Practical cross‐layer routing and channel assignment in cognitive radio ad hoc networks

In the heterogeneous and unreliable channel environment of cognitive radio ad hoc networks (CRAHNs), a multipath route with channel assigned is preferable in both throughput and reliability. The cross‐layer multipath routing and channel assignment in CRAHNs is becoming a challenging issue. In this paper, this problem is characterized, formulated, and shown to be in the form of mixed integer programming. For this Non‐deterministic Polynomial‐time (NP)‐hard problem, the deficiency of the widely used linearization and sequential fixing algorithm is first analyzed. The main contribution of this paper is the development of a new backtracking algorithm with feasibility checking to search optimal solutions and a heuristic algorithm with high feasible solution‐obtained probability (HHFOP) for distributed application in CRAHNs. Through feasibility checking and solution bounds validating, backtracking algorithm with feasibility checking cuts off unnecessary searching space in early stage without loss of optimal solutions, making it much more efficient than brute searching. For practical application in CRAHNs with polynomial complexity, HHFOP first computes the maximal‐supported throughput through link‐channel assignment and link‐capacity coordination for each candidate path. Then the paths are combined, and the route throughput is optimized. Extensive simulation results demonstrate that HHFOP can achieve a high feasible solution‐obtained probability with little throughput degradation compared with linearization and sequential fixing algorithm, indicating its practicability for distributed applications in CRAHNs. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed cross‐layer optimization for wireless regional area network‐based cognitive radio networks

This paper presents a study of a cross‐layer design through joint optimization of spectrum allocation and power control for cognitive radio networks (CRNs). The spectrum of interest is divided into independent channels licensed to a set of primary users (PUs). The secondary users are activated only if the transmissions do not cause excessive interference to PUs. In particular, this paper studies the downlink channel assignment and power control in a CRN with the coexistence of PUs and secondary users. The objective was to maximize the total throughput of a CRN. A mathematical model is presented and subsequently formulated as a binary integer programming problem, which belongs to the class of non‐deterministic polynomial‐time hard problems. Subsequently, we develop a distributed algorithm to obtain sub‐optimal results with lower computational complexity. The distributed algorithm iteratively improves the network throughput, which consists of several modules including maximum power calculation, excluded channel sets recording, base station throughput estimation, base station sorting, and channel usage implementation. Through investigating the impacts of the different parameters, simulation results demonstrates that the distributed algorithm can achieve a better performance than two other schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

CCRA: channel criticality based resource allocation in cognitive radio networks

In cognitive radio networks, signal to interference plus noise ratio (SINR) is a quantity that is used to analyze the bounds of the capacity of a channel. This is the reason for SINR being one of the important parameters toward evaluating the performance of spectrum sharing in every network. To maximize the channel utilization in any network, the SINR of a channel should be considered to be within a threshold. This also leads to lesser power consumption, and the quality of service for the licensed users is maintained. Further, reduced SINR leads to an improvement in the quality of communication in the network. In this paper, a graph theoretic measure for the efficient utilization of channels in cognitive radio networks has been proposed and is named as channel criticality based resource allocation (CCRA). Using the SINR as the weight of the graph, a novel concept of channel criticality has also been introduced in this work. The proposed CCRA technique has also been compared with the existing interference aware channel assignment (IACA) technique in terms of the channel utilization. Through simulations, the CCRA has been observed to outperform the IACA scheme. The average channel utilization of the proposed CCRA was observed to have increased by 8%, when the secondary users were introduced in the network as compared with the IACA technique. Copyright © 2015 John Wiley & Sons, Ltd.     

Prediction‐based MAC‐layer sensing in cognitive radio networks

We consider a cognitive radio network which coexists with multiple primary users (PUs) and secondary users (SUs) transmit over time‐varying channels. In this scenario, one problem of the existing work is the poor performances of throughput and fairness due to variances of SUs' channel conditions and PUs' traffic patterns. To solve this problem, we propose a novel prediction‐based MAC‐layer sensing algorithm. In the proposed algorithm, the SUs' channel quality information and the probability of the licensed channel being idle are predicted. Through the earlier predicted information, we schedule the SUs to sense and transmit on different licensed channels. Specifically, multiple significant factors, including network throughput and fairness, are jointly considered in the proposed algorithm. Then, we formulate the prediction‐based sensing scheduling problem as an optimization problem and solve it with the Hungarian algorithm in polynomial time. Simulation results show that the proposed prediction‐based sensing scheduling algorithm could achieve a good tradeoff between network throughput and fairness among SUs. Copyright © 2014 John Wiley & Sons, Ltd.     

