Distributed Cognitive Radio Networks Research Articles

A Distributed Network Q-Mac with Quality of Service Provisioning

A new distributed Cognitive Radio network Q-MAC has been proposed in the paper. The Q-MAC Protocol provides an efficient approach to address quality of service provisioning of delay sensitive applications. This MAC Protocol guarantees the QoS of network for such applications by giving priority to applications with higher time delay requirements in the stage of channel reservation. The performance of the Q-MAC Protocol with those of two existing protocols are compared. The results show that the Q-mac provides better throughput than those existing protocols. The analysis model and simulation results show that the designed Q-MAC Protocol is simple and effective. This Protocol can recognize and meet the QoS requirements of delay-sensitive applications and can effectively deal with the problem of multi-channel hidden terminal.

Distributed Collaborative Spectrum Sensing Using 1-Bit Compressive Sensing in Cognitive Radio Networks

In cognitive radio (CR) networks, spectrum sensing is an essential task for enabling dynamic spectrum sharing. However, the problem becomes quite challenging in wideband spectrum sensing due to high sampling pressure, limited power and computing resources, and serious channel fading. To overcome these challenges, this paper proposes a distributed collaborative spectrum sensing scheme based on 1-bit compressive sensing (CS). Each secondary user (SU) performs local 1-bit CS and obtains support estimate information from the signal reconstruction. To utilize joint sparsity and achieve spatial diversity, the support estimate information among the network is fused via the average consensus technique based on distributed computation and one-hop communications. Then the fused result on support estimate is used as priori information to guide the next local signal reconstruction, which is implemented via our proposed weighted binary iterative hard thresholding (BIHT) algorithm. The local signal reconstruction and the distributed fusion of support information are alternately carried out until reliable spectrum detection is achieved. Simulations testify the effectiveness of our proposed scheme in distributed CR networks.

Scalable Learning-Based Heterogeneous Multi-Band Multi-User Cooperative Spectrum Sensing for Distributed IoT Systems

The emerge of Internet of Things (IoT) brings up revolutionary changes to wireless communications. Cognitive radio (CR) can be seen as one of the prominent solutions to spectrum scarcity in IoT, where multi-band cooperative spectrum sensing (CSS) is the key. However, lack of centralized control and increase in number of devices place a room for many challenges. One of the main challenges is secondary users' (SUs') scheduling to sense a subset of channels in heterogeneous distributed CR networks (CRNs). To overcome the aforementioned challenge, in this paper, we propose a novel heterogeneous multi-band multi-user CSS (HM2CSS) scheme. The proposed scheme allows heterogeneous SUs to sense multiple channels and consists of two stages. We formulate a mathematical model to optimize leader-selection for each channel in the first stage. We then formulate another optimization problem to determine corresponding cooperative SUs to sense these channels in the second stage. After that, diffusion learning is used to decide on the availability of channels. Simulations illustrate that the proposed scheme improves detection performance and CRN throughput, is scalable in terms of detection performance, and provides fair energy consumption for CSS on all channels compared to existing multi-band CSS schemes.

Multichannel MAC protocol with dynamic backoff contention for distributed cognitive radio networks

Multiuser access is a critical issue in distributed cognitive radio networks (DCRNs), as the collisions among the competing secondary users (SUs) may decrease the network throughput significantly. In order to reduce the collisions, we propose a dynamic backoff algorithm to find an optimal backoff contention window to maximize the network throughput and reduce the channel access delay. Based on the proposed algorithm, a multichannel medium access control (MAC) protocol with dynamic backoff contention (MMAC-DB) is designed. In this protocol, the time duration of each channel is divided into four phases: idle, sensing-sharing, contention, and data transmission. The dynamic backoff algorithm is implemented in the contention phase. Moreover, a duration tradeoff is made between the data transmission phase and the contention phase. The effectiveness of the proposed protocol is examined by extensive simulations, which shows that the proposed protocol can enhance the throughput and reduce the channel access delay.

