Dynamic spectrum access based on interruptible spectrum leasing

Dynamic spectrum access (DSA) based on interruptible spectrum leasing allows secondary users (SUs) to lease a licensed, but idle, spectrum that is owned by primary users (PUs) on condition that the PUs preempt the access to the leased spectrum. This paper considers a DSA scenario where the SUs opportunistically use the primary spectrum in addition to their own band and the PUs use their own band regardless of the opportunistic access. This operating scenario can contribute to leverage the spectrum utilization by exploiting underutilized spectrum resources, but involves a problem that the SUs may be forced to interrupt on-going services in response to the PUs?? reclamation of the leased spectrum. In this paper, we address the optimal call admission control (CAC) problem in order to coordinate the DSA based on interruptible spectrum leasing by considering the tradeoff between the additional spectrum use and the penalty on the service interruption. To this end, we adopt the profit of the secondary wireless service provider as a cost function of the CAC policy in a market mechanism manner. The optimization problem is modeled as a profit maximization problem, and a linear programming (LP) formulation of the semi-Markov decision process approach is provided. Through the simulation results, we analyze the LP solution of the optimal CAC for the leasing based DSA and demonstrate that the proposed CAC policy judiciously uses the access opportunities of the SUs considering the service interruption.     

Cluster‐based coordination scheme for cooperative cognitive radio networks

In this paper, a cluster‐based two‐phase coordination scheme for cooperative cognitive radio networks is proposed considering both spectrum efficiency and network fairness. Specifically, candidate secondary users (SUs) are first selected by a partner selection algorithm to enter the two‐phase cooperation with primary users (PUs). In phase I, the selected SUs cooperate with PUs to acquire a fraction of time slot as a reward. In phase II, all SUs including the unselected ones share the available spectrum resources in local clusters; each of which is managed by a cluster head who participated in the cooperation in phase I. To improve the total network utility of both PUs and SUs, the maximum weighted bipartite matching is adopted in partner selection. To further improve the network performance and communication reliability, network coding is exploited during the spectrum sharing within the cluster. Simulation results demonstrate that, with the proposed cluster‐based coordination scheme, not only the PUs' transmission performance is improved, but also SUs achieve spectrum access opportunities. Copyright © 2015 John Wiley & Sons, Ltd.     

Cooperative spectrum sharing of multiple primary users and multiple secondary users

This paper proposes a multiple-input multiple-output (MIMO) based cooperative dynamic spectrum access (DSA) framework that enables multiple primary users (PUs) and multiple secondary users (SUs) to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non-MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.     

A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. Copyright © 2013 John Wiley & Sons, Ltd.     

Joint routing and channel assignment using online learning in cognitive radio networks

Cognitive radio networks (CRNs) are the solution for the problem of underutilizing the licensed spectrum for which there are more requests in the last couple of decades. In CRNs, Secondary users (SUs) are permitted to access opportunistically the licensed spectrum owned by primary users (PUs). In this paper, we address the problem of joint routing and channel assignment for several flows generated by source SUs to a given destination. We consider a more realistic model based on Markov modulated Poisson process for modeling the PUs traffic at each channel and the SUs try to exploit short lived spectrum holes between the PUs packets at the selected channel. The SUs want to cooperatively minimize the end-to-end delay of source SUs flows meanwhile the quality of service requirements of the PUs would be met. To consider partial observation of SUs about PUs activity at all channels and quick adaptation of SUs decisions to environment changes and cooperative interaction of SUs, we use decentralized partially observable markov decision process for modeling the problem. Then, an online learning based scheme is proposed for solving the problem. Simulation results show that the performance of the proposed method and the optimal method is close to each other. Also, simulation results show that the proposed method greatly outperforms related works at control of interference to the PUs while maintains the end-to-end delay of SU flows in a low level.

     

MaxDiv: an optimal randomized spectrum access with maximum diversity scheme for cognitive radio networks

Cognitive radio network (CRN) is an emerging technology that can increase the utilization of spectrum underutilized by primary users (PUs). In the literature, most exiting investigations on CRNs have focused on how secondary users (SUs) can coexist harmlessly with the PUs. Despite the importance of such a coexistence issue, it is also crucial to investigate the coexistence of SUs because (i) the PUs usually rarely use the licensed spectrum and (ii) the advantages of CRN will significantly increase the number of SUs in the future. To address this challenging issue, we propose, in this paper, an optimal randomized spectrum access scheme, whose main ideas include the following: (i) an SU shares its sensing results with neighboring SUs and (ii) with the regional sensing results, an SU will access available channels with a non‐uniform probability distribution. We first formulate a multichannel optimal randomized multiple access (MC‐ORMA) problem that aims to maximize the throughput of the CRN; we then develop efficient distributed algorithms to solve the MC‐ORMA problem; we derive the closed‐form value of collision probability for each SU; and finally, we conduct extensive numerical experiments and compare our theoretical analysis with simulation results to demonstrate the advantages of our scheme. Copyright © 2011 John Wiley & Sons, Ltd.     

