Robust beamforming and artificial noise design in interference networks with wireless information and power transfer

In this paper, the robust beamforming and artificial noise design is investigated in two-user interference networks with wireless information and power transfer. Specifically, we focus on the secure communication of the two pairs in the presence of an energy receiver (ER) which acts as the potential eavesdropper and intends to wiretap the confidential message transmitted to one of the information receivers (IRs). With only imperfect eavesdropper’s channel state information (ECSI) at the transmitters, our goal is to minimize the total transmit power, while guaranteeing the worst-case secrecy rate requirement at the wiretapped IR, the signal-to-interference-plus-noise ratio requirement at the wiretap-free IR and the energy harvesting requirement at the ER. In particular, we first model the imperfect ECSI in the sense of ellipsoidal uncertainties. Then, our design goal can be further reformulated as a two-stage optimization problem. With the help of rank relaxation and one-dimensional line search, the considered two-stage problem can be solved efficiently. Simulation results verify the effectiveness of the proposed design in different scenarios.     

无线携能通信系统中基于人工噪声的波束成形算法研究

在存在多天线窃听者的情况下,研究了无线携能通信系统的物理层安全传输问题。传统上,人工噪声方案是一种保证物理层安全通信的有效策略。因此,提出了一种人工噪声辅助的波束成形算法,以提高信息与能量联合传输的安全性。该算法在满足多项约束（接收端能量采集门限、信息泄漏控制指标和发送功率）的基础上,通过优化波束成形预编码矩阵和人工噪声实现无线携能通信系统的物理层安全通信。在数学上该算法是一个非凸优化问题,不易求解。为此,首先引入最小均方误差接收算法和连续凸近似方法将其转换为凸的二阶锥规划子问题,然后对该凸问题进行迭代求解。仿真结果表明,该算法能够在保证窃听者无法解码信息的同时,实现信息和能量的联合传输,并且算法收敛速度快。     

无线充电传感器网络能量效率优化研究

本文将SWIPT技术应用到无线充电传感器网络中,提出了一种基于SWIPT的协作传输协议（简称CTS）,利用无线信息和能量的协作传输来提高无线能量传输的效率。在此基础上,设计了一个以最大化网络效用为目的的资源分配策略优化问题,并提出RAPOA算法来求解问题。仿真实验表明CTS最大化了网络效用,提高了无线充电传感器网络的能量传输效率。     

能量收集无线网络中面向统计服务质量的最优功率分配

针对能量收集无线网络中的服务质量（QoS）保障问题,提出了面向统计QoS的最优功率分配方案,从而最大化时延QoS约束下的有效容量。首先,构建能量收集无线网络的有效容量最大化问题。其次,利用凸优化理论求解出最优功率分配方案以及该方案下的最大有效容量,并得出了两种特例下的最优功率分配方案,即：当QoS需求非常松弛时,最优化功率分配方案收敛于注水策略;当QoS需求非常严格时,最优化功率分配方案收敛于信道反转策略。然后,求解了所提最优功率分配方案得到的信道中断概率。最后,通过仿真实验,检验了该最优功率分配方案的性能。实验结果表明,与现有策略相比,所提方案能够获得更大的有效容量。     

A MAC layer power management scheme for efficient energy delay tradeoff in a WLAN

Energy efficient operation is of paramount importance for battery-powered wireless nodes. In an effort to conserve energy, standard protocols for WLANs have the provision for wireless nodes to “sleep” periodically. In this paper we first consider the problem of optimizing the timing and duration of the sleep state of a single wireless node (or user) with the objective of minimizing power consumption with respect to a QoS constraint. The QoS parameter that we have focused on is average packet delay. Using a Dynamic Programming formulation, coupled with a duality argument, we solve the optimization problem numerically. Using a branching process analysis, we were able to derive closed form expressions for the optimal sleep duration, as well as the associated minimal rate of power consumption. We show that the optimal power cost derived from the one-user Dynamic Programming (DP) formulation provides a lower bound to the average power consumption for the multiple user case. To gain better insight into the optimal sleep policy we also formulate and solve a two-user optimization problem, similar to the one user case. Although the complexity of the DP approach grows very quickly with the number of users, the insights gained from the DP approach led us to design a simple, centralized, adaptive algorithm for assigning the sleep duration of an arbitrary number of wireless nodes operating in an infrastructure mode served by a single Access Point (AP). Our algorithm adapts dynamically to the packet arrival rate and statistics, as well as the tolerable average packet delay. We describe two different service policies – the Round Robin scheme and the Shortest Sleep First (SSF) scheme. The Round Robin scheme is the preferred service policy when all wireless nodes in the system have the same packet arrival statistics and the same tolerable average delay. The SSF Scheme is designed mainly for a system where nodes are heterogeneous with different tolerable average packet delay. Simulation results show that the power efficiency of our algorithm is comparable to the bound on performance that is obtained from the one-user dynamic programming formulation.     

