Data traffic‐based analysis of delay and energy consumption in cognitive radio networks with and without resource reservation

A new opportunistic cross‐layer MAC protocol involving channel allocation and packet scheduling for cognitive radio networks is proposed. Cognitive radio allows secondary users (SUs) to exploit the available portions of the licensed spectrum bands without interfering with primary users. In particular, we consider a cognitive radio system, where SUs are equipped with two transceivers: a control transceiver and a software‐defined radio transceiver. Data traffic characteristics of SUs are considered to ameliorate system performance. So, we propose a mechanism of resource reservation to improve QoS requirements that favors successful SUs to transmit data during x time slots without interfering with primary users. The key novelty of this paper is giving priority for SUs with important data traffic and which frequently solicits data channels to transmit for the remaining time of the ongoing time slot and for the next time slots directly after checking the channel availability. We develop a new analytical model to evaluate delay parameter for two scenarios with and without resource reservation and we then investigate the impact of those scenarios on the energy consumption. We show through simulations that cognitive radio performances increase noticeably with the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

QoS‐Guaranteed Multiuser Scheduling in MIMO Broadcast Channels

This paper proposes a new multiuser scheduling algorithm that can simultaneously support a variety of different quality‐of‐service (QoS) user groups while satisfying fairness among users in the same QoS group in MIMO broadcast channels. Toward this goal, the proposed algorithm consists of two parts: a QoS‐aware fair (QF) scheduling within a QoS group and an antenna trade‐off scheme between different QoS groups. The proposed QF scheduling algorithm finds a user set from a certain QoS group which can satisfy the fairness among users in terms of throughput or delay. The antenna trade‐off scheme can minimize the QoS violations of a higher priority user group by trading off the number of transmit antennas allocated to different QoS groups. Numerical results demonstrate that the proposed QF scheduling method satisfies different types of fairness among users and can adjust the degree of fairness among them. The antenna trade‐off scheme combined with QF scheduling can improve the probability of QoS‐guaranteed transmission when supporting different QoS groups.     

A unified spectrum sensing and throughput analysis model in cognitive radio networks

Cognitive radio (CR) is a newly developed technology for increasing spectral efficiency in wireless communication systems. In the CR networks, there exist two traditional spectrum‐sharing technologies called spectrum overlay and spectrum underlay. A new hybrid overlay/underlay paradigm has also been discussed in the literature. In this work, we create a unified spectrum sensing and throughput analysis model, which is suitable for overlay, underlay, and hybrid overlay/underlay paradigms in the CR networks. In the proposed model, the energy detection scheme is employed for the spectrum sensing in the network in which the co‐channel interference is present among primary users and secondary users (SUs). The SUs' throughput in the proposed CR system model is then analyzed. The simulations are also carried out for demonstrating the performance of overlay, underlay, and hybrid overlay/underlay paradigms. Copyright © 2013 John Wiley & Sons, Ltd.     

Simultaneous spectrum sensing,data transmission and Energy harvesting in multi‐channel cognitive sensor Networks with imperfect signal cancellation

In multichannel cognitive sensor networks, the sensor users which have limited energy budgets sense the spectrum to determine the activity of the primary user. If the spectrum is idle, the sensor user can access the licensed spectrum. However, during the spectrum sensing, no data transmits. For improving the network throughput and saving more energy consumption, we propose the simultaneous spectrum sensing and data transmission scheme where the sensor receiver decodes the received signal, and from the remaining signal, the status of the channel (idle/busy) is determined. We also consider that the sensor users are powered by a radio‐frequency (RF) energy harvester. In this case, energy harvesting, data transmission, and spectrum sensing are done simultaneously. On the other hand, we select the proper sensor users for spectrum sensing and energy harvesting. We also allocate the best channels for data transmission simultaneously so that the network throughput maximizes and the constraints on the energy consumption and the detection performance are satisfied for each band. We formulate the problem and model it as a coalition game in which sensors act as game players and decide to make coalitions. Each coalition selects one of the channels to sense and transmit data, while the necessary detection probability and false alarm probability and also the energy consumption constraints are satisfied. The utility function of a coalition is proposed based on the energy consumption, false alarm probability, detection probability, and the network throughput. This paper proposes an efficient algorithm to reach a Nash‐stable coalition structure. It is demonstrated that the proposed method maximizes the network throughput and reduces the energy consumption while it provides sufficient detection quality, in comparison to other existent methods.     

