基于中断概率的协作通信中继选择与功率分配算法

研究了功率受限情况下多中继协作通信网络的中继选择和功率优化问题。在AF网络中,提出了一种低复杂度中继选择与功率分配算法,其目标是在总功率一定的条件下使系统的中断概率最小。本算法对源节点和所有潜在中继节点进行功率分配,结合当前信噪比选择最优的中继集合,通过最速下降法求出使系统中断概率最低的功率分配因子。该算法不需要知道大量瞬时信道信息、不需要系统在等功率条件下进行中继选择,只需求得中继节点排列矩阵便可根据当前信噪比自适应获得最优中继节点集合。仿真结果表明,在相同条件下,该算法明显优于不同中继节点集合下几种算法的中断性能,并且与传统的SAF及AAF算法相比,有效降低了中断概率,提升了系统性能和功率效率。     

基于萤火虫算法的多中继功率分配

为了充分实现中继协作,降低多中继协作通信系统功率分配优化问题的计算复杂度,提出了基于萤火虫算法的多中继功率分配方案。在一定的总功率和节点功率约束下,以最大化平均信噪比为优化目标函数,建立了多中继协作系统的功率分配最优化模型。选取该目标函数作为萤火虫的适应度函数,用向量表示萤火虫的状态,该向量的维数为待分配源节点和中继节点的个数,通过萤火虫聚集得到种群中最好的萤火虫,即可获得渐进最优功率分配。仿真结果表明,与平均功率分配相比,基于萤火虫算法的功率分配方案能降低2.44%~6.17%的比特差错率,提高了系统性能。     

Residual energy based multi-relay selection and power allocation scheme in two-way relay network

In this paper, we have proposed a multi-relay selection and power allocation scheme for two-way relay network which aims to maximize the sum-rate of two-way relay system. First, to prolong network lifetime, a multi-relay selection strategy is proposed in which both channel state information （CSI） and remaining energy （RE） are considered. Next, a multi-relay power allocation algorithm based on convex optimization （MRPA-CO） is presented. To reduce the computational complexity, it can be divided into two steps： terminal nodes power allocation （TNPA） and relay nodes power allocation （RNPA）. Simulation results indicate that the proposed relay selection strategy can significantly prolong network lifetime compared to other relay selection strategies which consider CSI only, and the MRPA-CO algorithm has great advantage over equal power allocation （EPA） on sum-rate in two-way relay network.     

Joint power allocation and multi-relay selection scheme based on system outage probability

An amplify-and-forward （AF） based multi-relay network is studied. In order to minimize the system outage probability with a required transmission rate, a joint power allocation （PA） and multi-relay selection scheme is proposed under both total and individual power constraints （TIPC）. In the proposed scheme, the idea of ordering is adopted to avoid exhaustive search without losing much system performance. Besides the channel quantity, the ordering algorithm proposed in this article also takes relays＇ maximal output ability into consideration, which is usually ignored in traditional relay ordering algorithms. In addition, simple power reallocation method is provided to avoid repetitive PA operation during the process of searching all possible relay subsets. By Adopting the idea of ordering and using the proposed power reallocation method lead to remarkable decrease of the computation complexity, making the scheme easier and more feasible to implement in practical communication scenarios. Simulations show that the proposed multi-relay selection scheme provides similar performance compared to the optimal scheme with optimal PA and exhaustive search （OPAES） but with much lower complexity.     

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution(NBS-DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access(OFDMA) system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game(SPABG) to maximize the system utility,under the constraints of each user’s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.     

协作D2D异构网络的联合资源分配和功率控制

针对下行协作D2D(Device-to-Device)异构网络中复用蜂窝用户的联合资源分配和功率控制问题,提出了一种量子珊瑚礁优化算法(Quantum Coral Reef Optimization Algorithm,QCROA).首先,构建异构网络模型并推导得到整个网络总吞吐量的数学表达式;其次,基于QCROA算法...     