Cooperative bargaining solution for efficient and fair spectrum management in cognitive wireless networks

This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co‐opetition strategy based on the Kalai–Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co‐opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi‐PU competition, PU's subcarrier contribution, multi‐SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co‐opetition strategy with several conventional ones, including the Kalai–Smorodinsky bargaining solution, sum rate maximization as well as the Max–Min. Results indicate that the co‐opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co‐opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. Copyright © 2013 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.     

Cooperative transmissions for secondary spectrum access in cognitive radios

In cognitive radio networks (CRNs), the primary users (PUs) and secondary users (SUs) will interfere with each other, which may severely degrade the performances of both primary and secondary transmissions. In this paper, we propose a two‐phase cognitive transmission (TCT) protocol for secondary spectrum access in CRNs, aiming at improving the secondary transmission performance while guaranteeing the quality‐of‐service (QoS) of primary transmissions. In TCT protocol, SUs gain the opportunities to access the licensed spectrum through assisting primary transmissions using superposition coding (SC), where SUs limit their transmit power to satisfy a given primary QoS requirement and also employ interference cancelation technique to mitigate the interference from PUs. Under the constraint of satisfying a required primary outage probability, we derive the closed‐form expressions of secondary outage probabilities over Rayleigh fading channels for proposed TCT protocol. Numerical and simulation results reveal that, with a guaranteed primary outage probability, TCT achieves better secondary transmission performance than traditional case. Copyright © 2013 John Wiley & Sons, Ltd.     

New coalition formation game for spectrum sharing in cognitive radio networks

In cognitive radio networks, Secondary Users (SUs) can access the spectrum simultaneously with the Primary Users (PUs) in underlay mode. In this case, interference caused to the licensed users has to be effectively controlled. The SUs have to make spectrum access decisions in order to enhance their quality of service, but without causing harmful interference to the coexisting PUs. In this paper, we propose a cooperative spectrum decision, which enables the SUs to share the spectrum with the PUs more efficiently. Our approach is based on a new coalitional game in which the coalition value is a function of the SUs' spectral efficiencies, the inter‐SUs interference, and the interference caused to the PUs. By applying new Enter and Leave rules, we obtain a stable coalition structure. Simulation results show that the SUs' spectral efficiencies are considerably increased and that the interference caused to the coexisting PU is reduced by about 7.5% as compared to an opportunistic spectrum access scheme. Moreover, the proposed coalitional game results in a more balanced spectrum sharing in the network. Copyright © 2014 John Wiley & Sons, Ltd.     

Cognitive medium access control protocols for secondary users sharing a common channel with time division multiple access primary users

The unused time slots in a primary time division multiple access (TDMA) network are regarded as the potential channel access opportunities for secondary users (SUs) in cognitive radio (CR). In this paper, we investigate the medium access control protocols that enable SUs to access a common TDMA channel with primary users (PUs). The primary traffic is assumed to follow a Bernoulli random process. A two‐state Markov chain is used to model the secondary traffic, and two different scenarios are considered. The first scenario assumes that the secondary packet arrivals are independent and follow a Bernoulli random process and a cognitive carrier sensing multiple access (Cog‐CSMA) protocol is proposed. A Rayleigh fading channel is considered in evaluating Cog‐CSMA, and its throughput expression is derived in this paper. The second scenario assumes that the packet arrivals follow a correlated packet arrival process and a cognitive packet reservation multiple access (Cog‐PRMA) protocol is proposed. A Markov chain is used to model the different system states in Cog‐PRMA and derive the throughput. Numerical results show that the Cog‐CSMA and Cog‐PRMA protocols achieve the objective of supporting secondary transmissions in a TDMA network without interfering the PUs' transmissions and improve the network bandwidth utilization. Copyright © 2012 John Wiley & Sons, Ltd.     

A fair MAC protocol for resource sharing in ad-hoc cognitive networks

Cognitive Radio (CR) technology allows an opportunistic use of the licensed spectrum by the CR users, avoiding harmful interference to Primary Users (PUs). To perform their activity, secondary users (SUs) have particular features compared to the PUs; sensing is one of the principal. Specifically the CR users must detect the spectrum holes left by PUs by performing sensing. All the protocol stack need to be redesigned taking into account the specificity of the cognitive environment. In this paper a novel MAC protocol for cognitive radio wireless ad-hoc networks is presented and analysed. The introduced protocol is distributed, collision-free and guarantees a fair channel assignment, also taking into account the requests of Quality of Service (QoS) of the CR nodes. The performance of the protocol has been studied through statistical computations. In particular, a Markov chain has been introduced to study the global performance of the protocol. In addition a simulation tool has been developed to validate the mathematical model and to prove the fairness of the resource sharing mechanism. The results prove the protocol efficiency and the high fairness, measured with the help of the Jain’s fairness index.     

