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。      

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.     

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.     

Quality of service‐aware coordinated dynamic spectrum access: prioritized Markov model and call admission control

In this paper, we propose a heterogeneous‐prioritized spectrum sharing policy for coordinated dynamic spectrum access networks, where a centralized spectrum manager coordinates the access of primary users (PUs) and secondary users (SUs) to the spectrum. Through modeling the access of PUs and multiple classes of SUs as continuous‐time Markov chains, we analyze the overall system performance with consideration of a grade‐of‐service guarantee for both the PUs and the SUs. In addition, two new call admission control (CAC) strategies are devised in our models to enhance the maximum admitted traffic of SUs for the system. Numerical results show that the proposed heterogeneous‐prioritized policy achieves higher maximum admitted traffic for SUs. The trade‐off between the system's serving capability and the fairness among multiple classes of SUs is also studied. Moreover, the proposed CAC strategies can achieve better performance under max‐sum, proportional, and max‐min fairness criteria than the conventional CAC strategies. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Spectrum sharing in multi-channel cooperative cognitive radio networks: a coalitional game approach

In this paper, we study a coalitional game approach to resource allocation in a multi-channel cooperative cognitive radio network with multiple primary users (PUs) and secondary users (SUs). We propose to form the grand coalition by grouping all PUs and SUs in a set, where each PU can lease its spectrum to all SUs in a time-division manner while the SUs in return assist PUs’ data transmission as relays. We use the solution concept of the core to analyze the stability of the grand coalition, and the solution concept of the Shapley value to fairly divide the payoffs among the users. Due to the convexity of the proposed game, the Shapley value is shown to be in the core. We derive the optimal strategy for the SU, i.e., transmitting its own data or serving as a relay, that maximizes the sum rate of all PUs and SUs. The payoff allocations according to the core and the Shapley value are illustrated by an example, which demonstrates the benefits of forming the grand coalition as compared with non-coalition and other coalition schemes.     

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.     

A novel model for implicit cooperation between primary users and secondary users in cognitive radio‐cooperative communication systems

Recently, cooperative communications are used to improve the communications performance in cognitive radio networks. In this paper, we present a new model for implicit cooperation between primary users and secondary users (SUs), where SUs transparently relay packets of primary transmitters (PTs) towards their primary receivers encouraging PTs to reduce their transmit power, which in turn will reduce the total interference at some intended secondary receivers (SRs). Secondary relays work as full‐duplex amplify‐and‐forward (AF) cooperative nodes. The system is modeled as a multi‐armed restless bandit problem where the optimal policy for joint relay selection and transmit power allocation is obtained in a distributed way taking both instantaneous channel states and residual energy into consideration. We solve the problem using primal‐dual priority‐index heuristic, which can reduce the online computations and implementation complexity. Simulation results show that this model can benefit both sides where the energy consumption at PTs is reduced significantly and signal to interference plus noise ratio (SINR) at the intended SUs is increased about 50% in average.     

Cooperative primary–secondary dynamic spectrum leasing game via decentralized bargaining

Dynamic spectrum leasing (DSL) has been proposed as a solution for better spectrum utilization. Most of the work focused on non-cooperative game to model primary/secondary users interactions in DSL approach. Some others introduced cooperative game just for secondary users (SUs). In this paper, both primary users (PUs) and SUs incentives and level of satisfactions are considered. Nash bargaining is developed with both PUs and SUs as bargainers. A simple pricing approach is introduced which makes the proposed method practically feasible. On one hand, SUs adjust their power regarding to price and tolerable interference which are announced by PU. On the other hand, PU adjusts its tolerable interference to maximize its profit. Simulation results verify the viability of proposed method.     

Fair and Efficient Spectrum Splitting for Unlicensed Secondary Users in Cooperative Cognitive Radio Networks