OFDMA协同通信系统子载波和功率联合分配算法

针对OFDMA协同通信系统资源分配仅考虑平均功率下的子载波分配,中继存在未用功率情况,研究子载波分配后中继剩余功率分配问题。提出一种既满足业务QoS需求又兼顾用户间公平性的子载波和功率联合分配算法,并设计一种基于二分法的功率注水分配方案。测试表明,该算法能在满足业务QoS需求及用户公平性的同时,提升系统容量。     

协作通信系统的功率分配策略研究

在无线通信中,为了对抗信道衰落,人们提出了分集技术。协作分集通过共享资源达到改善通信质量、提高通信性能的目的。研究了放大转发协作通信系统中的功率分配策略。对于协作通信系统的功率分配研究了3种方法:迭代法,直接计算法,理想的穷搜索法。研究表明,迭代法是最佳方案,因为这种方法的迭代次数可以人为控制,而且性能与理想的穷搜索法相差不大。     

最小功耗的中继选择与功率分配的联合优化

研究采用放大转发协议的单向和双向中继网络中的中继选择与功率分配的联合优化策略。该策略以一定服务质量(QoS)要求为约束条件,以最小化中继网络中各节点的总功率为目标,建立优化问题。运用凸优化技术,得到了该优化问题的闭合解。仿真结果表明在满足相同的QoS要求下,该最优联合策略较传统的随机选择与等功率分配策略具有较低的功率消耗。     

放大转发OFDM协同中继系统多业务资源分配机制

提出了点到点多载波协同中继系统多业务资源分配框架,并给出了一种最优化自适应功率、载波和比特分配算法;为了降低算法复杂度,又提出了一种次优搜索算法,该算法依据信道特性,在满足业务QoS基础上使业务占用资源最小.仿真结果表明:提出的最优算法在保障多媒体业务QoS的基础上能够有效改善频谱效率,对比于传统算法有1～2bit/(s·Hz)的性能提升;而提出的次优搜索能够取得接近最优算法的性能(差别在0.6 bit/(s·Hz)左右),并且实现复杂度由指数级别降至线性.     

分布式双向中继选择算法及用户功率分配

针对放大转发的瑞利双向中继信道的节点选择问题,提出了基于部分信道信息的分布式双向中继选择算法。算法通过计算双向链路的接收信噪比,推导出满足目标接收信噪比的转发阈值,各中继节点根据该阈值决定是否参与转发,从而实现分布式选择。此外,考虑用户总功率受限的情况,在分布式中继选择基础上提出了优化功率分配策略,使双向信道的接收信噪比更加接近。仿真结果表明,分布式中继选择算法与最优多中继算法的系统传输速率相似,计算复杂度大大降低,尤其是在中继数目增大的情况下更加明显。优化功率分配策略能进一步提高系统能量效率,在相同性能下可节省7%左右的功率。     

Energy efficiency based multi-relay selection and power allocation in OFDM cooperation networks

Getting along with the improvement of green communications, the energy efficiency （EE） of wireless network becomes more and more important. However, in nmlti-relay-assisted systems, the related work obviously depends on the end-to-end performance, whereas EE of relays has not attracted enough attention. The authors propose an orthogonal frequency division multiplexing （OFDM） multi-relay system based on amplify and forward （AF） mode. Taking incorporating EE and remaining energy as factor, decision criteria of attending cooperation is designed. The EE based asynchronous power iteration method is presented, and the existence and convergence of nash equilibrium （NE） is proven. Furthermore, a joint algorithm in subcarrier pairing, relay selection and power allocation is given. Genetic algorithm （GA） and iteration method are integrated to improve the convergence speed additionally. Simulation demonstrates the obvious improvement of EE, decrease of power consumption and increase of lifetime in relays of this algorithm with the constraint of minimum data transmission rate.     

Bandwidth allocation and distributed relay selection for multiple‐user and multiple‐relay cooperative systems using Stackelberg game

Cooperative communication is an ongoing research area which lies on the basic idea of transmission of information from the transmitter to the receiver with the assistance of a virtual array of relay nodes in between, which will eventually provide the spatial diversity. This paper deals with the resource allocation (bandwidth in this case) among multiple users (source‐ destination pairs) in a cooperative communication environment along with the relay selection when there are multiple relay nodes to assist the transmitting nodes to pass on their data signal to respective receivers. A multi‐user, multi‐relay system model is considered here on which Amplify‐and‐Forward relaying scheme is applied. The bandwidth allocation and relay selection are done based on the Stackelberg game according to which transmitting nodes are treated as purchasers and relaying nodes are treated as vendors. By this planned approach, the transmitting nodes can discover the relays at comparatively better positions and can purchase the optimal bandwidth from those helping relays. By this approach, the relays which are competing with each other can increase their own utilities by demanding the optimal prices and the multiple users which are competing with each other can maximize their own utilities by demanding the optimal bandwidths. Distributed relay selection scheme is applied here which does not require precise information of channel state information as opposed to Centralized scheme and it gives comparable results, too.     