The Optimal Spectrum Sensing Time for Maximizing Throughput of 802.11-Based MAC Protocol for Cognitive Radio Networks Under Unsaturated Traffic Conditions

Cognitive radio has attracted considerable attention as an enabling technology for addressing the problem of radio frequency shortages. In cognitive radio networks (CRNs), secondary users (SUs) are allowed to opportunistically utilize the licensed spectrum bands of primary users (PUs) when these bands are temporarily unused. Thus, SUs should monitor the licensed spectrum bands to detect any PU signal. According to the sensing outcomes, SUs should vacate the spectrum bands or may use them. Generally, the spectrum sensing accuracy depends on the sensing time which influences the overall throughput of SUs. That is, there is a fundamental tradeoff between the spectrum sensing time and the achievable throughput of SUs. To determine the optimal sensing time and improve the throughput of SUs, considerable efforts have been expended under the saturated traffic and ideal channel assumptions. However, these assumptions are hardly valid in practical CRNs. In this paper, we provide the framework of an 802.11-based medium access control for CRNs, and we analyze this framework to find the optimal spectrum sensing time under the saturated and unsaturated traffic condition. Through simulation, the proposed analytic model is verified and the fundamental problem of the sensing-throughput tradeoff for CRNs is investigated.     

Prioritized Medium Access Control in Cognitive Radio Ad Hoc Networks: Protocol and Analysis

Cognitive radio (CR) technology enables opportunistic exploration of unused licensed channels. By giving secondary users (SUs) the capability to utilize the licensed channels (LCs) when there are no primary users (PUs) present, the CR increases spectrum utilization and ameliorates the problem of spectrum shortage. However, the absence of a central controller in CR ad hoc network (CRAHN) introduces many challenges in the efficient selection of appropriate data and backup channels. Maintenance of the backup channels as well as managing the sudden appearance of PUs are critical issues for effective operation of CR. In this paper, a prioritized medium access control protocol for CRAHN, PCR-MAC, is developed which opportunistically selects the optimal data and backup channels from a list of available channels. We also design a scheme for reliable switching of a SU from the data channel to the backup channel and vice-versa. Thus, PCR-MAC increases network throughput and decreases SUs’ blocking rate. We also develop a Markov chain-based performance analysis model for the proposed PCR-MAC protocol. Our simulations, carried out in \(NS-3\) , show that the proposed PCR-MAC outperforms other state-of-the-art opportunistic medium access control protocols for CRAHNs.     

认知无线电中基于MIMO波束成形的协同频谱接入设计

协同认知无线电技术由于其高效的频谱利用效率已经吸引越来越多的关注。在协同认知网络中,当第一用户（Primary User,PU）之间的信道状况恶劣时,特定的第二用户（Secondary User, SU）被选为中继协同PU完成信息传递,作为回报,PU分配一定的信道资源给SU,使其用于传输自己的信息。当SU系统中一个节点拥有多天线时,假设其可以很好的获悉其与PU之间的信道状态信息,通过波束成形设计可以使其在中继PU信息的同时完成自身信息的发送,而且使两者之间的信号互不干扰。这种频谱共享式的接入方式可以节约信道资源,提高频谱利用率。本文对采用放大转发（Amplify and Forward, AF）中继协议的SU发射端分别采用最小化加权均方误差和准则（Minimizing Sum of Weighted Mean Square Errors, MSWMSE）和迫零准则（Zero Forcing, ZF）对波束成形参数进行设计。仿真结果表明,两种设计方式都可以满足消除用户间干扰的要求;另外,由于基于MSWMSE准则的波束成形参数能够更好的平衡噪声和用户间干扰项对信号的损耗,因而获得更优的性能表现,而且通过调整加权系数可以满足PU用户不同的性能要求。      

认知中继协同无线通信系统功率分配和混合频谱接入方案

文章首先对Underlay 认知-中继协作（cognitive radio relay cooperation, CR-RC）系统信源和中继的功率分配问题进行了研究,获得了Underlay CR-RC系统信源、中继独立功率分配(independent power allocation, IPA）和联合功率分配（joint power allocation, JPA）方案,并给出了基于IPA和JPA的CR-RC系统的中断概率和各态历经容量的封闭解析解;其次通过对Underlay CR-RC系统中断性能的比较分析,提出了高频谱效率、高能量效率的混合Interweave-Underlay CR-RC方案。在该方案中,定义了主、从用户中断概率约束,充分考虑了主、从系统的服务质量(quality of service, QoS),当即使从用户的发射功率为零,主系统的QoS仍不能满足时,从用户以最大功率发送信号,无需考虑其对主用户的影响;当由于很强的主用户干扰,使得从用户的QoS不能得到满足时,从用户不再发射信号,发信功率为零;当主、从系统的QoS能够同时满足时,以Underlay模式工作。      