QoS保障下的无人机传感网安全通信路径规划

在无线传感器网络中,无人机在传感器覆盖区域内定期巡游,以收集传感器感知的数据。由于无线信道的广播性质,信息更容易被地面上的非法节点窃听,无线通信安全受到挑战。通过无人机的轨迹规划和传感器功率控制可以在物理层保障无线通信的安全性。然而,现有研究无人机辅助无线通信路径规划的文献中,没有考虑到用户或节点需要最小通信时间来保证服务质量。针对此问题,在无线传感器网络通信系统中,加入最小通信时间约束,通过联合优化无人机的飞行轨迹、传感器的发送功率和无人机服务传感器的调度顺序,提出平均保密率最大化问题,并证明了其非凸性。为解决所提的非凸问题,将原问题分解为3个子问题,提出了一个应用块坐标下降、连续凸优化、迭代舍入方法的快速收敛迭代算法TPA。实验结果表明,所提算法TPA的平均保密率比未进行轨迹优化的基准算法提高了15.7%,比未进行功率控制的基准算法提高了159.8%。TPA与未加入最小通信时间约束的基准算法相比,在2种不同任务分布情况下,当无人机飞行周期大于70 s时,任务完成率平均提升44.6%和27.1%。     

An efficient routing scheme with optimal power control in wireless multi-hop sensor networks

Power consumption is a critical problem in providing multimedia communications among wireless sensor nodes (WSNs). To reduce power consumption and satisfying QoS requirements, in this paper, we propose an efficient routing scheme with optimal power management and on-demand quality control for WSNs. Two cost functions are developed to minimize the transmitting power and maximize the link quality under the constraint that an end-to-end frame error probability should be met. The heuristic problem of minimizing power consumption under frame error constraints is formulated and resolved with a closed-form expression. With this closed-form expression, we can determine an optimal route rapidly by calculating the power requirement for each sensor node. Finally, our analytical results indicate that the proposed scheme is superior to a previous work with the same constraint and is also comparable to the results obtained from a heuristic simulation.     

SWIPT网络中保障物理层安全的保密能量效率优化

针对下行多用户携能通信网络中具有非线性特征的能量收集过程,提出了一种使用连续凸逼近方法的能量收集方案.该方案考虑授权用户对信息的安全性要求,构造了具有最大化保密能量效率的优化问题,联合优化了多用户的保密速率与网络能耗.为求解该多变量耦合的非凸优化问题,采用泰勒级数转换非凸函数,在连续凸逼近和Dinkelbach理论框架内,设计了满足最大保密能量效率要求的资源分配算法,获得了授权用户所需的最小输入功率.仿真实验的结果验证了该算法在最优化系统保密能量效率上的有效性.为多输入多输出或无法获得完整信道状态信息等更真实无线携能通信网络中通信安全及能量效率的研究提供了依据.     

基于RSS的无线传感器网络半定规划定位算法研究

在无线传感器网络定位中,基于RSS测量的定位方法是最常用的方法之一。由于传统的最大似然估计(MLE)算法的目标函数具有非线性和非凸性,在应用于无线传感器网络定位时,会产生多个局部最优值。针对该问题提出一种基于半定规划(SDP)的凸优化定位方法。首先采用泰勒级数近似对目标函数进行线性化处理,然后通过引入冗余变量将原无约束优化问题转化为约束优化问题,最后应用半定松弛(SDR)技术将约束优化问题转化为半定规划(SDP)凸优化问题进行求解。通过仿真实验的比较,说明本文提出的优化算法在定位精度、鲁棒性方面优于已有算法。     

