Optimal energy-efficiency capacity and sensing tradeoff for hybrid spectrum sharing in CRN

This paper investigates the tradeoff between energy-efficiency capacity and spectrum sensing under hybrid spectrum sharing model,where the spectrum sharing method is based on sensing results of seconda...     

Capacity in fading environment based on soft sensing information under spectrum sharing constraints

In this paper, the ergodic channel capacity for a secondary user is investigated using soft sensing information about primary user activity in a shared channel under joint peak transmit power and average received interference power constraints for Nakagami-m fading channel. The results of the proposed power adaptation scheme illustrate the effect of communication environment parameters and soft sensing information about primary user activity on the channel capacity of secondary user. In particular, the effect of cross link channel state information to maximize the channel capacity for the power adaptation scheme is emphasized by considering the Lagrangian optimization problem for joint peak transmit power and average interference power constraints. Moreover, the performance of the primary user is also investigated considering the interference of the secondary user to the primary in spectrum sharing environment in terms of transmission rate and average channel capacity.     

Investigation on outage capacity of spectrum sharing system using CSI and SSI under received power constraints

In this paper, we have investigated the outage capacity of secondary user for opportunistic spectrum sharing under the joint peak and average received power constraints for Rayleigh fading environment. Under this communication scenario, on detecting the licensed primary user inactive, the secondary unlicensed users transmit data/information in the licensed frequency band such that no or minimum interference may be experienced by the primary user. The soft sensing information (SSI) and secondary user’s channel state information is used to obtain the closed form expressions for the ergodic and outage capacity using truncated channel inversion with fixed rate technique under the joint peak and average received power constraints. Numerically simulated results are provided to demonstrate the improvement in outage capacity of secondary user under the proposed spectrum sharing scheme. Moreover, the proposed scheme is also compared with other conventional spectrum sharing schemes to illustrate the benefits of SSI and received power constraints on the outage capacity of secondary user.

     

OFDMA认知无线电网络中面向需求的频谱共享

从满足次网络通信需求的角度,设计一个两阶段模型,求解OFDMA 认知无线电网络中频谱租赁与分配问题。模型第1阶段,次基站收集次网络通信需求,向多个主基站租用频谱资源。运用Bertrand博弈对主、次基站的交易行为进行建模,并将纳什均衡作为最终定价方案。第2阶段,基于纳什议价方案,将次基站子载波和功率分配问题定义成非线性规划问题,并通过拉格朗日乘数法进行求解。仿真实验表明,相对于其他频谱共享方案,所提方案高效地满足每个次用户的通信需求。     

Multi-channel transmission strategy for dynamic spectrum access

Cognitive radio is a promising technology that deals with the scarcity of radio spectrum. In this paper, we propose a new multi-channel transmission strategy for dynamic spectrum access in cognitive radio network. Starting with the model of spectrum activities, we present the multi-channel transmission strategy which has primary user’s protection mechanism to improve the spectrum efficiency and study its performance under perfect and imperfect sensing. Numerical example results reveal that the performance of the proposed strategy has the superiority with respect to capacity performance of cognitive users and the protection of primary users.     

基于空间位置的混合频谱共享系统功率分配研究简

针对次用户空间位置分布的随机性,提出空域混合Overlay/Underlay频谱共享模型以提高无线频谱利用率。根据次用户在不同空间位置对主用户的干扰,在主用户干扰容限约束下推导出次用户工作于Overlay状态和Underlay状态的空间区域;以最大化系统容量为准则建立认知系统功率优化分配模型,推导出次用户的最优功率分配方案,进而得到认知系统可获得的最大容量;理论和仿真结果表明,基于空间位置的混合频谱共享系统可以获得比Overlay系统更高的容量。     

Interference‐resilient spectrum sharing with collision detection and data recovery for cognitive radio networks

Data recovery under collision of primary/secondary users in cognitive radio networks is largely an unaddressed problem. Existing approaches require either (a) retransmissions, (b) interference‐free alignment of transmission parameters, or (c) prior knowledge for data recovery. In contrast to the existing approaches, the paper proposes estimation of channel state information based on received collided frames and recommends techniques for spectrum sharing, collision detection, and data recovery. Specifically, based on estimated channel vector, interference‐resilient spectrum‐sharing protocol and techniques are proposed for (a) identification of primary user (PU) activity before (or during) secondary user's (SU's) transmission, (b) MIMO channel estimation under collision, (c) optimal pilot permutation, and (d) interference cancellation (with/without receiver diversity). Results are reported for different baseband modulation techniques under frequency selective/flat fading channel scenarios that demonstrate the efficacy of a proposed work.     

