认知无线网络中的跨层资源优化

跨层资源优化是设计认知无线网络重要的一环,是典型的多目标优化问题。为此,提出一种自适应克隆与邻域选择优化算法解决认知无线网络中的资源优化分配问题。以使用带宽、消耗功率、数据传输速率等指标作为认知网络优化目标,并将其在算法中进行优化。通过2种典型测试函数的仿真比较,结果表明该算法能够有效解决认知无线网络中的频谱资源分配、功率控制及速率提升等多目标优化问题,且与SPEA-2算法和NNIA算法相比,具有明显的优越性。     

基于能量效率的认知无线网络联合优化算法

为提高认知无线网络能量有效性,提出一种基于能量效率的联合优化算法。在考虑主用户干扰容限的基础上构建了能量有效性模型,将优化目标分解为接入策略求解和功率优化问题,采用粒子群算法反复迭代,得到接入概率与功率分配的联合最优解。仿真结果表明,相对于不考虑功率优化或接入概率的传统优化方法,所提算法可使系统能量效率得到显著提升。     

认知无线网络中基于多用户公平性的功率分配

研究认知无线网络中保证多用户场景下保证用户速率需要的功率分配问题.提出了保证用户公平性的最小化用户实际传输速率与期望速率差值的优化模型,给出了一种集中式功率分配算法1;为了减少减少迭代次数,提出了一种改进的集中式算法2;最后给出了一种分布式的求解算法3.仿真结果表明三种求解算法都收敛于最优解,且集中式算法2的迭代次数明显小于集中式算法1,分布式功率分配算法有利于减少实现的复杂度.     

一种多中继协作系统中功率优化分配策略的无线网络容量算法研究

针对限制网络容量的主要因素（信道带宽与信道信噪比）,本文提出了一种多中继协作系统中功率优化分配策略的无线网络容量算法。首先,论文提出采用多中继协作的方式,提高网络传输速率,建立网络最大流数学模型。然后,在网络总功率受限的情况下,对中继节点进行功率优化分配,建立最大化网络容量计算数学模型。最后,论文建立网络仿真环境,对比多中继协作且能量优化分配与非中继协作且能量等分两种策略在中断概率、网络容量等方面的表现。得出如下结论：网络容量随节点数量增加呈现先增后减的趋势,多中继协作且能量优化分配策略更加有利于提高无线网络容量。     

动态主用户流量模型的跨层优化设计

为适应主用户流量变化较快的场景,在不完美频谱感知的情况下最大化认知用户的吞吐量,提出了一种基于集中式Overlay认知无线网络中感知时间与资源分配跨层优化算法。将优化目标分解为信道分配和检测时间同功率分配联合优化两个子问题,通过子算法迭代,最终得到感知时间与资源分配的联合最优解。仿真结果表明,相对于仅考虑频谱感知或资源分配的单层优化算法,该算法可在兼顾公平的前提下使次用户吞吐量得到有效提升。     

基于禁忌搜索和Q-learning的CR-NOMA系统的功率分配算法

针对下一代移动通信对于高速率和大规模连接的需求,对认知无线电（CR）-非正交多址接入（NOMA）混合系统中通过优化功率分配来提升次用户总传输速率进行研究,提出一种基于禁忌搜索和Q-learning的功率分配（PATSQ）算法。首先,认知基站在系统环境中观测并学习用户的功率分配,次用户采用NOMA方式接入授权信道。其次,将功率优化分配问题中的功率分配、信道状态和总传输速率分别表述为马尔可夫决策过程中的动作、状态和奖励,通过结合禁忌搜索和Q-learning的方法来解决该马尔可夫决策过程问题并得到一个最优的禁忌Q表。最后,在主次用户服务质量（QoS）和最大发射功率的约束下,认知基站通过查找禁忌Q表得到最优的功率分配因子,实现系统中次用户总传输速率的最大化。仿真结果表明,在总功率相同条件下,所提算法在次用户总传输速率和系统容纳用户数量上要优于认知移动无线网络（CMRN）算法、次用户预解码（SFDM）算法以及传统等功率分配算法。     

无线网络中需求驱动的动态频谱分配

研究无线网络中协同动态频谱接入模型下的动态频谱分配问题,在考虑基站频谱需求的基础上,将物理干扰模型下的动态频谱分配问题建模为一个非线性优化问题。通过将非线性优化问题转换为线性规划问题,提出一种无线网络中需求驱动的动态频谱分配算法,计算初始频谱分配,并应用迭代增强算法为节点添加多余信道。仿真结果表明,该算法在有效频谱利用率和平均满意度上都优于现有算法。     