智能反射面辅助的无线传感网络充电策略研究

在无线可充电传感网的研究中面临诸多挑战,如无线功率传输中易衰弱、充电规划复杂度高、内存数据易溢出导致丢包。为此,引入智能反射面（IRS）并基于强化学习设计一种无线传感网能量传输和数据收集方案IRS_MDP。首先,该方案建立反射相位偏移优化问题,计算出以任一传感器节点为充电目标节点时IRS的最优相移值,实现最大化目标节点处所接收的功率。其次,根据上述结果并结合传感器实时状态,基于强化学习设计关于充电和数据传输过程的优化充电策略实现丢包率降低。仿真结果表明,该方案相较其他方案可以更好地提升网络吞吐量和降低数据丢包率。     

智能反射面辅助无人机的物理层安全传输方案

在无线通信系统中,信息发送端和接收端之间的通信链路易受到建筑物的遮挡和非法者的主动窃听。利用无人机（unmanned aerial vehicle,UAV） 灵活的移动性以及智能反射面（intelligent reflective surface,IRS） 在无线环境中智能可控特性,提出一种智能反射面辅助无人机的物理层安全传输方案,以最大化系统平均保密率。该方案首先采用块坐标下降法将最大化系统平均保密率问题分解为UAV-IRS飞行轨迹优化、IRS相移优化以及系统传输功率优化三个子问题。其次,通过引入松弛变量、相位对齐以及逐次凸逼近方法将每个子问题转换为凸优化问题。最后,再运用交替优化方法逐次求解三个凸优化问题。数值仿真结果表明,系统平均保密率与源节点发射功率、UAV-IRS飞行位置和高度、IRS反射元件数量等因素有关。并且与另外两个基准方案相比,所提的方案能有效地提高系统的平均保密率,并且具有较好的收敛性。     

基于误码率与中断概率约束的femtocell网络分布式功率控制

家庭基站(femtocell)网络可有效改善无线通信业务的室内覆盖性能,提高信道容量.然而,复杂的动态通信环境导致信道的不确定性,影响用户服务质量.基于此,研究双层femtocell网络在快衰落信道环境下基于误码率约束的功率控制问题;考虑信号传输的中断概率,以及服务质量指标–误码率等方面的要求,构造在此约束下的优化问题;最大化双层femtocell网络的净收益,使得网络系统的通信性能最优;通过对概率约束进行数学处理,将其转化为确定性形式,并提出分布式鲁棒优化算法对等价的确定性优化问题进行求解,从而获得最优功率分配策略.最后,通过仿真验证了所提出算法的收敛性和有效性.     

面向无线传感器网络的无线携能通信研究

能量受限是无线传感器网络应用的瓶颈问题,为了使无线传感器网络获得稳定持续的能量来源,提出将无线携能通信（ SWIPT）技术应用到无线传感器网络中。基于时分多址（ TDMA）的通信方式建立了适应于无线传感器网络的无线携能通信系统新优化模型。通过凸优化问题的求解得到该优化模型的最优分配策略。利用仿真实验对无线携能通信在无线传感器网络中应用的可行性进行了分析,对方法的有效性进行了验证。     

Cooperative updating in the Hopfield model.

We propose a new method for updating units in the Hopfield model. With this method two or more units change at the same time, so as to become the lowest energy state among all possible states. Since this updating algorithm is based on the detailed balance equation, convergence to the Boltzmann distribution is guaranteed. If our algorithm is applied to finding the minimum energy in constraint satisfaction and combinatorial optimization problems, then there is a faster convergence than those with the usual algorithm in the neural network. This is shown by experiments with the travelling salesman problem, the four-color problem, the N-queen problem, and the graph bi-partitioning problem. In constraint satisfaction problems, for which earlier neural networks are effective in some cases, our updating scheme works fine. Even though we still encounter the problem of ending up in local minima, our updating scheme has a great advantage compared with the usual updating scheme used in combinatorial optimization problems. Also, we discuss parallel computing using our updating algorithm.     