基于资源分配和功率控制的D2D中继选择

为优化蜂窝用户通信与设备直传(D2D)中继通信共存下的同频干扰问题,满足蜂窝用户容量要求,提出了一种基于能效的联合资源分配和功率控制的D2 D中继选择算法.该算法首先对等效D2 D中继链路进行资源分配,减小算法复杂度的同时使得D2 D链路对蜂窝链路产生的干扰最小;然后以资源分配结果和功率控制算法为依据进行中继选择.该方案不仅考虑了D2 D中继链路的能效问题,而且还同时考虑到了对蜂窝链路的干扰问题.通过仿真验证,所提算法不仅能有效提升D2 D中继链路的能效值,同时降低了对蜂窝用户的干扰.     

能量收集双向中继网络的中继选择和功率分配

结合能量收集技术,研究了放大转发双向中继网络的系统性能。基于双向中继系统中的两个端到端信噪比平衡准则,推导出了单中继选择情况下信源最优的功率分配方案和中继最优的能量收集比例。仿真结果证明所提方法能够实现最好的系统性能。通过比较发现,能量收集双向中继网络比传统双向中继网络能够实现更高的传输速率。     

协同分集中的中继选择方法

协同分集是一种新颖的分集技术。在协同通信中合理地选择中继能给系统带来更大的增益。在介绍协同分集原理和模型的基础上，引出了基于协作区域与基于及时信道状况和计时策略的两种中继选择方法，并对这两种方法进行了分析和比较。     

Research on the low complexity adaptive power allocation algorithm in cooperative systems

Cooperative diversity is a new technology to improve bit error rate(BER)performance in wireless communications.A new power allocation algorithm to improve BER performance in cellular uplink has been proposed in this paper.Some existing power allocation schemes were proposed for the purpose of maximizing the channel capacity or minimizing the outage probability.Different from these schemes,the proposed algorithm aims at minimizing the BER of the systems under the constraint of total transmission power.Besides this characteristic,the proposed algorithm can realize a low complexity real-time power allocation according to the fluctuation of channels.Simulation results show that the proposed algorithm can decrease the BER performance of the systems effectively.     

改进蛙跳算法的多中继协作系统最优功率分配

协作通信与直接通信相比能够显著地提高系统性能,功率分配是协作通信中的一个关键问题。为了获得合理的协作中继通信系统功率分配方案,提出一种基于改进蛙跳算法的多中继节点功率分配方法。首先对功率分配问题进行分析,将其转换为一个非线性优化问题,然后将青蛙表示为源节点,中继节点的功率,以平均信噪比作为青蛙的食物,并通过青蛙的信息交流和协作找到最优的功率分配方案,最后采用仿真对比实验对本文算法性能进行测试。仿真结果表明,相对于其它功率分配方法,改进蛙跳算法有效地提高了系统的信道容量,降低了中断概率,以较低的复杂度提高了系统的性能。     

Energy-efficient joint relay node selection and power allocation over multihop relaying cellular networks toward LTE-Advanced

Cooperative relaying is emerging as an effective technology to fulfill requirements on high data rate coverage in next-generation cellular networks,like long term evolution-advanced (LTE-Advanced).In this paper,we propose a distributed joint relay node (RN) selection and power allocation scheme over multihop relaying cellular networks toward LTE-Advanced,taking both the wireless channel state and RNs’ residual energy into consideration.We formulate the multihop relaying cellular network as a restless bandit system.The first-order finite-state Markov chain is used to characterize the time-varying channel and residual energy state transitions.With this stochastic optimization formulation,the optimal policy has indexability property that dramatically reduces the computational complexity.Simulation results demonstrate that the proposed scheme can efficiently enhance the expected system reward,compared with other existing algorithms.     

Power allocation in cooperative MIMO systems under individual power constraints

Power allocation(PA)plays an important role in capacity improvement for cooperative multiple-input multiple-output(Co-MIMO)systems.Many contributions consider a total power constraint(TPC)on the sum of transmit power from all nodes in addressing PA problem.However,in practical implementations,each transmit node is equipped with its own power amplifier and is limited by individual power constraint(IPC).Hence these PA methods under TPC are not realizable in practical systems.Meanwhile,the PA problem under IPC is essential,but it has not been studied.This paper extends the traditional non-cooperative water-filling PA algorithm to IPC-based Co-MIMO systems.Moreover,the PA matrix is derived based on the compound channel matrix from all the cooperative nodes to the user.Therefore,the cooperative gain of the IPC-based Co-MIMO systems is fully exploited,and further the maximal instantaneous capacity is achieved.Numerical simulations validate that,under the same IPC conditions,the proposed PA scheme considerably outperforms the non-cooperative water-filling PA and uniform PA design in terms of ergodic capacity.