Cross-Layer Analysis and Optimization on Access Delay in Channel-Hopping-Based Distributed Cognitive Radio Networks

In channel-hopping (CH)-based distributed cognitive radio networks (CRNs), the time duration that secondary users (SUs) spend for establishing communication links is called access delay. To evaluate access delay, we propose an access delay model by jointly considering imperfect spectrum sensing and multi-channel multi-SU transmission, from the cross-layer perspective. The model considers two typical scenarios. The first scenario assumes that the SUs do not use contention scheme (CS) which indicates that the time slot is relatively shorter to just allow a transmission. The second scenario assumes that the SUs employ CS [i.e., modified Distributed Coordination Function (DCF)-based Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) in this paper], which indicates that the time slot is long enough to regulate multiple transmissions. We then propose a bio-inspired algorithm for the first scenario and a self-adaptive step-length algorithm for the second scenario to search for the optimal values of spectrum sensing parameters. The theoretical analysis and simulation results validate the proposed access delay model and show that the proposed algorithms can reduce the most redundant computation. They also show that the optimization of cross-layer parameters can significantly decrease SUs’ access delay. Moreover, we conduct a cost-benefit analysis to evaluate the performance of the two scenarios.

Agent-Based Model of the Spectrum Auctions with Sensing Imperfections in Dynamic Spectrum Access Networks

Cognitive radio (CR) is the underlying platform for the application of dynamic spectrum access (DSA) networks. Although the auction theory and spectrum trading mechanisms have been discussed in the CR related works, their joint techno-economic impact on the efficiency of distributed CR networks has not been researched yet. In this paper we assume heterogeneous primary channels with network availability statistics unknown to each secondary user (SU) terminal. In order to detect the idle primary user (PU) network channels, the SU terminals trigger regularly the spectrum sensing mechanism and make the cooperative decision regarding the channel status at the fusion center. The imperfections of the spectrum mechanism create the possibility of the channel collision, resulting in the existence of the risk (in terms of user collision) in the network. The spectrum trading within SU network is governed by the application of the sealed-bid first-price auction, which takes into account the channel valuation as well as the statistical probability of the risk existence. In order to maximize the long-term payoff, the SU terminals take an advantage of the reinforcement comparison strategy. The results demonstrate that in the investigated model, total revenue and total payoff of the SU operator (auctioneer) and SU terminals (bidders) are characterized by the existence of the global optimum, thus there exists the optimal sensing time guaranteeing the optimum economic factors for both SU operator and SU terminals.

A Novel Decentralized Scheme for Cooperative Compressed Spectrum Sensing in Distributed Networks

Compressed sensing (CS) recently turns out to be an effective approach to alleviate the sampling bottleneck in wideband spectrum sensing. However, the computation overhead incurred by compressed reconstruction is nontrivial, especially in a power-constrained cognitive radio (CR). Moreover, additional information, which is generally unavailable in practice, is needed in conventional CS-based wideband spectrum sensing schemes to improve the reconstruction quality as well as the detection performance. To address these issues, this paper proposes a novel decentralized scheme for cooperative compressed spectrum sensing in distributed CR networks. Our key observation is that the sparse signals are unnecessary to be reconstructed since the task of spectrum sensing is only interested in the spectrum occupancy status. The major novelty of the proposed scheme relates to the use of Karcher mean as a statistic indicating the spectrum occupancy status, thereby eliminating the compressed reconstruction stage and significantly reducing the computational complexity. Considering limited communication resources per CR, a decentralized implementation based on alternating direction method of multipliers is presented to calculate the Karcher mean via one-hop communications only. The superior performance of the proposed scheme is demonstrated by comparing with several existing decentralized schemes in terms of detection performance, communication overhead, and computational complexity.