A cross‐layer study for application‐aware multi‐hop cognitive radio networks

Satisfying the different requirements of applications is important in multi‐hop cognitive radio networks, because the spectrum resources change dynamically and the requirements for various applications could be very different. In this paper, we propose new schemes of channel allocation and route selection for real‐time and non‐real‐time applications to tackle this challenge. Our scheme is flexible so that it can adapt to the different application requirements, and it can provide enough throughput while maintaining the packet loss rate and transmission rate requirements. First, we give the network model in a cognitive radio network environment, and show how to calculate the capacity of the route in multi‐hop cognitive radio networks. Second, we formulate optimization problems to fulfill the rate requirements of different applications for each unicast session. We also consider the primary user activities, channel availability, interface and interference constraint. We propose the corresponding routing and channel allocation schemes for different application scenarios. Third, we propose an admission control scheme to study the impact of application requirements for multiple sessions in cognitive radio networks. Finally, we implement simulations to show the performance of our schemes and compare them with existing schemes. Copyright © 2014 John Wiley & Sons, Ltd.     

Utility‐based resource allocation in uplink of OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically on the basis of non‐interfering to licensed users. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA‐based cognitive radio networks. The objective is to maximize the system utility, which is used as an approach to balance the efficiency and fairness of wireless resource allocation. First, a theoretical framework is provided, where necessary and sufficient conditions for utility‐based optimal subcarrier assignment and power allocation are presented under certain constraints. Second, based on the theoretical framework, effective algorithms are devised for more practical conditions, including ellipsoid method for Lagrangian multipliers iteration and Frank–Wolfe method for marginal utilities iteration. Third, it is shown that the proposed scheme does not have to track the instantaneous channel state via an outage‐probability‐based solution. In the end, numerical results have confirmed that the utility‐based resource allocation can achieve the optimal system performance and guarantee fairness. Copyright © 2009 John Wiley & Sons, Ltd.     

An uplink resource allocation scheme for OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, the uplink radio resource allocation is investigated for OFDMA‐based cognitive radio networks. In consideration of the characteristics of cognitive radio and OFDMA, an improved water‐filling power allocation scheme is proposed under the interference temperature constraints for optimal performance. Based on the improved water‐filling power allocation, a simple subcarrier allocation algorithm for uplink is proposed. The subcarrier allocation rules are obtained by theoretical deduction. In the uplink subcarrier allocation algorithm, the subcarriers are allocated to the users with the best channel quality initially and then adjusted to improve the system performance. A cursory water‐filling level estimation method is used to decrease the complexity of the algorithm. Asymptotic performance analysis gives a lower bound of the stability of the water‐filling level estimation. The complexity and performance of the proposed radio resource allocation scheme are investigated by theoretical analysis and numerical results. Copyright © 2008 John Wiley & Sons, Ltd.     

认知无线网络中基于主用户行为的联合路由和信道分配算法

针对认知无线网络中主用户行为将导致频谱瞬时变化而影响路由稳定性的问题,提出了一种基于主用户行为的路由和信道联合分配算法。该算法通过采用呼叫模型对主用户行为建模,并根据动态源路由协议的路由寻找机制,在目的节点等待多个路由请求分组后选择受主用户行为影响最小的路由,然后沿着所选定路径的反方向传送路由回复分组并完成信道分配。理论分析证明了算法中的链路平均持续时间期望与主用户活动概率成反比且具有与网络节点数成正比的计算复杂度。仿真结果表明,该算法具有比Gymkhana路由方案更高的分组投递率和更低的平均分组时延。     

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

With the advent of various emerging wireless products, the usage of limited spectrum has grown exponentially in the recent years. In the next few years, that mobile data traffic globally is expected to grow up to 50 EB/month, which is nearly a five times increase over year 2018. Therefore, it will become extremely difficult to satisfy the ever increasing demand through the current fixed spectrum assignment policy in which spectrum band is exclusively used for the particular applications, and it has also led to underutilization of a significant portion of the spectrum (like TV bands). Cognitive radio networks has emerged as a possible solution for the problem which makes dynamic spectrum access possible for unlicensed user when licensed user is not active. Among various operations of cognitive radio, channel assignment to the unlicensed user is very important. Further, wireless regional area network is one of the most important application of cognitive radio, which provides wireless broadband to the rural area using vacant TV channels. This paper discusses channel assignment techniques considering various functionalities for cognitive radio networks in respect of wireless regional area network in the existing literature. Initially, a comprehensive introduction to both cognitive radio networks and wireless regional area networks is provided, and in the end, the paper summarizes the various issues and research challenges in the channel assignment for wireless regional area networks.     

