based on hybrid approach of combination of cooperative decision and contention-free approach is proposed. Cooperative decision, to overcome hidden node or the case when there is no common channel between the CU's and contention-free approach, to solve the issues in contention mechanism, where same channel is selected simultaneously by multiple CU's. Proposed CR-i-MAC permits an effective dynamic spectrum access to CUs without effecting the QoS for PU's. The simulative performance analysis of proposed CR-i-MAC is tested in various critical cases like multi-channel single-radio and multi-channel multi-radio over different on demand routing protocols like dynamic source routing, ad-hoc on demand distance vector and weighted cumulative expected transmission time using network simulator (NS-2). The performance of the network is measured on the basis of parameters like throughput, delay and interference. The analysis of the simulation results shows that the proposed CR-i-MAC outperforms various other CR MAC's in terms of both increased throughput and reduced delays thereby making the system stable and efficient.

Multiuser-diversity-based interference alignment in cognitive radio networks

As a promising interference management technique, interference alignment (IA) has been applied to cognitive radio (CR) networks. However, the received signal-to-interference-plus-noise ratio (SINR) may decrease dramatically under some channel conditions in IA-based CR networks, and this will reduce the quality of service (QoS) of primary users (PUs). In this paper, we study the problem of SINR decrease and propose a multiuser-diversity-based IA scheme to make it more practical to be applied to CR networks. Since the number of secondary users (SUs) is changing dynamically in practical CR networks, we present two schemes targeted at two different scenarios. In the first scenario with a large number of SUs, the IA network cannot accommodate all the PUs and SUs simultaneously with perfect elimination of interferences. The corresponding scheme is to select those SUs, which can maximally improve the QoS of PUs, to access to the spectrum by forming an IA network with the PUs. Thus the performance of PUs can be significantly improved. To further ensure the interest of SUs, the scheme is revised and a tradeoff is made between the PUs and SUs. In the second scenario with a smaller number of SUs, the IA network can accommodate all the users simultaneously without mutual interference. User selection and antenna selection strategies are adaptively employed to guarantee the performance of PUs. Furthermore, fairness among SUs is also investigated. Simulation results are presented to show the effectiveness of the proposed schemes for CR networks.

Filter‐and‐forward transceiver design for cognitive two‐way relay networks

In this study a new approach to filter-and-forward (FF) relay design in an overlay cognitive radio (CR) network with frequency selective channels is proposed. In this system, to implement two-way relaying scheme, a secondary multi-antenna node acts as a relay and helps two primary users (PUs) communicate with each other and in return the secondary node superposes its signal to filtered signals of PUs. The authors intend to design secondary transceiver under two criteria, one from the viewpoint of improving the performance of secondary network and the other to guarantee quality of service (QoS) of primary network. The first criterion is to maximise the signal-to-interference-plus-noise ratio (SINR) of secondary receiver subject to constraints on QoS of PUs and the relay transmitted power. For the other one, the goal is to achieve max-min fairness among PUs through maximising the worse signal-to-interference-plus-noise ratio (SINR) of PUs subject to constraints on QoS of secondary receiver and transmit power of relay. The authors employ an alternating optimisation algorithm to find the beamforming matrices and the allocated power to secondary receiver's message in these non-convex problems. Simulation results show that the proposed FF approach has better performance compared with simple AF relaying strategy.