Reputation-based secure spectrum situation fusion in distributed cognitive radio networks

In distributed cognitive radio (CR) network, the cooperative spectrum situation sensing based on consensus scheme may be disrupted by spectrum sensing data falsification (SSDF) attacks. In this paper, a secure spectrum situation fusion scheme based on reputation is proposed to counter attacks. The neighboring nodes of secondary users (SUs) get the Corresponding dynamic trust value according to their behavior, which restrict the impact of the malicious behavior on the premise to ensure information interaction of normal nodes. Theoretical analysis and simulation results show that the consensus fusion scheme based on reputation has better performance than the existing algorithm which eliminates the neighboring node with the biggest deviation value from mean value. It demonstrates that the proposed scheme not only achieves better convergence properties but also has higher detection probability than the existing scheme in the process of spectrum situation fusion.

Secure Cooperative Spectrum Sensing and Allocation in Distributed Cognitive Radio Networks

Cognitive radio networks (CRNs) are an emerging wireless communications technique for resolving the significant spectrum scarcity problem. Despite their promising characteristics, CRNs also introduce new security threats, especially the internal attacks during the spectrum sensing and allocation process, which can degrade the efficiency of spectrum sensing and allocation. To address this issue, this paper proposes a distributed secure cooperative spectrum sensing strategy (DSCS) based on a dynamic reputation model to defend against attacks and provide reliable spectrum sensing. Moreover, the reputation values are used as weights in a novel distributed cheat-proof spectrum allocation strategy (DCSA) based on the Vickrey-Clarke-Groves (VCG) mechanism. Both theoretical analysis and simulation results indicate that the proposed DSCS and DCSA strategies can provide an effective countermeasure against the internal spectrum sensing data falsification (SSDF) attacks through enabling secondary users to obtain more accurate cooperative sensing results in adversarial environments.

Adaptive and Autonomous Channel Access Methods for Distributed Cognitive Radios

In distributed multichannel cognitive radio (CR) networks, autonomous CRs face competition from one another to access the potentially available channels. Efficient resource allocation in such scenarios can be achieved by carrying out negotiation among distributed CRs via a coordinator (base station) or with the help of a common control channel. While the use of a coordinator or a common control channel simplifies the problem, it may create significant signaling overhead or potential contention under heavy load. Opportunistic channel selection strategies that require no centralized coordination among the autonomous CRs are surveyed in this paper and also novel results related to our own proposed $$\gamma $$?-persistent adaptive strategy are provided. Unlike our previous work in Khan et al. (IEEE Trans Mob Comput 12(2): 2013), we evaluate the performance of the proposed $$\gamma $$?-persistent strategy in terms of different performance metrics such as: (1) Average throughput of an individual CR; (2) Probability of finding a channel free in first step (given that the channel is free) for an autonomous CR; and (3) Average number of unsuccessful transmissions experienced by a CR. Using these performance metrics, we compare the performance of the proposed strategy with two other distributed strategies and also with a centralized strategy. We show that the proposed strategy allows the CRs to find a free channel with high probability in the first sensing step (given that the channel is free). This reduces the overhead of multiple sensing steps incurred by an autonomous CR. The reduced number of sensing steps required to find a channel free in turn improves throughput per time slot of a CR. Moreover, the proposed strategy reduces the likelihood of unsuccessful transmissions by CRs which in turn improves throughput and also reduces the transmission attempt costs of an autonomous CR.

Preemptive Opportunistic MAC Protocol in Distributed Cognitive Radio Networks

A preemptive opportunistic cognitive radio (CR) medium access control (MAC) protocol, which is called PO-MAC, is proposed for distributed CR networks. PO-MAC consists of three main phases: network initialization, reporting, and contention. The primary user (PU) channel exclusively assigned to each secondary user (SU) is sensed during the sensing period, and the sensing result is then reported to all other SUs without collisions during the reporting phase. Using the sensing results, SUs can preempt and make use of free channels via a contention method during the contention phase. It is demonstrated that PO-MAC outperforms existing CR MAC protocols in terms of the end-to-end delay and throughput performance. Further, it is shown that PO-MAC effectively operates when used in real-time services such as voice over Internet protocol.

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.