Robust routing and channel allocation in multi-hop cognitive radio networks

Wireless Networks - Jointly consider routing and spectrum selection is essentially and necessary in multi-hop cognitive radio networks. System cost and throughput are commonly used to evaluate...     

Resource allocation in underlay cognitive radio networks with full‐duplex cognitive base station

This paper considers an underlay cognitive radio network with a full‐duplex cognitive base station and sets of half‐duplex downlink and uplink secondary users, sharing multiple channels with the primary user. The resource allocation problem to maximize the sum rate of all the secondary users is investigated subject to the transmit power constraints and the interference power constraint. The optimization problem is highly nonconvex, and we jointly use the dual optimization method and the successive convex approximation method to derive resource allocation algorithms to solve the problem. Extensive simulations are shown to verify the performance of the resource allocation algorithms. It is shown that the proposed algorithms achieve much higher sum rate than that of the optimal half‐duplex algorithms and the reference full‐duplex algorithms.     

A low‐complexity resource allocation algorithm in OFDMA‐based cooperative cognitive radio networks

In this paper, we propose a low‐complexity resource allocation algorithm for the orthogonal frequency division multiplexing cooperative cognitive radio networks, where multiple primary users (PUs) and multiple secondary users (SUs) coexist. Firstly, we introduce a new concept of ‘efficiency capacity’ to represent the channel conditions of SUs by considering both of the interference caused by the PUs and the channel gains of the SUs with the assist of the relays. Secondly, we allocate the relay, subcarrier and transmission power jointly under the constraint of limiting interference caused to the PUs. Simulation results show that the proposed algorithm can achieve a high data rate with a relative low power level. Copyright © 2014 John Wiley & Sons, Ltd.     

Prediction based channel allocation performance for cognitive radio

The interdependency, in a cognitive radio (CR) network, of spectrum sensing, occupancy modelling, channel switching and secondary user (SU) performance, is investigated. Achievable SU data throughput and primary user (PU) disruption rate have been examined for both theoretical test data as well as data obtained from real-world spectrum measurements done in Pretoria, South Africa. A channel switching simulator was developed to investigate SU performance, where a hidden Markov model (HMM) was employed to model and predict PU behaviour, from which proactive channel allocations could be made. Results show that CR performance may be improved if PU behaviour is accurately modelled, since accurate prediction allows the SU to make proactive channel switching decisions. It is further shown that a trade-off may exist between achievable SU throughput and average PU disruption rate. When using the prediction model, significant performance improvements, particularly under heavy traffic density conditions, of up to double the SU throughput and half the PU disruption rate were observed. Results obtained from a measurement campaign were comparable with those obtained from theoretical occupancy data, with an average similarity score of 95% for prediction accuracy, 90% for SU throughput and 70% for PU disruption rate.     

Application layer QoS optimization for multimedia transmission over cognitive radio networks

In cognitive radio (CR) networks, the perceived reduction of application layer quality of service (QoS), such as multimedia distortion, by secondary users may impede the success of CR technologies. Most previous work in CR networks ignores application layer QoS. In this paper we take an integrated design approach to jointly optimize multimedia intra refreshing rate, an application layer parameter, together with access strategy, and spectrum sensing for multimedia transmission in a CR system with time varying wireless channels. Primary network usage and channel gain are modeled as a finite state Markov process. With channel sensing and channel state information errors, the system state cannot be directly observed. We formulate the QoS optimization problem as a partially observable Markov decision process (POMDP). A low complexity dynamic programming framework is presented to obtain the optimal policy. Simulation results show the effectiveness of the proposed scheme.     

