Multi-channel Cognitive Radio Networks Research Articles

Cross-layer modeling and optimization of multi-channel cognitive radio networks under imperfect channel sensing

In this paper, we consider a multi-channel cognitive radio network with multiple secondary users (SUs) and analyze the performance of users in the network. We assume primary users (PUs) adopt the automatic repeat request (ARQ) protocol at the medium access control layer. We have two main goals. Our first goal is to develop a cross-layer performance model of the cognitive radio network by considering the retransmission characteristics of the ARQ protocol and the interference between PUs and SUs due to imperfect channel sensing. Using the cross-layer performance model we analyze the throughput performance of SUs and the delay performance of PUs. &nbsp Our second goal is to propose an optimal channel sensing method that maximizes the throughput performance of SUs while a given delay requirement of PUs is guaranteed. To this end, using our cross-layer performance model, we formulate an optimization problem and solve it to get an optimal channel sensing method that satisfies the design objectives. Numerical and simulation results are provided to validate our analysis and to investigate the performance of the optimal channel sensing method.

On the Performance of Channel Assembling and Fragmentation in Cognitive Radio Networks

Flexible channel allocation may be applied to multi-channel cognitive radio networks (CRNs) through either channel assembling (CA) or channel fragmentation (CF). While CA allows one secondary user (SU) occupy multiple channels when primary users (PUs) are absent, CF provides finer granularity for channel occupancy by allocating a portion of one channel to an SU flow. In this paper, we investigate the impact of CF together with CA for SU flows by proposing a channel access strategy which activates both CF and CA and correspondingly evaluating its performance. In addition, we also consider a novel scenario where CA is enabled for PU flows. The performance evaluation is conducted based on continuous time Markov chain (CTMC) modeling and simulations. Through mathematical analyses and simulation results, we demonstrate that higher system capacity can be achieved indeed by jointly employing both CA and CF, in comparison with the CA-only strategies. However, this benefit is obtained only under certain conditions which are pointed out in this paper. Furthermore, the theoretical capacity upper bound for SU flows with both CF and CA enabled is derived when PU activities are relatively static compared with SU flows.

Joint cooperative spectrum sensing and MAC protocol design for multi-channel cognitive radio networks

In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.

Channel prediction-based channel allocation scheme for multichannel cognitive radio networks

Cognitive radio (CR) has been proposed to solve the spectrum utilization problem by dynamically exploiting the unused spectrum. In CR networks, a spectrum selection scheme is an important process to efficiently exploit the spectrum holes, and an efficient channel allocation scheme must be designed to minimize interference to the primary network as well as to achieve better spectrum utilization. In this paper, we propose a multichannel selection algorithm that uses spectrum hole prediction to limit the interference to the primary network and to exploit channel characteristics in order to enhance channel utilization. The proposed scheme considers both the interference length and the channel capacity to limit the interference to primary users and to enhance system performance. By using the proposed scheme, channel utilization is improved whereas the system limits the collision rate of the CR packets.

Channel Assembling with Priority-Based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation

With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocated to real-time and elastic users and channel access opportunities are distributed between these two queues in a way that real-time services receive higher priority. Two queuing schemes are introduced based on the delay tolerance of interrupted elastic services. Furthermore, continuous time Markov chain models are developed to evaluate the performance of the proposed CA strategy with queues, and the correctness as well as the preciseness of the derived theoretical models are verified through extensive simulations. Numerical results demonstrate that the integration of queues can further increase the capacity of the secondary network and spectrum utilization while decreasing blocking probability and forced termination probability.

Impact of Fairness Models on Resource Allocation in a QoS Constrained Competitive Cognitive Radio Network

We consider a multi-channel cognitive radio network (CRN) where multiple secondary users share a single channel and multiple channels are simultaneously used by a single secondary user (SU) to satisfy their rate requirements. In this competitive CRN, our interest is in determining optimal power and rate distribution choices for each SU while maintaining fairness in of across all SUs. Unlike prior approaches that focus on resource allocation based on instantaneous quality of service (QoS), our approach to fairness encompasses both current and prior history of user experience with respect to QoS (collectively referred to as of experience). Specifically, we quantify user experience over time by introducing dynamic fairness weights for each SU in the resource allocation framework. The dynamics of the weights are governed by social behavioral models. In this paper, we study the effect of Homo Egualis (HE), Homo Parochius (HP) and Homo Reciprocan (HR) models. HE or HR based fairness weights in the resource allocation scheme result in a proportionate resource allocation with respect to users demand. Hence, with respect to unweighted allocation scheme (allocation scheme based on instantaneous QoS), the fairness weights in the resource allocation scheme cause some users to sacrifice resources and some users to gain resources to maintain a balance in allocated resources. HP based fairness weights show that collaboration among users through forming group result to achieve a proportionate resource allocation with respect to demand at least across the users of the collaborating group. Simulation results show that considering dynamic fairness weights in the resource allocation scheme provides a better system level fairness index (based on Jain fairness index (1)) relative to the unweighted allocation scheme.. Keywords-Competitive CRN; Quality of Experience; Fairness; Jain fairness index; Home Egualis; Homo Parochius; Homo Reciprocan.