Rate and Power Optimization Under Received-Power Constraints for Opportunistic Spectrum-Sharing Communication

In this paper, the channel capacity of secondary user is investigated for opportunistic spectrum sharing with primary user in a Rayleigh fading environment. In the proposed communication scenario, on finding transmission opportunities in licensed band, secondary user utilizes the band as long as the interference power inflicted on primary receiver is below the predefined threshold, and adjusts its transmission power and data rate based on the sensing information available from spectrum sensor. In this context, two different adaptation schemes namely adaptive transmission power scheme and adaptive rate and transmission power scheme are investigated under joint peak and average received power constraints at primary receiver for multilevel quadrature amplitude modulation format. The closed form expressions are derived for the ergodic channel capacities of these schemes and numerical results are presented to validate the theoretical results. Moreover, a comparison between channel capacities is given to illustrate the benefit of using soft sensing information under said constraints.

     

基于寡头定价的动态频谱接入控制

为了解决频谱接入中主用户和次级用户交互信息过程复杂的问题,提出了一种基于寡头定价的动态频谱接入控制算法。该算法利用博弈论建立寡头定价模型,通过控制次级用户的频谱接入过程以实现系统收益的最大化,算法只需一次用户信息交互,且无需建立公共控制信道,网络拓扑结构简单。通过比较帕累托最优与全局最优的关系,实验计算与性能分析证明了该算法的有效性。     

Analysis of secondary throughput and optimization in cooperative spectrum sensing

In cooperative spectrum sensing,more secondary user makes more opportunity for detecting the vacant spectrums,which resulting the spectrum utilization improved,however much bandwidth would be occupied for sending the local observation results,inducing the reduced secondary throughput.In this paper,an adaptive algorithm for selecting detection threshold was proposed,where the maximized secondary throughput can always be achieved while assuring sufficient protection to primary user,regardless of the number of...     

Maximized achievable rate of SINR‐measurement‐based spectrum sharing with binary feedback

Motivated by the difficulty in measuring channel state information between heterogeneous primary and secondary systems, we propose a signal‐to‐interference‐noise ratio (SINR)‐based spectrum sharing policy. In the proposed spectrum sharing policy, a secondary user who does not cause SINR outage at the primary receiver is admitted to share the primary user's spectrum. In this article, we analyze the achievable rate of a secondary user and for whom the achievable rate is maximized in the SINR‐constrained spectrum sharing. The maximized achievable rate is determined by the ratio of the distance between the secondary transmitter and the primary receiver to the distance between the secondary transmitter and receiver, and it is proportional to the distance ratio. In conclusion, secondary links with large distance ratio can support high data rate applications so long as SINR constraint of the primary user is guaranteed. Copyright © 2011 John Wiley & Sons, Ltd.     

Optimized channel prediction and auction-based channel allocation for personal cognitive networks

Cognitive networks are stands out as intelligent technology which evolved to enhance spectrum utilization. Secondary users are allowed to utilize the primary user's frequency bands on idling times. Identifying the idle licensed spectrum is achieved through spectrum sensing. The spectrum holes should be explored such that a suitable spectrum can be selected and allocated to the secondary users. Existing spectrum sensing and selection schemes have limitations due to interferences. Thus, an optimization algorithm based on bio-inspired improved weed optimization was presented in this research work for enhanced channel utilization. The optimization model explores the channel characteristics and reduces the primary network interferences through its optimal solution. Further, Markov greedy-based auction scheme was presented for channel allocation. Considering the channel capacity, delay, and switching rates the allocation is performed to enhance the overall system performance. Simulation analysis demonstrates the superior performance of the proposed model over existing techniques like particle swarm optimization and genetic algorithm.     