Utility‐optimal cross‐layer resource allocation in distributed wireless cooperative networks

In this paper, we propose a distributed cross‐layer resource allocation algorithm for wireless cooperative networks based on a network utility maximization framework. The algorithm provides solutions to relay selections, flow pass probabilities, transmit rate, and power levels jointly with optimal congestion control and power control through balancing link and physical layers such that the network‐wide utility is optimized. Via dual decomposition and subgradient method, we solve the utility‐optimal resource allocation problem by subproblems in different layers of the protocol stack. Furthermore, by introducing a concept of pseudochannel gain, we model both the primal direct logical link and its corresponding cooperative transmission link as a single virtual direct logical link to simplify our network utility framework. Eventually, the algorithm determines its primal resource allocation levels by employing reverse‐engineering of the pseudochannel gain model. Numerical experiments show that the convergence of the proposed algorithm can be obtained and the performance of the optimized network can be improved significantly. Copyright © 2012 John Wiley & Sons, Ltd.     

Power allocation in OFDM cognitive radio relay networks with outdated channel state information

In this paper, we study power allocation in OFDM cognitive radio (CR) relay networks. The objective of power allocation is to maximize the instantaneous capacity of the CR network. It is assumed that the available channel state information between the secondary and primary users is an outdated but correlated version of the actual instantaneous channel state information. Optimal power allocation schemes are developed for both decode‐and‐forward and amplify‐and‐forward relay assisted CR transmission, assuming that the primary users are subject to average interference constraints and the CR transmitters are subject to maximum transmit power constraint. In addition, suboptimal power allocation schemes with reduced complexity are also proposed. Performance of the proposed schemes is compared with uniform power allocation and numerical results confirm that the proposed power allocation schemes achieve significant capacity improvement in comparison to uniform power loading. Furthermore, the proposed suboptimal power allocation schemes can be used as less complex alternatives for optimal power allocation with some capacity degradation. Copyright © 2014 John Wiley & Sons, Ltd.     

Sensing error aware delay-optimal channel allocation scheme for cognitive radio networks

Spectrum sensing is not always perfect in practical cognitive radio networks. In this paper, two kinds of sensing errors are considered into the channel allocation scheme. Our work focuses on the cases that the channel availability varies fast during a channel allocation period, in which case the channel dynamics needs to be considered. The sensing errors are modeled to derive the metric of mean delay for each user-channel combination using the vacation queueing model. Further, the optimal resource allocation is determined based on the mean delay metric by bipartite graph matching. The simulation results indicate that the proposed mean delay metric can represent the transmission performance successfully, and the proposed resource allocation scheme is robust to sensing errors.     

Chain store game based channel allocation in cognitive radio system

In adaptive channel allocation for secondary user(SU) of cognitive radio(CR) system,it is necessary to consider allocation process from the temporal perspective.In this article,a chain store game is modeled to achieve SU's equilibrium state.Due to the computational complexity of solving equilibrium states,the authors explore the correlated equilibrium(CE) by importing signal mechanisms based on time and sequence number.Also,correlated equilibrium based game algorithms are presented.Simulations show that the...     

Optimal power allocation for cognitive radio networks with relay‐assisted directional transmission

In this paper, the problem of power allocation in a cooperative cognitive radio (CR) network is investigated. An optimal power allocation is proposed to maximize efficiency of the secondary network in which secondary users transmit simultaneously over a spectral band assigned to the primary users. The CR network employs directional relays to improve efficiency of the communication links and minimize interference introduced to the primary users. Unlike the conventional cooperative relay‐assisted network, the directional relays are grouped in clusters. This clustering technique along with directional transmission can significantly reduce interference to the primary links and improve the system performance. Two algorithms are also developed on the basis of the penalty method to determine unknown transmission powers. Some corroborant numerical examples are provided to illustrate quick convergence behavior of the proposed algorithms and great superiority of employing clustered directional relays in cooperative CR networks. Copyright © 2013 John Wiley & Sons, Ltd.     

DCLRRA: Distributed cross‐layer routing and resource allocation techniques for OFDMA‐based broadband wireless networks

In this study, we develop a fully distributed routing protocol for OFDMA‐based multihop broadband wireless access (BWA) networks such as those of IEEE 802.16j. We refer to this protocol as the DCLRRA protocol. DCLRRA is based on autonomous resource allocation schemes that we also derive in this paper. The routing protocol's selection of the proper resource allocation scheme is based on whether the relay stations (RSs) are nomadic or stationary. While we develop the autonomous resource allocation schemes, we exploit the multi‐user capabilities of the OFDMA physical layer. This allows simultaneous data transmission sessions within the same neighborhood while offering a total elimination of interference between transmitting nodes. The direct result of this strategy is increased throughput with high utilization of the communication channel. We examine our routing technique to show its performance merits through extensive simulations. Copyright © 2010 John Wiley & Sons, Ltd.