协同认知无线网络中自适应中继节点选择算法

最优停止规则算法的优点是避免主用户考察所有次用户,使主用户能在较短观测时间内挑选出满足通信服务质量的中继节点。但存在些许不足之处,如仅考虑了单次协同通信情况,没有充分利用历史中继节点选择信息。为了克服上述缺点,需要优化该算法的性能,通过引入反馈机制,提出了自适应中继节点选择算法,在每次中继节点选择结束后更新信息库中次用户中继概率,主用户从中继概率高的次用户开始观测。研究结果表明:自适应中继节点选择算法的效率要比最优停止规则算法高;该算法可进一步减少观测次数,降低系统的传输时延和观测能耗,提高主用户的平均吞吐率。     

Channel exploration for aggregation in cognitive radio system

In this paper we focus on channel exploration problem in the cognitive radio (CR) system, where the exploration process consumes time. The explored channels can be aggregated by CR user for its transmission. CR user adopts a synchronous slotted structure with primary users. Usually, the channel exploration problem is formulated as an optimal stopping problem. However, most previous related works are based on the assumption that channel state changes randomly across slots. In the system, channel state contains channel availability and link quality on the channel. When channel state’s transition across slots follows a Markov process, the problem becomes different. Then we introduce a two-dimension Partially Observable Markov Decision Process framework into the optimal stopping problem. We concentrate on the myopic rule of the new problem. By exploring the structure property of the myopic rule, we can achieve the optimal performance under the myopic rule with a lower computation complexity. To further reduce the computation complexity for a practical application, we then propose a greedy approach. The simulation results show CR user can obtain a near-optimal performance by the greedy approach. The validity of our proposed approaches is also verified by simulation.     

Optimal precoder design for non‐regenerative multiple‐input multiple‐output cognitive relay systems with perfect and imperfect channel state information

This paper studies optimal precoder design for non‐regenerative multiple‐input multiple‐output (MIMO) cognitive relay systems, where the secondary user (SU) and relay station (RS) share the same spectrum with the primary user (PU). We aim to maximize the system capacity subject to the transmit power constraints at the SU transmitter (SU‐Tx) and RS, and the interference power constraint at the PU. We jointly optimize precoders for the SU‐Tx and RS with perfect and imperfect channel state information (CSI) between the SU‐Tx/RS and PU, where our design approach is based on the alternate optimization method. With perfect CSI, we derive the optimal structures of the RS and SU‐Tx precoding matrices and develop the gradient projection algorithm to find numerical solution of the RS precoder. Under imperfect CSI, we derive equivalent conditions for the interference power constraints and convert the robust SU‐Tx precoder optimization into the form of semi‐definite programming. For the robust RS precoder optimization, we relax the interference power constraint related with the RS precoder to be convex by using an upper bound and apply the gradient projection algorithm to deal with it. Simulation results demonstrate the effectiveness of the proposed schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

To‐send‐or‐not‐to‐send: An optimal stopping approach to network coding in multi‐hop wireless networks

Network coding is all about combining a variety of packets and forwarding as much packets as possible in each transmission operation. The network coding technique improves the throughput efficiency of multi‐hop wireless networks by taking advantage of the broadcast nature of wireless channels. However, there are some scenarios where the coding cannot be exploited due to the stochastic nature of the packet arrival process in the network. In these cases, the coding node faces 2 critical choices: forwarding the packet towards the destination without coding, thereby sacrificing the advantage of network coding, or waiting for a while until a coding opportunity arises for the packets. Current research works have addressed this challenge for the case of a simple and restricted scheme called reverse carpooling where it is assumed that 2 flows with opposite directions arrive at the coding node. In this paper, the issue is explored in a general sense based on the COPE architecture requiring no assumption about flows in multi‐hop wireless networks. In particular, we address this sequential decision making problem by using the solid framework of optimal stopping theory and derive the optimal stopping rule for the coding node to choose the optimal action to take, ie, to wait for more coding opportunity or to stop immediately (and send packet). Our simulation results validate the effectiveness of the derived optimal stopping rule and show that the proposed scheme outperforms existing methods in terms of network throughput and energy consumption.     