Channel Selection Based on Trust and Multiarmed Bandit in Multiuser, Multichannel Cognitive Radio Networks

This paper proposes a channel selection scheme for the multiuser, multichannel cognitive radio networks. This scheme formulates the channel selection as the multiarmed bandit problem, where cognitive radio users are compared to the players and channels to the arms. By simulation negotiation we can achieve the potential reward on each channel after it is selected for transmission; then the channel with the maximum accumulated rewards is formally chosen. To further improve the performance, the trust model is proposed and combined with multi-armed bandit to address the channel selection problem. Simulation results validate the proposed scheme.

Dynamic spectrum access with packet size adaptation and residual energy balancing for energy-constrained cognitive radio sensor networks

We demonstrate an improvement in energy efficiency and network lifetime for the cluster-based multi-channel cognitive radio sensor network (CRSN). The improvement roots from two techniques proposed in dynamic spectrum access. The first technique exploits packet size adaptation: varying the packet size to adapt the transmission over the state-varying channel. This is to efficiently utilize the battery of sensors by having the most appropriately sized packets successfully transmitted, in accordance with the instantaneous channel conditions. The second technique focuses on channel assignment with awareness of the residual energy of sensors, such that sensors can spend their energy in a balanced way. This helps to prolong the network lifetime, compared to the random channel pairing approach. As all those techniques rely on the estimates of channel states and their performance is tied with the estimation accuracy, we theoretically derive a polynomial-time resolvable expression for the maximum-likelihood (ML) estimator PMF function. In light of this expression, the impact of channel estimation accuracy on network performance is thereby illustrated.

Performance Analysis of Unslotted CSMA with Hybrid Sensing in Multi-Channel Cognitive Radio Network

We propose and analyze an unslotted CSMA with hybrid sensing in multi-channel cognitive radio network, which combines randomm-sensing and all sensing. We model the system by 3-demensional continuous time Markov process, calculate the steady state probability of the system, and obtain several performance measures such as throughput and forced termination probability of SUs. By comparing the performances of hybrid sensing, randomm-sensing and all sensing, the numerical results show that hybrid sensing scheme overcome the defect of low performance in randomm-sensing scheme.

Optimal Spectrum Access for Users in Multi-Channel Cognitive Radio Networks

Cognitive Radio, a software defined rad io, is an emerging technology which uses opportunistic spectrum access (OSA) for the efficient utilizat ion of the spectrum. Its main aim is to utilize the unused portions of the spectrum by allo wing unlicensed users (secondary users) to transmit data in absence of primary users. In this paper the assignment of mu ltip le primary and secondary users in a mult iple channel system is addressed with the sole aim of optimizing the total throughput. We have considered an optimal spectrum access (OSA) algorith m for the allot ment of both the primary and secondary users in a mult iple channel system and compared the results with the well-known meta-heuristic techniques such as Simulated Annealing (SA) and Tabu Search (TS). The results reveal that OSA algorithm is mo re efficient as compared to SA and TS as far as throughput optimization is considered.

Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks

In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions.

Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection

In this paper, we consider a multi-channel cognitive radio network (CRN) where each secondary user (SU) can only choose to sense a subset of channels. We formulate a joint optimization problem of sensing-channel selection, sensing time and power allocation under the constraints of average transmit power budget and average interference power budget, which maximizes the CRN’s total throughput. We propose a greedy algorithm to solve the joint optimization problem, which has much less computational complexity. Moreover, it is shown that the search space of the greedy algorithm can be further pruned. Finally, numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm.