Coalitional game‐based behavior analysis for spectrum access in cognitive radios

The core of cognitive radio paradigm is to introduce cognitive devices able to opportunistically access the licensed radio bands. The coexistence of licensed and unlicensed users prescribes an effective spectrum hole‐detection and a non‐interfering sharing of those frequencies. Collaborative resource allocation and spectrum information exchange are required but often costly in terms of energy and delay. In this paper, each secondary user (SU) can achieve spectrum sensing and data transmission through a coalitional game‐based mechanism. SUs are called upon to report their sensing results to the elected coalition head, which properly decides on the channel state and the transmitter in each time slot according to a proposed algorithm. The goal of this paper is to provide a more holistic view on the spectrum and enhance the cognitive system performance through SUs behavior analysis. We formulate the problem as a coalitional game in partition form with non‐transferable utility, and we investigate on the impact of both coalition formation and the combining reports costs. We discuss the Nash Equilibrium solution for our coalitional game and propose a distributed strategic learning algorithm to illustrate a concrete case of coalition formation and the SUs competitive and cooperative behaviors inter‐coalitions and intra‐coalitions. We show through simulations that cognitive network performances, the energy consumption and transmission delay, improve evidently with the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

混合频谱共享方式下多用户动态频谱分配算法

为解决混合overlay/underlay频谱共享方式下多用户动态频谱分配问题,构建了混合频谱共享方式下动态频谱分配模型,提出了基于Q学习的多用户动态频谱分配算法. 该算法在不对主用户产生有害干扰的前提下,以最大化次用户总吞吐量为目标,构建了与次用户相对应的虚拟次用户作为智能体. 通过与环境交互学习,进行信道和共享方式初选;频谱分配系统根据冲突情况和各智能体的学习结果调整信道分配策略直至次用户间无冲突. 仿真结果表明,该算法在无信道检测和信道先验知识的条件下,能根据前一时隙信道状态和次用户传输速率需求,实现动态信道分配和频谱共享方式确定,避免次用户间冲突,减少主次用户间冲突,有效提升次用户总吞吐量.     

Cross‐Layer Resource Allocation in Multi‐interface Multi‐channel Wireless Multi‐hop Networks

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi‐channel wireless multi‐hop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems — flow control; next‐hop routing; rate allocation and scheduling; power control; and channel allocation — and finally solved by a low‐complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.     

Cognitive radio network with coordinated multipoint joint transmission

Cognitive radio (CR) is considered to be a promising technology for future wireless networks to make opportunistic utilization of the unused or underused licensed spectrum. Meanwhile, coordinated multipoint joint transmission (CoMP JT) is another promising technique to improve the performance of cellular networks. In this paper, we propose a CR system with CoMP JT technique. We develop an analytical model of the received signal‐to‐noise ratio at a CR to determine the energy detection threshold and the minimum number of required samples for energy detection–based spectrum sensing in a CR network (CRN) with CoMP JT technique. The performance of energy detection–based spectrum sensing under the developed analytical model is evaluated by simulation and found to be reliable. We formulate an optimization problem for a CRN with CoMP JT technique to configure the channel allocation and user scheduling for maximizing the minimum throughput of the users. The problem is found to be a complex mixed integer linear programming. We solve the problem using an optimization tool for several CRN instances by limiting the number of slots in frames. Further, we propose a heuristic‐based simple channel allocation and user scheduling algorithm to maximize the minimum throughput of the users in CRNs with CoMP JT technique. The proposed algorithm is evaluated via simulation and found to be very efficient.     

