最大化瑞利熵的干扰对齐优化算法

干扰对齐技术常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,然而目前采用的迭代方法并不能做到完全的干扰对齐。针对这种情况,提出了一种新的干扰对齐优化算法,避开了反转信道的操作。该算法在最大化信干噪比算法的基础上加入完全干扰对齐的约束条件,将系统中各用户的所有干扰对齐约束条件进行奇异值分解,最终通过瑞利熵最大化的求解方法联合迭代求解发送侧的预编码矩阵与接收侧的干扰抑制矩阵。仿真结果表明,所提优化算法在较高信噪比时不同天线数下的和速率、不同迭代次数下的和速率等方面都优于原最大信干噪比算法。     

基于干扰和功率控制的多小区分布式波束成形

在多小区干扰信道中,基于分布式竞争设计,提出两种优化基站发射波束成形矩阵的设计,使每个小区的最差信干噪比最大.一种是基于干扰控制的设计,利用差异化的干扰系数,抑制小区间的干扰,提高系统性能.另一种是基于功率控制的设计,通过调整各基站的发射功率,提高系统性能.这两种设计,都能保持算法的分布式特性,又能有效地提高用户信干噪比.仿真分析表明,基于功率控制的设计在功率大的情况下,性能优于基于干扰控制的设计.     

一种基于博弈论的5G异构网络多目标优化干扰算法

为解决高铁无线网络的通信干扰问题,提升高铁通信的吞吐量和能量效率,提出了一种基于博弈论的双目标优化干扰算法。首先,通过获取非理想信道的相应预编码矩阵和干扰抑制矩阵,计算包括延迟和衰落的非理想信道状态信息,实现干扰信号的空间对齐。其次,基于系统总功率、信干噪比,建立了功率分配双目标最佳博弈模型,实现吞吐量和能效的双重优化,并采用最大信噪比的干扰对齐算法,通过迭代计算实现干扰管理优化。最后,基于Matlab仿真平台与传统的干扰优化算法进行对比分析。实验结果表明,当信干噪比为30 dB、列车运行速度为300 km/h时,所提算法的吞吐量增加48.95%,能量效率增加53.02%,误码率减少14.37%;当信干噪比为30 dB、轨旁设备数量为5时,所提算法的吞吐量达到88.03%,能量效率达到71.58%;与其他算法相比,所提算法在系统吞吐量、能量效率和传输可靠性方面均具有显著优势。     

多用户MIMO网络下基于分簇的非迭代干扰对齐算法

针对多用户多输入多输出(MIMO)干扰网络条件下,干扰对齐算法性能受限的问题,提出一种多用户MIMO网络下基于分簇的非迭代干扰对齐算法。通过一种分层的干扰处理设计,首先在上层依据干信链路耗损比,将来自不同发送端的干扰分为簇内有效干扰和簇间无效干扰;然后在下层利用联合最大化信漏噪比(SLNR)算法与迫零(ZF)算法消除干扰,提升了算法的适用性。仿真结果表明,当用户数量较多时,所提算法与现有算法相比,在高信噪比(SNR)条件下具有更高的系统容量与更低的系统复杂度。     

多用户认知网络中基于Grassmann流形梯度法的干扰对齐算法

针对多个主用户和多个次用户的MIMO认知网络,本文给出了一种不依赖信道互惠性和不需要前后向链路交替式迭代的干扰对齐方法。对于次用户,首先,通过对其进行编码,建立了消除主次用户间相互干扰后的等效模型。然后,在等效模型的基础上,以最大化总容量为目标函数设计预编码矩阵,并采用基于Grassmann流形上的梯度法对目标函数进行求解得到预编码。最后,在接收端以最大信干噪比准则来设计接收滤波器矩阵。仿真结果显示,在低信噪比时,本文算法与现有典型算法性能相同,而在高信噪比时本文算法性能更优。      