On the Queue Dynamics of Multiuser Multichannel Cognitive Radio Networks

For protocol and system design in cognitive radio networks (CRNs), it is essential to identify which system settings or environmental conditions have great impacts on the quality-of-service (QoS) performance for secondary users (SUs) and how they influence it, which are still open issues. In this paper, an analytical framework to quantify the queue dynamics of a multi-SU multichannel CRN is developed. In the analytical framework, we consider the important lower-layer mechanisms and settings, including spectrum sensing errors, medium-access control (MAC) protocols, link adaptation technologies such as adaptive modulation and coding (AMC) and automatic repeat request (ARQ), and limited buffer size. By modeling the queue dynamics as a discrete-time finite-state Markov chain (FSMC), we derive the analytical expressions of the average queue length, packet-dropping rate, and packet-collision rate. Based on these expressions, the QoS metrics including average queueing delay, packet-loss rate, and effective throughput are obtained. Simulation and numerical results are presented to verify the accuracy of the proposed analytical framework and investigate the QoS performance of SUs.

Performance analysis of opportunistic spectrum access protocol for multi-channel cognitive radio networks

Cognitive radio (CR) has emerged as one of effective methods to enhance the utilization of existing radio spectrum. Main principle of CR is that secondary users (SUs) are allowed to use the spectrum unused by primary users (PUs) without interfering PU's transmissions. In this paper, PUs operate on a slot-by-slot basis and SUs try to exploit the slots unused by PUs. We propose OSA protocols in the single channel and we propose an opportunistic spectrum access (OSA) protocols in the multi-channel cognitive radio networks with one control channel and several licensed channels where a slot is divided into contention phase and transmission phase. A slot is divided into reporting phase, contention phase and transmission phase. The reporting phase plays a role of finding idle channels unused by PUs and the contention phase plays a role of selecting a SU who will send packets in the data transmission phase. One SU is selected by carrier sense multiple access / collision avoidance (CSMA/CA) with request to send / clear to send (RTS/CTS) mechanism on control channel and the SU is allowed to occupy all remaining part of all idle channels during the current slot. For mathematical analysis, first we deal with the single-channel case and we model the proposed OSA media access control (MAC) protocol by three-dimensional discrete time Markov chain (DTMC) whose one-step transition probability matrix has a special structure so as to apply the censored Markov chain method to obtain the steady state distribution. We obtain the throughput and the distribution of access delay. Next we deal with the multi-channel case and obtain the throughput and the distribution of access delay by using results of single-channel case. In numerical results, our mathematical analysis is verified by simulations and we give numerical results on throughput and access delay of the proposed MAC protocol. Finally, we find the maximum allowable number of SUs satisfying the requirements on throughput and access delay.

Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

This paper addresses power allocation problem for spectrum sharing multi-band cognitive radio networks, where the primary user (PU) allows secondary users (SUs) to transmit simultaneously with it by coding SU's signal together with its own signal. The PU acts as the relay for the SUs and sells its transmit power to the SUs to increase its benefit, and the SUs bid for the PU's transmit power for maximizing their utilities. We propose a power allocation scheme based on traditional ascending clock auction, in which the SUs iteratively submit the optimal power demand to the PU according to the PU's announced price, and the PU updates that price based on all SUs' total power demands. Then we mathematically prove the convergence property of the proposed auction algorithm (i.e., the auction algorithm converges in a finite number of clocks), and show that the proposed power auction algorithm can maximize the social welfare. Finally, the performance of the proposed scheme is verified by the simulation results.

Adaptive code symbol assignment in a rateless coded multichannel cognitive radio network

SUMMARYBecause of its robustness to packet loss and adaptivity to channel conditions, rateless codes have been used in cognitive radio networks to improve the secondary system performance. In this paper, we investigate an adaptive code symbol assignment scheme for the secondary user (SU) in a multichannel cognitive radio network based on rateless coding. In particular, the SU transmitter first encodes its information data through rateless coding and then assigns the unceasingly generated code symbols adaptively to each available channel obtained by spectrum sensing. Thanks to the forward incremental redundancy provided by rateless codes, it is unnecessary for the SU receiver to request the retransmission of lost symbols and the code symbols collected from any channel at any time contribute to the final data recovery. With an alternating channel occupancy model of the primary user (PU), we conduct a weight enumerator analysis to derive the optimal number of code symbols to be assigned to each available channel, thus to maximize the system throughput while protecting PU from interference. Both theoretical analysis and numerical results demonstrate the good performance of our proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.