Joint queue control and user scheduling in MIMO broadcast channel under zero‐forcing multiplexing

This paper studies the problem of queue control and user scheduling in multi‐antenna broadcast (downlink) systems under zero forcing beamforming transmit strategy. In the system, we assume that the data packet arrives randomly to the buffered transmitter. By taking the broadcast channel as a controlled queueing system, we deduce the property of queue control function that maximizes the weighted system throughput while guarantees the delay fairness among users. We also present a low‐complexity user selection algorithm with the consideration of queue state and channel state together. Simulation results show that the joint queue control and user selection policy can achieve considerable fairness and stability among users. Copyright © 2009 John Wiley & Sons, Ltd.     

Cluster‐based adaptive multispectrum sensing and access in cognitive radio networks

Spectrum sensing and access have been widely investigated in cognitive radio network for the secondary users to efficiently utilize and share the spectrum licensed by the primary user. We propose a cluster‐based adaptive multispectrum sensing and access strategy, in which the secondary users seeking to access the channel can select a set of channels to sense and access with adaptive sensing time. Specifically, the spectrum sensing and access problem is formulated into an optimization problem, which maximizes the utility of the secondary users and ensures sufficient protection of the primary users and the transmitting secondary users from unacceptable interference. Moreover, we explicitly calculate the expected number of channels that are detected to be idle, or being occupied by the primary users, or being occupied by the transmitting secondary users. Spectrum sharing with the primary and transmitting secondary users is accomplished by adapting the transmission power to keep the interference to an acceptable level. Simulation results demonstrate the effectiveness of our proposed sensing and access strategy as well as its advantage over conventional sensing and access methods in terms of improving the achieved throughput and keeping the sensing overhead low. Copyright © 2012 John Wiley & Sons, Ltd.     

A prediction and scheduling framework in centralized cognitive radio network for energy efficient non‐real time communication

Advent of Internet of Things led to an exponential rise in battery‐operated sensors transmitting small non‐real time (NRT) data regularly. To this end, this work proposes a framework for centralized cognitive radio network (CRN) that facilitates better spectrum utilization and low‐cost opportunistic NRT data transfer with high energy efficiency. The novelty of this framework is to incorporate Hidden Markov Model–based prediction within the traditional cognitive radio sensing‐transmission cycle. To minimize the prediction time, we design a Hardware‐based Hidden Markov Model engine (H2M2) to be used by the cognitive base station (CBS). CBS exploits the H2M2 engine over high primary user (PU) activity channels to minimize the collisions between PUs and NRT secondary users, thereby reducing the SU energy consumption. However, this is at the cost of reduced throughput. Taking this into account, we propose an Intersensing‐Prediction Time Optimization algorithm that identifies the predictable PU activity channels and maximizes the throughput within a PU interference threshold. Furthermore, to minimize the total battery consumption of all the SUs within CRN, a Battery Consumption Minimizing Scheduler is designed at the CBS that efficiently allocates the predictable PU channels to the NRT SUs. By exploiting the unutilized high PU activity channels, the proposed Centralized Scheduling, Sensing and Prediction (CSSP) framework improves the spectral efficiency of the CRN. Exhaustive performance studies show that CSSP outperforms traditional nonpredictive sensing techniques in terms of energy efficiency and interference management. Finally, through a proof of concept, we validate the ability of CSSP framework in enabling NRT communication.     