多小区MIMO系统中干扰对齐算法分析

干扰对齐技术是解决无线通信系统中同频干扰的重要手段,与传统干扰管理方法相比可获得更大的信道复用增益,提高系统容量。基于工程应用实现的考虑,重点研究了多小区MIMO系统中干扰对齐技术的实现,对求闭式解的经典算法和分布式迭代典型算法在系统容量、收敛性等方面的性能进行了分析比较。针对未来Massive MIMO技术的应用,同时仿真分析了算法在空间相关信道下性能,并分析总结了算法的适用情况。仿真结果表明,基于矩阵投影距离的分布式迭代干扰对齐算法综合性能最优,且具有更好的工程适用性。     

非对称MIMO双向中继干扰信道的干扰对齐算法

针对非对称的多用户MIMO双向中继干扰信道,本文提出了一种简化的基于最大信干噪比的干扰对齐算法,给出了干扰对齐的可行性条件和干扰抑制方案,并分析了系统容量和自由度。本文算法的中继节点不必做复杂的信号处理,大大降低了整个系统的信号处理复杂度;同时,本文算法是基于最大信干噪比方案,与现有文献的中继迫零方案比较,大大提高了系统在中低信噪比时的容量;进一步,通过仿真验证表明,基于本文算法的K用户对双向中继干扰网络可以达到。      

基于容量最大化的非迭代干扰对齐优化算法

现有分布式迭代干扰对齐算法没有考虑基站与用户终端处理能力的差异,使得基站和用户端都具有较高的计算复杂度和系统开销。针对下行链路和上行链路分别提出一种基于容量最大化准则的非迭代干扰对齐优化算法。所提算法在基站端使用基于容量最大化准则的优化方法求解发送预编码矩阵或接收抑制矩阵,在用户端使用迫零准则生成接收抑制矩阵或随机生成发送预编码矩阵。分析和仿真结果表明,所提的2种算法基站端的计算复杂度和系统开销与现有算法相当,但用户端的计算复杂度和系统开销大大降低,并且可以获得与最大信干噪比(Max-SINR)算法相当的系统性能。     

蜂窝系统中分布式空域基站协作的仿真研究

对分布式空域基站协作进行了分析仿真,重点对两小区场景和三小区场景采用最大化层虚拟信干噪比算法的预编码技术进行了仿真验证,并与采用最大化虚拟信干噪比算法的预编码技术进行了比对。仿真结果表明通过分布式的基站协作预编码算法,可以有效地抑制小区间干扰,提高系统的性能;结果还表明层虚拟信干噪比算法比虚拟信干噪比算法有更好的性能,增加天线数量也可以提高系统的性能。     

认知MIMO系统基于正交投影的SLNR收发联合设计算法

为实现认知MIMO系统中认知网络与主用户网络的高效频谱共享,提出一种基于正交投影的SLNR收发联合设计算法。该算法首先通过正交投影预处理将信号投射到干扰信道的零空间从而消除对主用户的干扰,然后针对认知网络,以改进的信漏噪比为优化指标,利用交替迭代的思想联合设计收发处理矩阵,提高认知网络的性能。仿真结果表明,算法能有效抑制用户间的共信道干扰,在保证主用户正常通信的同时,有效提高了认知网络的误码率及和容量性能。      

Interference graph based adaptive interference coordination method in indoor UDN

An interference graph based adaptive interference coordination method was proposed for indoor scenario of ultra dense network (UDN).The algorithm aimed at maximizing system throughput.Firstly,the interference relationship in the system was modeled as an interference graph,and the iterative coloring algorithm was used to determine the available resources of each small cell base station (SBS).Thereafter,the SBS allocated resources to each user by using a throughput optimizing resource allocation algorithm.The method could adaptively select a resource allocation strategy according to the network topology and channel conditions,thereby mitigating interference in the system.The simulation results show that compared with the existing methods,the proposed method effectively reduces the system outage probability while significantly improving the throughput performance through a small additional signaling overhead.     