A joint sensing and transmission power control policy for RF energy harvesting cognitive radio networks

We consider a radio frequency energy harvesting cognitive radio network in which a secondary user (SU) can opportunistically access channel to transmit packets or harvest radio frequency energy when the channel is idle or occupied by a primary user. The channel occupancy state and the channel fading state are both modeled as finite state Markov chains. At the beginning of each time slot, the SU should determine whether to harvest energy for future use or sense the primary channel to acquire the current channel occupancy state. It then needs to select an appropriate transmission power to execute the packet transmission or harvest energy if the channel is detected to be idle or busy, respectively. This sequential decision‐making, done to maximize the SU's expected throughput, requires to design a joint spectrum sensing and transmission power control policy based on the amount of stored energy, the retransmission index, and the belief on the channel state. We formulate this as a partially observable Markov decision process and use a computationally tractable point‐based value iteration algorithm. Section 5 illustrate the significant outperformance of the proposed optimal policy compared with the optimal fixed‐power policy and the greedy fixed‐power policy.     

Interference‐aware spectrum handover for cognitive radio networks

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

Robust beamforming in cognitive radio

This letter considers the multi-antenna cognitive radio (CR) network, which has a single secondary user (SU) and coexists with a primary network of multiple users. Our objective is to maximize the service probability of the SU, subject to the interference constraints on the primary users (PUs) in the form of probability. Exploiting imperfect channel state information (CSI), with its error modeled by added Gaussian noise, we address the optimization for the beamforming weights at the secondary transmitter. In particular, this letter devises an iterative algorithm that can efficiently obtain the robust optimal beamforming solution. For the case with one PU, we show that a much simpler algorithm based on a closed-form solution for the antenna weights of a given power can be presented. Numerical results reveal that the optimal solution for the constructed problem provides an effective means to tradeoff the performance between the PUs and the SU, bridging the non-robust and worstcase based systems.     

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.     

Ergodic capacity and outage probability optimization for secondary user in cognitive radio networks under interference outage constraint

This paper considers a cognitive radio network where a secondary user (SU) coexists with a primary user (PU). The interference outage constraint is applied to protect the primary transmission. The power allocation problem to jointly maximize the ergodic capacity and minimize the outage probability of the SU, subject to the average transmit power constraint and the interference outage constraint, is studied. Suppose that the perfect knowledge of the instantaneous channel state information (CSI) of the interference link between the SU transmitter and the PU receiver is available at the SU, the optimal power allocation strategy is then proposed. Additionally, to manage more practical situations, we further assume only the interference link channel distribution is known and derive the corresponding optimal power allocation strategy. Extensive simulation results are given to verify the effectiveness of the proposed strategies. It is shown that the proposed strategies achieve high ergodic capacity and low outage probability simultaneously, whereas optimizing the ergodic capacity (or outage probability) only leads to much higher outage probability (or lower ergodic capacity). It is also shown that the SU performance is not degraded due to partial knowledge of the interference link CSI if tight transmit power constraint is applied.     

Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks

In this paper, we revisit the problem of fusing decisions transmitted over fading channels in a wireless sensor network. Previous development relies on instantaneous channel state information (CSI). However, acquiring channel information may be too costly for resource constrained sensor networks. In this paper, we propose a new likelihood ratio (LR)-based fusion rule which requires only the knowledge of channel statistics instead of instantaneous CSI. Based on the assumption that all the sensors have the same detection performance and the same channel signal-to-noise ratio (SNR), we show that when the channel SNR is low, this fusion rule reduces to a statistic in the form of an equal gain combiner (EGC), which explains why EGC is a very good choice with low or medium SNR; at high-channel SNR, it is equivalent to the Chair-Varshney fusion rule. Performance evaluation shows that the new fusion rule exhibits only slight performance degradation compared with the optimal LR-based fusion rule using instantaneous CSI.     

Robust energy efficiency power allocation for relay-assisted uplink cognitive radio networks

In this paper, we investigate a worst-case robust power allocation scheme to improve energy efficiency (EE) for an amply-and-forward relaying uplink underlay OFDM cognitive radio system with imperfect channel situation information about the channel between primary user (PU) and secondary user (SU) and the channel between SU and corresponding relay. Specifically, a max–min problem is formulated to transform the original optimization problem into maximum EE on minimum throughout channel, and an epigraph problem is introduced to obtain analytical expressions of objective power allocation. Simulation results show that the proposed EE power allocation scheme is valid and effective in EE and robustness.     