基于上下行对偶的CRN下行功率分配和波束赋形算法

认知无线网络（CRN）在underlay工作模式下的多用户下行功率分配和波束赋形问题研究中存在通用的SDR算法计算复杂度高,实用性受限以及优化问题中忽视主网络（PN）对认知用户（SU）的干扰等问题。针对这些问题,首先在CRN网络模型中增添PN对SU的干扰,生成优化问题;而后基于上行和下行的对偶特性,采用虚拟功率,将优化问题进行形式变换,成为上行功率分配和波束赋形问题;得到能够简便、快速求解的迭代算法。分析了算法的收敛特性,得到了收敛条件;并进一步计算了算法的复杂度,结果表明优于SDR算法。数值仿真显示,算法收敛很快;而且表明主网络基站（PBS）发送功率的变化影响可行解区域;PBS发送功率的增加会导致CRN下行功率增大,影响较显著。     

基于分布式协作Q学习的信道与功率分配算法

为提高分布式认知无线网络认知用户信道与功率分配算法的能量效率和收敛速度,将单位能量的平均比特数作为通信效率指标,平衡用户通信质量和系统能量消耗,提出一种基于多Agent协作强化学习的分布式信道与功率分配算法。在多Agent独立Q学习的基础上引入协作学习,各用户通过独立Q学习后,共享Q值并进行融合再学习。仿真结果表明,与基于能效的独立Q学习算法、独立Q学习算法以及随机功率分配算法相比,该算法能够有效提高认知用户发射功率和信道分配时的收敛速度。     

基于量子果蝇优化的认知无线网络频谱分配*

将频谱分配的二进制编码转化为量子序列编码,提出一种基于量子果蝇优化的认知无线网络频谱分配方法。首先,将果蝇优化算法(FOA)转化为量子果蝇优化算法(QFOA)算法,拓展FOA算法的应用范围;然后,采用选择、交叉、变异操作改进QFOA算法,提高算法收敛速度,增加样本种群多样性,避免算法陷入局部最优;接下来,利用改进QFOA算法对频谱分配的量子序列进行寻优,寻求最优的网络效益或者用户公平性,得到网络整体性能最优的频谱分配策略。仿真结果表明,改进的QFOA算法收敛速度快且跳出局部最优能力强,应用到认知无线网络频谱分配中,增加了网络资源利用率,提高了网络的整体性能。     

Multicell power allocation method based on game theory for inter-cell interference coordination

As a new technology, coordinated multipoint (CoMP) transmission is included in LTE-Advanced study item. Moreover, the network architecture in LTE-Advanced system is modified to take into account coordinated transmission. Under this background, a novel power allocation game model is established to mitigate inter-cell interference with cellular coordination. In the light of cellular cooperation relationship and centralized control in eNodeB, the power allocation in each served antenna unit aims to make signal to interference plus noise ratio (SINR) balanced among inter-cells. Through the proposed power allocation game algorithm, the users’ SINR can reach the Nash equilibrium, making it feasible to reduce the co-frequency interference by decreasing the transmitted power. Numerical results show that the proposed power allocation algorithm improves the throughput both in cell-center and cell-edge. Moreover, the blocking rate in cell-edge is reduced too.     

QoS constrained resource allocation to secondary users in cognitive radio networks

In this paper, 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 such an environment, we attempt to evaluate the optimal power and rate distribution choices that each secondary user has to make in order to maintain their quality of service (QoS). Our measures for QoS include signal to interference plus noise ratio (SINR)/bit error rate (BER) and minimum rate requirement. We propose two centralized optimization frameworks in order to solve for the optimal resource management strategies. In the first framework, we determine the minimum transmit power that SUs should employ in order to maintain a certain SINR and use that result to calculate the optimal rate allocation strategy across channels. In the second framework, both transmit power and rate per channel are simultaneously optimized with the help of a bi-objective problem formulation. Unlike prior efforts, we transform the BER constraint into a convex constraint in order to guarantee optimality of the resulting solutions. Simulation results demonstrate that in both frameworks, optimal transmit power follows “reverse water filling” process and rate allocation follows SINR. We also observe that, due to the ability to adapt both power and rate simultaneously to attain a certain BER, the joint optimization framework results in a lower total transmit power than the two-stage approach.     

基于信干噪比反馈的多基站协作预编码

针对蜂窝小区的干扰,给出了基于信干噪比(SINR)反馈的基站协作策略,采用SINR门限锁定系统边缘用户,避免了传统穷搜索算法的复杂性,在多小区规模上索引协作基站。基于SWF功率分配,采用SVD预编码设计。仿真表明,该方案既弱化了小区边缘用户受到的干扰,提高了系统信息吞吐量,又减少了高反馈量带来的复杂度,是一个很好的折中方案。     

一种多数据流MIMO系统中的改进自适应算法

研究表明自适应MIMO技术是无线频谱资源有限情况下提高通信系统吞吐量的一种有效方式.文中对数据流MIMO系统提出一种基于MMSE检测的改进自适应算法,首先利用基于奇异值分解(SVD)的注水算法进行初始功率分配和数据流选择,然后选用信干噪比(SINR)作为等效信道质量指示(CQI),在总发射功率和误帧率(FER)一定的前提下,根据现有一种迭代算法进一步计算每个数据流上分配的功率及其使用的调制编码模式.仿真结果表明该自适应算法能改善系统吞吐量,且在低信噪比下简化了原来的迭代算法.     