Interference alignment based on optimizing bit allocation with limited feedback in interfering MIMO-MAC networks

A novel limited feedback for interference alignment algorithm was proposed based on the disadvantages of traditional limited feedback interference alignment schemes for MIMO uplink.Unlike the traditional linear interference alignment,an iterative scheme was presented.The pre-coder was designed through maximizing the target signal to the interference leakage and noise ratio,and interference suppression matrix was designed by maximizing the signal to interference plus noise ratio for each data stream,which can come over rate loss in low SNR.In addition,the bit allocation of traditional limited feedback schemes were based on the mean of interference leakage,which were not perfect and make the total number of the effective bits less than the bits provided by system.Thus,a novel bit allocation scheme was provided that improving bit utilize and decreasing quantization error.Theoretical analysis and simulation experiments show that compare to the existed classical algorithms,the algorithm was a stepwise enhancement of signal quality for iterative search in perfect CSI which was better than linear algorithm and has a larger space with no need for strictly align interference in limited feedback CSI which reduces the influence of quantization error more.The effective bit distribution and bit utilization are improved by bit allocation,resulting in improved performance in limited feedback.     

基于认知无线电的新型非合作功率控制博弈算法

从认知无线电技术特性出发,在干扰温度门限的限制条件下,提出了基于新的代价函数功率控制博弈论算法,以有效地提高认知用户的信干噪比。根据信道状况、吞吐量最大化和功率限制的需求,将功率控制问题转化为一个干扰受限的多约束非线性规划问题。结合博弈论和最优化理论,证明了其纳什均衡的存在性和唯一性,给出了该模型的分布式求解算法。仿真实验表明,该算法可以有效提高认知用户的QoS和系统性能,充分利用无线资源。     

基于压缩感知的MIMO-OFDM系统自适应信道估计

针对超密集组网中导频复用将产生导频干扰,严重影响移动用户下行链路信道估计准确性的问题,提出了一种使用短导频的幂函数稀疏度自适应匹配追踪(Power Sparsity Adaptive Matching Pursuit,PSAMP)算法.该算法由稀疏度预估计和追踪重构两部分构成.首先通过幂函数试探得到一个略小于真实稀疏度的预估值,再通过压缩采样匹配追踪重构信号,改善估计结果;若不能成功重构,则逐渐增加信号原子数量.仿真结果表明,相较于传统自适应压缩感知重建算法,所提的P SAMP算法在高信噪比区域具有更好的信道估计性能.     

Interference avoidance strategy for ultra dense network with pilot reuse

In the ultra dense network (UDN),the pilot reuse scheme would produce significant interference,which will affect the accuracy of channel estimation.To solve this problem,an interference avoidance strategy for UDN with pilot reuse was proposed.An interference model of subcarriers for UDN was provided and the interference probability of subcarriers was derived.Then,based on the model,a pilot position selection model was proposed and an interference avoidance strategy for UDN with pilot reuse was provided.The simulation results show that compared with the traditional channel estimation algorithm,the channel estimation with proposed interference avoidance strategy can effectively avoid the interference and ensure the accuracy of channel estimation in UDN with pilot reuse.     

Performance analysis of ultra‐dense networks with MRC reception and successive interference cancellation under rate‐limited backhaul

Ultra‐dense network (UDN) is one of candidate technologies for next generation cellular networks. In this paper, we explore performance limits of cooperative UDN with maximal ratio‐combining detection under limited‐capacity backhaul links. More concretely, based on the imperfect estimation, lower bounds of the average per‐user rate are derived for maximal ratio‐combining detection with and without successive interference cancellation scheme when the number of Base stations (BSs) in the network goes to infinite. Then we discuss how the average per‐user rate is impacted by the number of cooperative BSs and the backhaul capacity. Our results show that there is an optimal number of cooperative BSs in the UDN to achieve the best performance in low signal‐to‐noise‐ratio region. Simulations demonstrate that our asymptotic rate bounds are tight when the number of BSs is large. Copyright © 2016 John Wiley & Sons, Ltd.     