Distributed execution of cognitive relaying with time incentive: multiple PU scenario

The prime focus of this study is in developing distributed algorithms for cognitive relaying with time incentive for multiple primary users (CRTI-M). CRTI-M is a symbiotic paradigm in which the incumbent primary users (PUs) of the spectrum, with weak transmission links, seek cooperation from the cognitive secondary user (SU) nodes in their vicinity, and in return reward them with an incentive time for the latter’s own communication. When relaying through the SU network, each PU can either use its own spectrum or that of the other PUs. Cross-layer optimization problems are formulated to enable both these possibilities in a multi-hop multi-channel cognitive radio network with the objective of maximizing the cumulative time incentive for the SUs. Corresponding distributed algorithms are developed, which face the challenge of meeting the constraints of the formulated problems with only local information and the lack of a centralized controller. Further, to make the CRTI-M schemes practically realizable, a MAC scheduling protocol is suggested, which gives emphasis to the distributed implementation and provides a unified framework for the PUs and SUs. Simulation results are furnished to demonstrate the effectiveness of the proposed algorithms.

Design and Analysis of Transmission Strategies in Channel-Hopping Cognitive Radio Networks

In recent years, channel-hopping-based medium access control protocols have been proposed to improve the capacity in a decentralized multichannel cognitive radio (CR) network without using extra control channels. Each CR user has to stochastically follow a default channel-hopping sequence in order to locate a channel and conduct its frame transmission. In this paper, theoretical analysis is conducted on the probability of channel availability and the average frame delay for primary users (PUs) by considering the impact caused by imperfect sensing of CR users and imperfect synchronization between the primary and CR networks. According to the proposed analytical model with realistic considerations, an optimal channel-hopping sequence (OCS) approach is designed for the CR users based on a dynamic programming technique. It is designed by exploiting the optimal load balance between channel availability and channel utilization within the delay constraints of PUs. By adopting the OCS approach, maximum aggregate throughput of CR users can be achieved while considering PU's quality-of-service (QoS) requirements. Moreover, in addition to the paired CR networks, the logical partition problem that occurs in generalized CR networks will also be addressed. This problem can severely degrade the aggregate throughput due to the decreased probability of connectivity between CR users, especially in a CR network with heavy traffic. Therefore, both wake-up successive contention (WSC) and wake-up counter-reset successive contention (WCSC) algorithms are proposed to increase the number of negotiations by both exploring the blind spot of imperfect sensing and amending the contention mechanisms between CR users. Compared to conventional channel-hopping sequences, numerical results illustrate that the proposed approaches can effectively maximize aggregate throughput for CR users under the QoS requirements of PUs.

Jointly optimizing sensing time and resource allocation in multichannel cognitive radio networks

SUMMARYSpectrum sensing is a key technique for determining the spectrum available in cognitive radio (CR) networks. In this paper, we study how to jointly optimize sensing time and resource allocation to maximize the sum transmission rate of all CR users of a multichannel CR network. We take into consideration the transmission power and interference constraints to protect primary users from harmful interference, as well as constraints of detection probability and false alarm probability. Under these constraints, we propose an asymptotically optimal resource allocation algorithm. The optimal sensing time can be obtained using the traditional one‐dimensional exhaustive search. However, owing to the high complexity of searching for the sensing time, we propose a simplified method to get the optimal sensing time under the assumption that false alarm probability is small. Simulation results show that the simplified method can obtain the optimal sensing time efficiently under strict constraint of false alarm probability. Copyright © 2012 John Wiley & Sons, Ltd.

Performance analysis of dynamic spectrum handoff scheme with variable bandwidth demand of secondary users for cognitive radio networks

Cognitive radio (CR) has attracted considerable attention as a promising technology for solving the current inefficient use of spectrum. In CR networks, available sub-channels are dynamically assigned to secondary users (SUs). However, when a primary user accesses a primary channel consisting of multiple sub-channels, data transmissions of the SUs already using the sub-channels may be terminated. In this paper, we analyze the performance of dynamic spectrum handoff scheme with channel bonding, in which the number of sub-channels used by an SU are variable. We model the multichannel CR network as a multiserver priority queueing system without waiting facility, deriving the blocking probability, the forced termination probability and the throughput for SUs. In terms of the way of forced termination, we consider two policies; one is that SUs using the largest number of sub-channels are forced to terminate their transmissions, and the other is that SUs using the smallest number of sub-channels are chosen for termination. The analysis is also validated by simulation. Numerical examples show that in both forced-termination policies, the throughput of SUs that are forced to terminate their transmissions degrades as the offered load to the system increases.