A distributed pricing algorithm for achieving network‐wide proportional fairness

Proportional fairness (PF) scheduling achieves a balanced tradeoff between throughput and fairness and has attracted great attention recently. However, most previous work on PF only considers the single cell scenario. This paper focuses on the problem of achieving network‐wide PF in a generalized multiple base station multiple user network. The problem is formulated as a maximization model and solved using the dual method. By decomposing the dual objective function, we get a distributed pricing based algorithm. Optimality of this algorithm is presented. Although the algorithm is derived using fixed link rate assumption, it can still apply in the presence of time‐varying rates. The proposed algorithm is suitable for distributed systems in the sense that it does not need any inter base station communication at all. Simulations illustrate that the proposed distributed network‐wide PF scheduling algorithm achieves almost the same performance as the centralized one. Compared with traditional local PF (LPF) scheduling, the network‐wide PF scheduling achieves higher throughput, lower throughput oscillation, and greater fairness. Copyright © 2010 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.     

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.     

Efficient error detection in soft data fusion for cooperative spectrum sensing

The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.     

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.     

A Parallel Repeated Auction for Spectrum Allocation in Distributed Cognitive Radio Networks

Cognitive radio (CR) is applied to solve spectrum scarcity. Although the auction theory and learning algorithm have been discussed in previous works, their combination is not yet researched in the distributed CR networks, where secondary users (SUs) can occupy several channels simultaneously by assuming that one channel can be accessed by at most one SU. A parallel repeated auction scheme is proposed to solve resource allocation in multi-user multi-channel distributed spectrum-overlay CR networks. A novel bid scheme in the light of the first-price sealed auction is designed to balance the system utility and allocation fairness. The proposed auction scheme can be developed based on a learning algorithm and be applied to the scenarios where the cooperation among SUs is unavailable. Under the assumption of limited entry budget, SUs can directly decide whether or not to participate in spectrum auction by comparing the possible bid with access threshold which can be applied into situations that SUs have different transmit power. Theoretical analysis and simulation results show that, compared with original myopic scheme and original genie-aided scheme, the proposed auction scheme can obtain a considerable improvement in efficiency and fairness, especially with adequate available resources.     

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.     

Adaptive opportunistic fair scheduling over multiuser spatial channels

We consider the problem of opportunistic fair scheduling (OFS) of multiple users in downlink time-division multiple-access (TDMA) systems employing multiple transmit antennas and beamforming. OFS is an important technique in wireless networks to achieve fair bandwidth usage among users, which is performed on a per-frame basis at the media access control layer. Multiple-transmit-antenna beamforming provides TDMA systems with the capability of supporting multiple concurrent transmissions, i.e., multiple spatial channels at the physical layer. Given a particular subset of users and their channel conditions, the optimal beamforming scheme can be calculated. The multiuser opportunistic scheduling problem then refers to the selection of the optimal subset of users for transmission at each time instant to maximize the total throughput of the system subject to a certain fairness constraint on each individual user's throughput. We propose discrete stochastic approximation algorithms to adaptively select a better subset of users. We also consider scenarios of time-varying channels for which the scheduling algorithm can track the time-varying optimal user subset. We present simulation results to demonstrate the performance of the proposed scheduling algorithms in terms of both throughput and fairness, their fast convergence, and the excellent tracking capability in time-varying environments.     

Transmit‐sense‐receive–based cognitive antijamming for airborne ad hoc networks

In this paper, a transmit‐sense‐receive mode–based simultaneous transmit‐and‐receive cognitive antijamming (SCAJ) strategy is proposed to enhance spectrally efficient of airborne networks in congested electromagnetic spectrum environment. We explore the performance of spectrum sensing based on energy detection in SCAJ system. The tight close form expressions of jamming detection and false‐alarm probability are derived under different channels, the throughput of individual SCAJ system is analyzed, and SCAJ transceiver‐based airborne ad hoc network capacity is presented for air platform equipping with digital beamforming antennas. Simulation results show that proposed SCAJ technology can improve the antijamming capability and airborne ad hoc network capacity compared to the half‐duplex cognitive antijamming scheme. It is an effective approach to solve the problem of designing airborne networks arise from the limited availability of spectrum and the desire to provide much higher data rates.