In cooperative cognitive radio networks (CCRNs), a licensed primary-user (PU) is allowed to leverage several unlicensed secondary-users (SUs) to relay its traffic. In this paper, a staged dynamic spectrum allocation (DSA) scheme is proposed for CCRNs. In the first stage, the network is uncongested. A simple pricing based DSA scheme is proposed for the PUs to lease their idled frequency bands to the SUs. And, hence, the initial quality of service (QoS) demands (in terms of the minimum rate requirements) of the PUs and the SUs are both satisfied through direct transmission on the allocated frequency bands. In the second stage, the network reaches the full-loaded situation. Therefore, a cooperative relaying based DSA scheme is proposed to stimulate the PUs to split more extra frequency bands to fulfill the increased QoS demands of the SUs, on condition that the QoS of the PUs are well maintained. By applying the cooperative bargaining game theory in the proposed cooperative relaying based DSA, on the one hand, the SUs can get fairness rate-rewards from the PUs according to the level of contribution that they can make to compensate the PUs for the rate-losses. Hence, the increased QoS demands of the SUs can be accommodated in short term. On the other hand, the PUs could retain the SUs successfully to obtain the long-term revenue, on condition that their QoS constraints are still satisfied. Finally, the analysis results of the proposed bargaining game theoretic DSA scheme (in the second stage) are testified through computer simulations.     

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 power efficient cooperative spectrum sensing under reduced bandwidth using location information

Frequency spectrum sharing between licensed primary users (PUs) and unlicensed secondary users (SUs) requires the SUs to reliably detect the spectrum occupancy. Due to multipath fading, single terminal detection is unreliable and results in a high probability of missed detection. This is solved by applying cooperative detection. However, when the number of SUs is large, the bandwidth for reporting their sensing results to the common receiver will be very huge. In this paper, we propose an improved frequency divisional cluster based cooperative spectrum sensing based on the location information which employs a censoring method to reduce the average number of sensing bits sent to the common receiver. The reduction in the number of sensing bits using proposed method in turn reduces the total transmission power of the secondary users in the cognitive network thus improving its battery life.     

Robust Probabilistic Distributed Power Control Algorithm for Underlay Cognitive Radio Networks under Channel Uncertainties

Due to limited cooperation among users and erratic nature of wireless channel, it is difficult for secondary users (SUs) to obtain exact values of system parameters, which may lead to severe interference to primary users (PUs) and cause communication interruption for SUs. In this paper, we study robust power control problem for spectrum underlay cognitive radio networks with multiple SUs and PUs under channel uncertainties. Precisely, our objective is to minimize total transmit power of SUs under the constraints that the satisfaction probabilities of both interference temperature of PUs and signal-to-interference-plus-noise ratio of SUs exceed some thresholds. With knowledge of statistical distribution of fading channel, probabilistic constraints are transformed into closed forms. Under a weighted interference temperature constraint, a globally distributed power control iterative algorithm with forgetting factor to increase convergence speed is obtained by dual decomposition methods. Numerical results show that our proposed algorithm outperforms worst case method and non-robust method.     

Enhancing cooperative spectrum sensing in cognitive radio ad hoc networks using priority-based two-stage detection model

Cooperation among unlicensed secondary users was more significant in cognitive radio ad hoc networks (CRAHNs). The main challenges of CRAHNs now a day address the main issues of spectrum scarcity and underutilization. Due to the lack of channel sensing, cooperative spectrum sensing (CSS) is the main challenge in CRAHNs. Efficient CSS is more essential to enhance the detection of performance by utilizing the theoretical studies of spatially distributed secondary users (SUs). This paper uses the priority-based two-stage detection model (PBTSDM) to analyze the cooperation strategy among secondary users (SUs) and primary users (PUs). SUs in distributed CSS sense continuously amongst themselves and take unified decision on the presence or absence of PUs by using entropy-based energy detection mechanism. The simulation results reveal that the sensing accuracy in terms of sensing time and energy efficiency (in terms of minimum energy consumption) increased significantly by using the proposed scheme.

     

Cognitive cooperative networks with decode‐and‐forward relay selection under interference constraints of multiple primary users

In this paper, we study the performance of cognitive cooperative radio networks under the peak interference power constraints of multiple primary users (PUs). In particular, we consider a system model where the secondary user communication is assisted by multiple secondary relays (SRs) that operate in the decode‐and‐forward mode to relay the signal from a secondary transmitter to a secondary receiver. Moreover, we assume that the transmit powers of the secondary transmitter and the SRs are subject to the peak interference power constraints of multiple PUs that operate in their coverage range. Given this system setting, we first derive the cumulative distribution function of the instantaneous end‐to‐end signal‐to‐noise ratio. Then, we obtain a closed‐form expression for the outage probability and an exact expression for the symbol error probability of the considered network. These tractable formulas enable us to examine the impact of the presence of multiple PUs on the performance of the considered spectrum sharing system. Furthermore, our numerical results show that system performance is improved significantly when the number of SRs increases or the channel mean power from the secondary user to the PUs is low. Also, any increase in the number of PUs in the coverage range of the secondary transmitter or the SRs leads to degradation in system performance. Finally, Monte Carlo simulations are provided to verify the correctness of our analytical results. Copyright © 2013 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.     