Social Incentives for Cooperative Spectrum Sensing in Distributed Cognitive Radio Networks

Cooperative spectrum sensing has been considered as a promising approach to improve the sensing performance in distributed cognitive radio networks. However, there may exist some selfish secondary users (SUs) who are unwilling to cooperate. The presence of selfish SUs could cause catastrophic damage to the performance of cooperative spectrum sensing. Following the social perspective, we propose a Social Tie-based Incentive Scheme (STIS) to deal with the selfish problem for cooperative spectrum sensing in distributed cognitive radio networks. This scheme inspires SUs to contribute sensing information for the SUs who have social tie but not others, and such willingness varies with the strength of social tie value. The evaluation of each SU’s social tie derives from its contribution for others. Finally, simulation results validate the effectiveness of the proposed scheme.

Design of OMC-MAC: An Opportunistic Multi-Channel MAC with QoS Provisioning for Distributed Cognitive Radio Networks

Dynamic resource availability and lack of central control unit offer many challenges while designing medium access control (MAC) protocol for a distributed cognitive radio network (DCRN). In this paper, we propose a novel MAC design for DCRN which provides an efficient approach to address quality of service (QoS) requirements of delay sensitive applications by defining higher priority to such applications during channel reservation. It also combats other major challenges such as efficient spectrum utilization, multi-channel hidden terminal problem (MHTP) and collision with primary user (PU) due to sensing error at SU. We develop an analytical framework to study the performance of the proposed protocol. We then compare the performance of proposed protocol with those of two existing protocols. Comparison results show that proposed MAC outperforms the existing protocols by providing better throughput and reducing DCRN users' collision probability with PUs in presence of sensing error. The results achieved from the analytical model and validated by simulations show that our simple yet efficient design identifies and fulfils the QoS requirements of delay sensitive applications, achieves excellent spectrum utilization, shows superb robustness in presence of sensing errors and handles MHTP effectively.

Interactive Admission and Power Control Protocol for Cooperative Spectrum Underlay in Distributed Cognitive Radio Networks

In this paper, we present a distributed and interactive admission and power control protocol for spectrum underlay environments. The protocol enables distributed primary users (PUs) to estimate and adjust the level of tolerable interference as their transmitting powers evolve to a given signal-to-interference-plus-noise ratio (SINR) target. The protocol also guides the powers of distributed secondary users (SUs) to achieve their own targets while restricting the transmitting powers from SUs so as not to interfere with the PUs. This restriction of interference from SUs to PUs is an essential part of cognitive radio networks (CRNs) and is facilitated by sending a warning tone from PUs to SUs in the proposed protocol. The SUs that have frequently received the warning tones turn off their transmitters and so autonomously drop from the system. This paper proves that, under the proposed interactive protocol, every PU finally achieves its target if it is originally feasible without SUs and the transmit powers of remaining SUs converge to a fixed point. The proposed method protects PUs perfectly in the sense that all the PUs reach their targets after power control. Numerical investigation shows how safely PUs are protected and how well SUs are admitted as a function of protocol parameters, the frequency of warning tones, the number of SUs to be admitted and the number of active PUs.

Performance Analysis of a Busy Cognitive Multi-Channel MAC Protocol

With rapid development of wireless technology, the fixed resource allocation strategies that are utilized in wireless networks to guarantee the Quality of Service lead to the shortage of radio resources. The cognitive radio (CR) technology has been introduced to address this problem, but this technique might increase the interference to primary users. In this paper, we consider the distributed CR network scenarios, analyze the performance of a Cognitive MAC Protocol where CR nodes sense channel that is in idle state to send cooperative information, and propose an alternative Cognitive Mac Protocol based on CR nodes send cooperative information when they sense the channel that is in busy state. Comparing the performance between previous protocol and our proposed protocol, we find that the latter can reduce the interference since misjudge obviously with more CR nodes, and eliminates the phenomenon of false detection completely to make full use of spectral efficiency without the influence of white noise.