Interference‐aware spectrum handover for cognitive radio networks

Cognitive radio (CR) is a promising technique for future wireless networks, which significantly improves spectrum utilization. In CR networks, when the primary users (PUs) appear, the secondary users (SUs) have to switch to other available channels to avoid the interference to PUs. However, in the multi‐SU scenario, it is still a challenging problem to make an optimal decision on spectrum handover because of the the accumulated interference constraint of PUs and SUs. In this paper, we propose an interference‐aware spectrum handover scheme that aims to maximize the CR network capacity and minimize the spectrum handover overhead by coordinating SUs’ handover decision optimally in the PU–SU coexisted CR networks. On the basis of the interference temperature model, the spectrum handover problem is formulated as a constrained optimization problem, which is in general a non‐deterministic polynomial‐time hard problem. To address the problem in a feasible way, we design a heuristic algorithm by using the technique of Branch and Bound. Finally, we combine our spectrum handover scheme with power control and give a convenient solution in a single‐SU scenario. Experimental results show that our algorithm can improve the network performance efficiently.Copyright © 2012 John Wiley & Sons, Ltd.     

Utility‐based probabilistic call admission control for complete fairness in wireless networks

Resource reservation or the other prioritization strategies adopted by Call Admission Control (CAC) schemes in wireless networks lead to unfair resource allocation to users belonging to different service classes (SCs) due to high divergence among the respective call blocking probabilities (CBPs). In this paper, we propose dynamic optimization of probabilistic CAC (P‐CAC) schemes to assure CAC fairness among users of different SCs in wireless networks. The approach is based on users utility combined with fairness optimization, aiming at dynamically determining the probability value in the P‐CAC scheme. This optimal probability is adjusted to network ongoing traffic, CBPs of each SC, prioritization levels characterizing the SCs supported, and the users risk aversion, which reflects their behavior toward the perceived QoS. The existence and uniqueness of the optimal probability that leads to absolute fairness among the users of a wireless network are proven. Copyright © 2012 John Wiley & Sons, Ltd.     

Spatial Spectrum Reuse for Opportunistic Spectrum Access in Infrastructure-Based Systems

Opportunistic spectrum access (OSA) receives a constantly growing interest due to its potential to mitigate spectrum scarcity and meet the increasing communication needs of mobile users. OSA refers to identifying and exploiting spatiotemporal unused portions of licensed spectrum to allow communication among unlicensed–secondary users (SUs) without adverse impact to the licensees (primary users—PUs). Key parameters in OSA are the spectrum opportunities detection method used by the SUs, and the interference level perceived by the PUs. A spatial spectrum reuse framework is proposed, where broadcast messages of an infrastructure-based primary system are exploited and combined with location-aware methods to detect spectrum opportunities and establish interference-free secondary links. The study of secondary link establishment probabilities revealed a spectrum reuse of up to 25% for omni-directional and up to 90% for directional antennas. Moreover, increased throughput is achieved in both cases, with directional antennas attaining significantly better performance.     

Joint power allocation and beamforming with users selection for cognitive radio networks via discrete stochastic optimization

Cognitive radio is a promising technique to dynamic utilize the spectrum resource and improve spectrum efficiency. In this paper, we study the problem of mutual interference cancellation among secondary users (SUs) and interference control to primary users (PUs) in spectrum sharing underlay cognitive radio networks. Multiple antennas are used at the secondary base station to form multiple beams towards individual SUs, and a set of SUs are selected to adapt to the beams. For the interference control to PUs, we study power allocation among SUs to guarantee the interference to PUs below a tolerable level while maximizing SUs?? QoS. Based on these conditions, the problem of joint power allocation and beamforming with SUs selection is studied. Specifically, we emphasize on the condition of imperfect channel sensing due to hardware limitation, short sensing time and network connectivity issues, which means that only the noisy estimate of channel information for SUs can be obtained. We formulate the optimization problem to maximize the sum rate as a discrete stochastic optimization problem, then an efficient algorithm based on a discrete stochastic optimization method is proposed to solve the joint power allocation and beamforming with SUs selection problem. We verify that the proposed algorithm has fast convergence rate, low computation complexity and good tracking capability in time-varying radio environment. Finally, extensive simulation results are presented to demonstrate the performance of the proposed scheme.