Spectrum auction with interference constraint for cognitive radio networks with multiple primary and secondary users

Extensive research in recent years has shown the benefits of cognitive radio technologies to improve the flexibility and efficiency of spectrum utilization. This new communication paradigm, however, requires a well-designed spectrum allocation mechanism. In this paper, we propose an auction framework for cognitive radio networks to allow unlicensed secondary users (SUs) to share the available spectrum of licensed primary users (PUs) fairly and efficiently, subject to the interference temperature constraint at each PU. To study the competition among SUs, we formulate a non-cooperative multiple-PU multiple-SU auction game and study the structure of the resulting equilibrium by solving a non-continuous two-dimensional optimization problem, including the existence, uniqueness of the equilibrium and the convergence to the equilibrium in the two auctions. A distributed algorithm is developed in which each SU updates its strategy based on local information to converge to the equilibrium. We also analyze the revenue allocation among PUs and propose an algorithm to set the prices under the guideline that the revenue of each PU should be proportional to its resource. We then extend the proposed auction framework to the more challenging scenario with free spectrum bands. We develop an algorithm based on the no-regret learning to reach a correlated equilibrium of the auction game. The proposed algorithm, which can be implemented distributedly based on local observation, is especially suited in decentralized adaptive learning environments as cognitive radio networks. Finally, through numerical experiments, we demonstrate the effectiveness of the proposed auction framework in achieving high efficiency and fairness in spectrum allocation.     

Multiuser two‐way relay processing and power control methods for cognitive radio networks

We consider a cognitive radio system where a secondary network shares the spectrum band with a primary network. Aiming at improving the frequency efficiency of the secondary network, we set a multiantenna relay station in the secondary network to perform two‐way relaying. Three linear processing schemes at the relay station based on zero forcing, zero forcing‐maximum ratio transmission, and minimum mean square error criteria are derived to guarantee the quality of service of primary users and to suppress the intrapair and interpair interference among secondary users (SUs). In addition, the transmit power of SUs is optimized to maximize the sum rate of SUs and to limit the interference brought to PUs. Numerical results show that the proposed multiuser two‐way relay processing schemes and the optimal power control policies can efficiently limit the interference caused by the secondary network to primary users, and the sum rate of SUs can also be greatly improved. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamic spectrum sharing in cognitive radio networks using truthful mechanisms and virtual currency

In cognitive radio networks, there are scenarios where secondary users (SUs) utilize opportunistically the spectrum originally allocated to primary users (PUs). The spectrum resources available to SUs fluctuates over time due to PUs activity, SUs mobility and competition between SUs. In order to utilize these resources efficiently spectrum sharing techniques need to be implemented. In this paper we present an approach based on game-theoretical mechanism design for dynamic spectrum sharing. Each time a channel is not been used by any PU, it is allocated to SUs by a central spectrum manager based on the valuations of the channel reported by all SUs willing to use it. When an SU detects a free channel, it estimates its capacity according to local information and sends the valuation of it to the spectrum manager. The manager calculates a conflict-free allocation by implementing a truthful mechanism. The SUs have to pay for the allocation an amount which depends on the set of valuations. The objective is not to trade with the spectrum, but to share it according to certain criteria. For this, a virtual currency is defined and therefore monetary payments are not necessary. The spectrum manager records the credit of each SU and redistributes the payments to them after each spectrum allocation. The mechanism restricts the chances of each SU to be granted the channel depending on its credit availability. This credit restriction provides an incentive to SUs to behave as benefit maximizers. If the mechanism is truthful, their best strategy is to communicate the true valuation of the channel to the manager, what makes possible to implement the desired spectrum sharing criteria. We propose and evaluate an implementation of this idea by using two simple mechanisms which are proved to be truthful, and that are tractable and approximately efficient. We show the flexibility of these approach by illustrating how these mechanisms can be modified to achieve different sharing objectives which are trade-offs between efficiency and fairness. We also investigate how the credit restriction and redistribution affects the truthfulness of these mechanisms.