Interference aware resource allocation for hybrid hierarchical wireless networks

This paper addresses the problem of interference aware resource allocation for OFDMA based hybrid hierarchical wireless networks. We develop two resource allocation algorithms considering the impact of wireless interference constraints using a weighted SINR conflict graph to quantify the interference among the various nodes: (1) interference aware routing using maximum concurrent flow optimization; and (2) rate adaptive joint subcarrier and power allocation algorithm under interference and QoS constraints. We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution.     

多用户MIMO系统中机会波束截断的信道反演

针对下行链路多用户MIMO系统,提出了一种简单的基于机会波束截断的信道反演方法。机会波束形成可以用最小的反馈获得MIMO系统慢衰落信道中下行链路的多用户分集增益和复用增益。在机会波束形成进行自适应信道截断的基础上,使各通信用户的信干噪比（SINR）相同,改善了系统的误比特率性能。仿真结果表明,总的用户数为30时,系统误比特率性能提高3~4 dB。信道反演比注水功率分配简单,降低了系统复杂度。     

Channel allocation and power control schemes for cross-tier 3GPP LTE networks to support multimedia applications

In this paper, we present the framework of a channel allocation (CA) and power control (PC) schemes for the minimization of interference in cross-tier 3GPP LTE networks that aim to support internet of multimedia things. Channel allocation scheme based on an interference graph preserving the minimum number of interfered MUEs by femtocells (IG-MIM) is proposed to mitigate interference amongst femtocells, and a game theory based power control algorithm is also proposed to reduce interference to surrounding macrocell users (MUEs). The proposed IG-MIM scheme constructs the interference graph based on a predefined threshold and allocates the subchannels to the femtocells that maintain the smallest number of interfered MUEs. For the power control, we design a payoff function based on the rewards from the achieved data rates and the penalties from the interference in regards to its adjacent femtocells. The simulation results show that the IG-MIM channel allocation significantly improves the SINR performance for the femtocell users (FUEs) being served; the game theory based power control decreases the power requirements of a femtocell and alleviates the interference to the MUEs.     

认知网络中基于博弈论的联合功率控制与速率分配算法

针对认知无线网络上行链路中的资源分配问题,提出了一种适应于多小区认知无线网络的基于功率控制与速率分配的博弈算法。为了更加合理地控制用户的功率和速率,减小各次用户间的干扰,首先,在效用函数中分别给功率和速率设置了不同的代价因子,使其能够更加合理地控制用户,避免用户过度增加发射功率。其次,从理论上证明了该算法纳什均衡的存在性、唯一性以及算法的收敛性。最后,为了解决发射功率和传输速率的最优化问题,给出了联合功率控制和速率分配的迭代更新算法流程图。理论分析及仿真结果表明,与同类博弈算法相比,在保证通信质量的前提下,所提算法可以使得用户以较小的发射功率获得较大的传输速率和较高的信干噪比（SINR）,并且减小了用户间的干扰,提高了次用户系统容量。     

A flexible mid-term frequency domain scheduler for resource allocation in HetNets based on the SINR requested by users

This article treats the resource allocation problem for the downlink of a multi-cell, multiservice Wireless Mobile Communications System (WMCS) with heterogeneous architecture deployed into an urban environment using Long Term Evolution (LTE) and Orthogonal Frequency Division Multiple Access (OFDMA) in its physical level.The optimization model aims to satisfy services to users by making an efficient use of the available resources, and a fair frequency block allocation, using the Signal to Interference-plus-Noise Ratio (SINR). It is a Mixed Integer Nonlinear Programming (MINLP) model whose solution is complex to obtain directly. The proposed solution algorithm decouples the solution space of the problem and uses an iterative and semi-distributed approach to implement a frequency-domain scheduler in the medium term that uses a global vision of the system to allocate resources trying to obtain the SINR required for all users (the proposed goal). Since it is not always possible to achieve it, we take advantage of the elasticity of some of the services offered and incorporate a slack variable to solve it.The approach allows selecting the frequency allocation strategy, the exploration focus of the search space and the system administrator’s vision. The results obtained show that the implementation that uses a coordinated frequency allocation obtains better results in the amount of users with full satisfaction and in the use of power when compared to implementations using other frequency allocation strategies. In scenarios with heterogeneous architecture, the combined effect of picocells and coordinated frequency allocation improves the value for the defined performance metrics.