Joint optimization and threshold structure dynamic programming with enhanced priority scheme for adaptive VANET MAC

Nodes in vehicular ad-hoc network (VANET) are highly mobile, traversing in unpredictable and varying environment. Therefore, contention window size and transmission power should adapt according to the high mobility transmission environment. In this paper, we propose an adaptive VANET medium access control (MAC) layer with joint optimization for VANET (MACVS) which aims at minimizing average delay and maximizing packet success rate. An adaptive joint optimization with proposed threshold structure dynamic programming, with closed loop feedback control system, is designed to optimize contention window size and transmission power. Adaptive optimization is done based on road traffic conditions and transmission reliable distance range (depicted by interference and noise), by monitoring the continuous change and threshold of received signal strength to interference and noise ratio. Mathematical expressions have been developed for the MACVS optimization framework, and the produced analytical results show good agreement with the simulation results. Simulations with different arrival rates and urban map of city center show that the proposed MACVS with low complexity joint optimization effectively reduces end-to-end delay while achieving high packet success rate under various network traffic condition.     

Transmit Antenna Selection with Optimum Combining for Aggregate Interference in Cognitive Underlay Radio Network

Transmit antenna selection (TAS) is most popular technique in underlay cognitive radio (CR) networks as they increase the capacity of secondary users with less hardware requirements. In this paper, a new scenario of CR ad-hoc network topology is proposed in which apart from primary users, there are multiple number of secondary users which are assumed to be distributed as homogeneous spatial Poisson point process (PPP) and are trying to use the primary spectrum in underlay mode. These multiple secondary transmitters generate the aggregate interference and can degrade the performance of secondary receiver. Here this aggregate interference is estimated and its impact on performance of secondary receiver under unconstrained mode of operation is presented. Further, to enhance the performance of secondary receivers in this scenario, single TAS technique based on maximizing the received signal to interference noise ratio by using optimum combining (OC) method is proposed. Furthermore, in this work the design of end to end Simulink based environment for secondary trans–receiver system with advancements in channel design and estimation is proposed. The bit error rate (BER) analysis is presented and verified for image data for single TAS-OC technique for unconstrained mode in underlay CR network in Rician fading channel. The BER performance is also presented for different number of secondary interference sources which are located at fixed distance in one case and they are assumed to be distributed as PPP in another case.     

Interference suppression for ultra dense network based on compressive sensing framework

Ultra-dense network (UDN) deployment of small cells introduces novel technical challenges, one of which is that the interference levels increase considerably with the network density. This paper proposes interference suppression scheme based on compressive sensing (CS) framework for UDN. Firstly, the measurement matrix is designed by exploiting the sparsity of millimeter wave channels. CS technique is employed to transform the high dimension sparse signal into low dimension signal. Then, the interference is canceled in the compressed domain. Finally, the stagewise weak orthogonal matching pursuit (SWOMP) algorithm is used to reconstruct the useful signal after interference suppression. The analysis and simulation results demonstrate the effectiveness of the algorithm. Simulation results demonstrate that the proposed interference suppression in compressive domain yields performance gains compared to other classical interference suppression schemes. The proposed algorithm can reduce the computational complexity of interference suppression algorithm.     

一种快速FH-OFDM通信帧格式及其验证

针对通信中跳频与正交频分复用两种技术结合存在同步困难的技术难点,提出一种快速跳频OFDM无线宽带通信帧格式,并设计了一种占用带宽为10 MHz、跳频速率为2 kHz、基带数据传输速率为14.324 Mbit/s的快速跳频OFDM通信收发系统.该帧格式使用加长循环前缀的方式提供高精度载波同步依据,将伪随机序列隐藏到频域数据中以便利用其完成精确定时同步、采样时钟同步和整数倍频偏估计,并且插入了梳状导频以便接收端进行信道估计.实验结果表明,接收机星座图可以很好地收敛,在信噪比为10 dB情况下,误码率低于10-8.本帧格式可较好地满足视频等数据的无线通信要求.