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

An efficient and adaptive channel handover procedure for cognitive radio networks

In designing cognitive radio systems, one of the most critical issues is handling the channel handover process (CHP). The CHP consists of spectrum sensing, spectrum decision, negotiation on the common control channel, and adjustment of frequency and modulation settings, and such, it can be a time‐consuming process. Consequently, initiating the CHP after each detected user activity (UA) can decrease the aggregate spectrum utilization. To alleviate this problem, we introduce a novel handover strategy to find the optimal trade‐off between the durations of the CHP and UAs. With the use this model, secondary users (SUs) track only local information on their current data channel to make the decision to initiate the CHP or to wait for the termination of the ongoing UA. The system adapts to the dynamic conditions of the data channels and reduces the frequency of handovers to increase throughput and decrease access delay. We give analytical utilization bounds for SUs and also compare the performance of our model to those of other channel handover strategies by using extensive simulations. Our results for channels with heterogeneous loads and dynamic environments show that this model can clearly decrease the frequency of handover and consequently increase the aggregate SU utilization. Copyright © 2013 John Wiley & Sons, Ltd.     

Determination of the multi‐slot transmission in Bluetooth systems with the estimation of the channel error probability

Bluetooth is an open specification for a technology to enable short‐range wireless communications that operate in an ad hoc fashion. Bluetooth uses frequency hopping with a slot length of 625 μs. Each slot corresponds to a packet and multi‐slot packets of three or five slots can be transmitted to enhance the transmission efficiency. However, the use of multi‐slot packet may degrade the transmission performance under high channel error probability. Thus, the length of multi‐slot should be adjusted according to the current channel condition. Segmentation and reassembly (SAR) operation of Bluetooth enables the adjustment of the length of multi‐slot. In this paper, we propose an efficient multi‐slot transmission scheme that adaptively determines the optimal length of slots of a packet according to the channel error probability. We first discuss the throughput of a Bluetooth connection as a function of the length of a multi‐slot and the channel error probability. A decision criteria which gives the optimal length of the multi‐slot is presented under the assumption that the channel error probability is known. For the implementation in the real Bluetooth system, the channel error probability is estimated with the maximum likelihood estimator (MLE). A simple decision rule for the optimal multi‐slot length is developed to maximize the throughput. Simulation experiment shows that the proposed decision rule for the multi‐slot transmission effectively provides the maximum throughput under any type of channel error correlation. Copyright © 2005 John Wiley & Sons, Ltd.     

Outage performance of cognitive AF relay networks with direct link and heterogeneous non‐identical constraints

Although there have been many interesting works on outage performance analysis of cognitive AF relay networks, we have not found works taking into consideration all the following issues: multiple primary users (PUs), the existence of the direct link from secondary user (SU) source to SU destination, non‐identical, independent Rayleigh‐fading channels, non‐identical interference power limits of PUs, and non‐identical noise powers in signals. Additionally, in outage performance analysis for such networks, the correlation issue, which results from the channel gain of interference links from the SU nodes to the PU, requires elaborate treatments. Hence, analyzing outage performance of non‐identical‐parameter networks (where all channels are fully non‐identical Rayleigh‐fading channels, the PUs have different interference power limits, and received signals have different noise powers) from the beginning is highly complicated. To overcome this problem, we conduct the analysis in two steps. In the first step, expressions of both exact and asymptotic outage probability of identical‐parameter cognitive AF relay networks (where all channels are fully non‐identical Rayleigh‐fading channels but all other parameters are identical) are obtained. Then in the second step, we propose a method for transforming a network with all non‐identical parameters into a new identical‐parameter network, meanwhile guaranteeing that outage performance of the two networks before and after the transformation are the same. Hence, OP of the original non‐identical‐parameter network can be obtained indirectly by using the analysis results obtained in the first step. Our analysis results are validated through numerical simulations. The effects of the number of PUs and the diversity level of channel parameters (which means the range of the channel parameter values) are also inspected by simulations. The results show that taking these factors into consideration is of key importance in obtaining a more accurate estimation of outage performance of such networks. Copyright © 2014 John Wiley & Sons, Ltd.     