Cooperative multiple access in cognitive radios to enhance QoS for cell edge primary users: asynchronous algorithm and convergence

Cognitive radio (CR) systems have been proposed for efficient usage of spare spectrum licensed to primary systems. This leads to the issue of providing as much spectrum to CR users as possible while not degrading the quality of service (QoS) of primary users of the spectrum. This paper proposes a novel cooperation scheme between primary and CR users to guarantee QoS of primary users up to the cell edge while making the licensed spectrum available for opportunistic access by the CR users. We suggest that the primary users at the cell edge, who have poor QoS, should allow secondary users to access their spectrum, while at the same time, the secondary users would help to enhance the primary users QoS using superposition coding on the primary users transmissions. Thus the proposed method can provide a so called "win-win strategy" by benefiting both primary and CR users. The proposed cooperative access scheme in cognitive radios solves efficiently the sum-rate maximization problem on cognitive Gaussian Multiple Access Channels (GMACs) for power allocation of primary systems that cooperates with CR systems in a distributed fashion. We solved the problem using iterative Jacobian method in a distributed manner. A totally asynchronous distributed power allocation for sum-rate maximization on cognitive GMACs is suggested. Numerical results show that the QoS of primary users at the cell edge is improved by the proposed cooperative access scheme.

Mean Energy Efficiency Maximization in Cognitive Radio Channels With PU Outage Constraint

Energy efficiency (EE) is very crucial for future green wireless communication systems, particularly for cognitive radio networks (CRNs). However, the EE design for CRNs in fast-fading scenarios has not been fully studied. This letter investigates the mean EE maximization problem for the secondary user (SU) in the fading cognitive radio channels consisting of both SUs and primary users (PUs). We adopt PU outage probability constraint to ensure the quality of service (QoS) of PUs and consider both the peak and mean transmit power constraints for SUs. However, this problem is nontrivial since the mean EE is nonconvex and PU outage probability constraint belongs to chance constraints. With the aid of the fractional programming and Lagrangian duality theory, we propose an efficient algorithm to derive the optimal power allocation strategy for SU to maximize its mean EE while guaranteeing the QoS of PUs. Simulation results assess the performance of our proposed scheme and show the tradeoff between SUs' mean EE and PU outage probability threshold only in some certain range.

On the Capacity of Secondary Networks Over Opportunistic Spectrum Access in Rayleigh Fading Channels

In this paper the effect of the opportunistic spectrum access on the spectrum utilization is studied in terms of the secondary network capacity measured at the secondary receiver. A mathematical model is developed to represent the secondary network capacity in Rayleigh fading channel. An exact analytical solution for the capacity is derived for both sensing and accessing fading channels. A numerical evaluation of the channel capacity is presented for different channel sensing and accessing schemes. The effects of detection and accessing channel parameters on the capacity are investigated. The analytical results that are validated by substantial simulations showed how the utilization of the network can be increased significantly by the suggested opportunistic spectrum accessing technique. It was found that when having a good sensing system with a high secondary user signal to noise ratio, accessing the licensed band increases and drives the spectrum utilization to its maximum. In addition, this work shows how the capacity can be positively affected by three factors: the secondary accessing channel, the primary user interference and the desired quality of service (QoS) of primary user. The awareness of a proper sensing scheme can maximize the spectrum utilization without degrading the QoS of primary users.

Primary service outage degradation in dynamic spectrum sharing with non-ideal spectrum sensing

In a dynamic spectrum sharing system, secondary users (SUs) attempt to maximise their throughput while preserving a given level of quality of service (QoS) for primary users (PUs). In doing so, the secondary network monitors the spectrum and decides on spectrum availability, which at times and for various reasons, may be erroneous. If spectrum is sensed as available, the secondary network selects an appropriate spectrum access strategy, and adjusts other communication parameters such as transmit power levels. In this study, the authors analyse primary service outage degradation caused by secondary access with non-ideal spectrum sensing. For different spectrum access strategies, namely, the overlay and the modified underlay spectrum access (MUSA), the authors derive a closed-form expression for the maximum outage probability degradation (MOD) in the presence of spectrum sensing errors and fading and show how adjustments by secondary service can result in attaining the desired QoS for PUs. Besides, for a given acceptable MOD in the primary network, the authors obtain a lower bound on the achievable expected rate of the secondary service in Nakagami-m and Rayleigh fading channels. Simulations confirm the analysis and show that MUSA considerably increases the secondary service rate, particularly when the activity of primary service is above 50%.