鲁棒的双向多中继物理层安全传输方案

针对双向多中继系统物理层安全传输无法获取窃听者的精确信道状态信息（CSI）的问题,提出鲁棒的多中继协作波束形成和人工噪声联合物理层安全传输方案,以最大化系统总功率约束下信道状态"最差情况"时的安全总速率。在该方案中,待求解的问题是一个复杂的非凸优化问题。采用交替迭代和连续凸近似（SCA）方法,对波束形成向量、人工噪声协方差矩阵和源节点发射功率进行交替优化迭代,得到了问题的优化解。仿真实验验证了所提方案的有效性,并表明该方案具有更优的安全性能。     

射频供能传感网中能量源布置和发送功率优化

射频能量捕获无线传感网（RF energy harvesting wireless sensor network,简称RFEH-WSN）是无线传感网的热点研究领域之一,专用射频能量源设备（energy transmitter,简称ET）的使用进一步增强了网络的可控制性和实用性.这类应用中一个值得研究的问题就是如何配置给定数量的ET,从而在满足节点能量需求的前提下优化布置位置和发送功率,减少能量消耗.首先对ET布置和发送功率联合优化问题建模,明确优化目标和限制条件.然后分别提出了先基于聚类算法确定ET位置再调整功率的分步优化方案,以及基于粒子群优化（particle swarm optimization,简称PSO）的布置与发送功率联合优化方案.仿真结果显示,布置和发送功率联合优化方案较分步优化方案,ET发送功率的节能效果更为明显.     

Energy-efficient cooperative routing in BER constrained multishop networks

Due to the limited energy supplies of nodes, in many applications like wireless sensor networks energy-efficiency is crucial for extending the lifetime of these networks. We study the routing problem for multihop wireless ad hoc networks based on cooperative transmission. The source node wants to transmit messages to a single destination. Other nodes in the network may operate as relay nodes. In this paper, we propose a cooperative multihop routing for the purpose of power savings, constrained on a required bit error rate (BER) at the destination. We derive analytical results for line and grid network topologies. It is shown that energy savings of 100% are achievable in line and grid networks with a large number of nodes for BER = 10⁻⁴ constraint at the destination.     

双无线供能IRS辅助的无线通信系统的吞吐量优化研究

在未来物联网等新型无线网络场景中,需要进行信息和能量同步传输,而且通信环境复杂多变,通信设备维护成本较高。一方面,智能反射面(IRS)能通过对无线信道的智能调控提高无线通信与无线传能的性能,另一方面,通过无线能量传输对IRS进行供能,解决部署IRS时存在的供能不便的问题,降低设备维护成本。研究双无线供能IRS辅助的无线通信系统的吞吐量优化,在该系统中,多天线基站先向IRS无线传输能量,然后在IRS的辅助下向多个单天线用户发送信息。针对基站与IRS之间的信道不受阻和受阻两种情况,分别提出两时隙和三时隙的传输模式,并研究优化它们的吞吐量。具体而言,研究联合优化基站的发射波束成形、IRS的反射波束成形以及各时隙长度,在基站最大发射功率、各用户最小接收速率、各时隙持续时间和IRS反射系数的模一约束下,最大化系统的总吞吐量。由于优化变量高度耦合,难以直接求最优解,提出了基于交替优化、连续凸逼近和半正定松弛的优化算法,以求得优化问题的高质量次优解。仿真结果显示,所提联合优化算法取得了明显高于基准算法的吞吐量性能,并且揭示了两时隙和三时隙传输模式的适用场景。     

Massive MIMO 下行系统能效资源分配算法

摘 要: 针对无线通信网耗能造成二氧化碳排放量和运营成本日益增加的问题,提出了一种下行大规模天线系统能效最优的资源分配算法。算法在基站端采用最大比合并(MRT)的预编码情况下,考虑各用户最小数据速率、最大发射功率和可容忍的干扰水平约束条件下,以最大化系统能效下界为准则建立非凸优化模型。首先采用一种迭代算法确定每个用户的带宽分配,然后根据分数规划的性质,将能效优化问题的分数形式转化为减式形式,进而利用凸优化方法求解基站端最优的发射天线数和发射功率来获得最优能效。仿真结果表明,所提算法能以较小的迭代次数收敛到最大能效值,并且有较好的系统频谱效率性能,同时算法复杂度得到了显著降低。     

基于能量收集的环境反向散射通信联合优化算法设计

针对环境反向散射通信系统,设计两跳无线信息和能量传输方案并基于能效最大化准则给出联合优化算法。源端配置多天线并采用最大比发送(Max Ratio Transmission,MRT)预编码方法,中继节点使用功率分流法以完成信息发送与能量收集。基于系统传输模型,对源端天线数和发送功率采用联合优化算法以得到系统最大能效。借助高信噪比近似法进行非凸向凸的转化以解决优化目标中非凸问题。此外,利用Lambert W函数得到源端天线数和发送功率联合优化的最优解。仿真结果验证了所提方案的有效性和正确性。