Channel assignment scheme in clustered multichannel cognitive radio networks with outdated CSI over Rayleigh fading channels

This work investigates channel assignment for cooperative spectrum sensing in multichannel cognitive radio networks, where the heterogeneity of primary user (PU) activity and the effect of varying channel condition on the received signal‐to‐noise ratio during cluster formation are considered. With the objective to minimize interference to the PU while enhancing multiple spectrum utilization of the secondary user (SU), an overlapping cluster‐based assignment is formulated into a nonlinear integer optimization problem. To obtain an efficient solution, the nonlinear integer problem is transformed into a mixed integer linear problem, based on which, this paper proposes an exact solution and then two new heuristic algorithms for suboptimal solutions, respectively. Furthermore, a comparative study of four different cluster head selection schemes with respect to their performance in cooperative spectrum sensing, under cluster's heterogeneity in terms of SUs distribution relative to PU transmitter location is presented. Based on the study, a robust cluster head selection scheme is proposed. Simulation results show that good sensing performance and increased opportunistic spectrum utilization in multichannel cognitive radio networks are two sides of a coin that depend on the ratio of the SUs to the number of PU channels. How far away the PU is from the cluster center is also seen to be key in the optimal selection of cluster heads in cooperative spectrum sensing.     

Efficient Spectrum Sensing with Minimum Transmission Delay in Cognitive Radio Networks

In cognitive radio (CR) networks, the secondary users (SUs) need to find idle channels via spectrum sensing for their transmission. In this paper, we study the problem of designing the sensing time to minimize the SU transmission delay under the condition of sufficient protection to primary users (PUs). Energy detection sensing scheme is used to prove that the formulated problem indeed has one optimal sensing time which yields the minimum SU transmission delay. Then, we propose a novel cooperative spectrum sensing (CSS) framework, in which one SU’s reporting time can be used for other SUs’ sensing. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, it is proved that there exists one optimal sensing time that minimizes the SU transmission delay. Under hard information fusion, for time varying channels, the novel multi-slot CSS is derived. The performance of SU transmission delay is studied in both perfect and imperfect reporting channels. Some simple algorithms are derived to calculate the optimal sensing settings that minimize the SU transmission delay. Computer simulations show that fundamental improvement of delay performance can be obtained by the optimal sensing settings. In addition, the novel multi-slot CSS scheme shows a much lower transmission delay than CSS based on general frame structure.     

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

Because 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.     

Power and Time Allocation Between Multiple Channels in Cognitive Radio Networks

In this paper, we consider a wideband cognitive radio network (CRN) containing a single secondary user (SU) which can only serially sense multiple narrowband channels and thus maximize the utilization of perceived available channels. Before transmitting, during a period of time τ, SU allocates τ _i to each channel and senses whether the channel is available or not. When transmitting, SU allocates different transmit power P _i to each channel. We study the problem of designing the optimal spectrum sensing time allocation τ _i , total sensing time τ and power allocation P _i between the multiple channels so as to maximize the achievable rate of CRN subject to the constraint of the total transmit power and probability of detection. The problem is transformed into some subproblems with low complexity and solved by optimal means separately. From the time and power allocation parameters, we conclude that channels with low probability of transmission chance or low channel gain will be closed without sensing or transmission in order to get the maximum rate. We also analyze how the conclusions can be applied to the scenario of multiple SUs. Numerical investigation shows that the proposed scheme can significantly achieve spectrum access and the optimization process improves the rate obtained by CRN.     

Meta‐heuristic algorithms for channel scheduling problem in wireless sensor networks

The channel scheduling problem is to decide how to commit channels for transmitting data between nodes in wireless networks. This problem is one of the most important problems in wireless sensor networks. In this problem, we aim to obtain a near‐optimal solution with the minimal energy consumption within a reasonable time. As the number of nodes increases in the network, however, the amount of calculation for finding the solution would be too high. It can be difficult to obtain an optimal solution in a reasonable execution time because this problem is NP‐hard. Therefore, most of the recent studies for such problems seem to focus on heuristic algorithms. In this paper, we propose efficient channel scheduling algorithms to obtain a near‐optimal solution on the basis of three meta‐heuristic algorithms; the genetic algorithm, the Tabu search, and the simulated annealing. In order to make a search more efficient, we propose some neighborhood generating methods for the proposed algorithms. We evaluate the performance of the proposed algorithms through some experiments in terms of energy consumption and algorithm execution time. The experimental results show that the proposed algorithms are efficient for solving the channel scheduling problem in wireless sensor networks. Copyright © 2011 John Wiley & Sons, Ltd.