改进粒子群算法在频谱功率分配中的应用

在认知无线电中,由于次用户干扰门限要求的存在,传统频谱功率分配方式获得的次用户有效信道容量较低。针对这一问题,提出了一种基于粒子群算法的频谱功率分配算法。首先建立基于干扰距离的认知网络干扰模型,将频谱功率分配问题转化为函数优化问题,并借助混合随机变异思想的粒子群算法进行求解;针对寻优过程中的约束问题,提出了一种基于投入产出比的外点法,保证粒子群在可行域中寻优,最终获得频谱功率分配。仿真结果表明,与传统算法相比,所提算法能够获得较高的次用户有效信道容量。     

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.     

基于合约制的认知网络协作频谱共享模型

为了提高认知无线电网络中主用户的能效和谱效,提出了一种基于合约制的协作频谱共享新模型。在该模型中,当主用户信道质量差时,次用户为其提供中继服务;作为回报,在主用户信道质量好时,次用户可以在一定的干扰约束下以underlay的模式和主用户共享频谱。在此框架下引入经济学中的合约理论,将主次用户间的协作问题建模为合约设计问题,并建立了主次用户评价合约收益的效用函数,将提高主用户的能效和谱效问题转变为设计合约使主用户获得最大效用的优化问题,并利用差分进化算法对该问题求解。最后,在不同的环境下,将主用户协作与不协作获得的效用进行对比,结果表明,主用户在没有额外投入频谱资源的条件下,不仅节省了发送功率,而且有效地提高了数据传输速率,进而提高了能效和谱效。     

Joint cooperative spectrum sensing and channel selection optimization for satellite communication systems based on cognitive radio

Cognitive radio has attracted considerable attention because of its ability to make full use of the available spectrum resources for wireless terrestrial communication networks. In addition, the satellite communication scenario, which requires a transparent air interface to integrated/hybrid Satellite–Terrestrial communication systems and provides a supplement for other multimedia services, will cause frequency scarcity. Satellite communication systems based on cognitive radio are available under scenarios that involve transmission with changing communications. In this paper, a cooperative spectrum‐sensing algorithm based on a time or bandwidth‐based cooperative spectrum‐sensing model of an integrated/hybrid cooperative satellite communication system is proposed. Moreover, the concept of weighted cooperative spectrum sensing is introduced. Compared with the traditional single‐user spectrum‐sensing algorithm, the cooperative spectrum sensing is able to cope with the interference to the primary user caused by a secondary user better. In addition, multiple earth stations that use some part of the bandwidth cooperatively to perform spectrum sensing throughout the whole frame can detect the presence of primary user in time. The satellite component combines the sensing results from earth stations to reach a final decision, and the optimal combination weights to maximize the detection probability of the secondary user are obtained. Numerical results that demonstrate the performance of the proposed algorithm are presented. Copyright © 2015 John Wiley & Sons, Ltd.     

Power allocation in cognitive radio networks with cooperative spectrum sensing

This paper studies power allocation among cooperative nodes (CNs) and secondary user (SU) under the assumption that only mean channel gains are available. We aim to find the power allocation that maximizes the SU average throughput under the constraints of the total power and individual transmission power for CN. We also consider the requirement on cooperative spectrum sensing with target miss-detection probability. Due to the high computational complexity of the optimal solution, we derive a near-optimal solution with low complexity while satisfying the requirements on transmission power and miss-detection probability. Moreover, the closed-form expression of approximation of power ratio is presented. Finally, numerical results verify our analysis and show that the proposed scheme achieves significant performance gain over others, and closes to the optimal solution.     

基于传输中断概率的认知无线电系统性能分析

如何设计最优的频谱感知与传输框架是认知无线电技术的重要环节。考虑频谱接入过程中数据传输中断对认知网络性能影响的问题,提出了一种新的基于传输中断概率的频谱感知与传输模型,联合优化频谱感知和数据传输两个阶段,将问题建模为对主用户的干扰量约束条件下的非凸优问题,以最大化认知网络吞吐量为目标联合优化感知时间、传输速率,并通过数值计算方法对其进行求解与仿真。数值分析表明,引入传输中断概率后,在满足上述约束条件的同时,在保护主用户和认知网络吞吐量、传输时延之间有了更好的权衡。     

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.