异构无线网络中基于SINR和层次分析法的SAW垂直切换算法研究

B3G或者4G无线网络体系致力于集成各种异构无线接入网络,其中一个主要的设计课题是支持垂直切换的研究。该文将多属性QoS考虑在内,针对各业务特点,提出一种基于SINR(信干噪比)和层次分析法(AHP)的SAW(简单加权法)垂直切换算法(SASAW)。它综合考虑SINR的影响以及要获得同等数据速率情况下,目标网络需要的等效SINR数值、用户通信代价、网络可用带宽等来构造属性矩阵做切换判决。为了评估性能,考虑3GPP定义的4类业务,利用层次分析法中的特征向量法来决定各个QoS属性之间的权重关系,构造比较判决矩阵并检验其一致性;根据判决矩阵,利用特征根法获得权重向量;最后根据属性矩阵和权重向量,利用SAW垂直切换算法进行判决。通过对算法的通过率、丢话率、垂直切换次数、平均用户代价等的性能比较,结果表明该文提出的算法能够根据各业务特点综合考虑各属性间关系,获得优良的系统性能。     

新的V-BLAST系统次优天线选择

该文提出新的基于ZF SIC检测的V-BLAST系统次优天线选择准则:最小化信道矩阵伪逆的最大行范数。基于贪婪选择思想,发射天线选择采用使得该范数增加最小的递增选择策略,接收天线选择采用使得该范数减少最大的递减选择策略。仿真表明所提出的新准则明显优于已有的最大第1检测层后处理信噪比准则,且相应的快速选择算法可以获得最优的基于最大最小准则的全搜索选择的大部分分集增益,而复杂度很低。     

FDA最优频率增量选取必要性分析

在干扰背景下,深入研究了频率分集阵列（FDA）雷达选取最优频率增量的必要性。在采用最优波束形成算法进行抗干扰的前提下,推导出目标与干扰的位置关系对FDA雷达输出信干噪比（SINR）的影响,进而分析输出SINR与频率增量的关系,并得出结论：在只有副瓣干扰的情况下,可不进行最优频率增量的选取,采用常规固定的频率增量也能输出高SINR;而当存在主瓣干扰时,不当的频率增量会使得输出SINR急剧下降并形成凹陷,且这种凹陷会随着频率增量的选取呈现周期性变化,极大地影响了FDA雷达的目标检测性能。计算机仿真也验证了这种周期性的凹陷变化,这表明了FDA雷达在抗主瓣干扰时必须进行最优频率增量选取。     

MIMO广播系统中基于有限反馈的多用户选择新算法

在基于有限反馈多输入多输出(MIMO)广播系统的多用户选择研究中,目前已有的用户信噪干扰比(SINR)估计存在较大误差,这使得整个系统的性能受到制约。该文利用推导出的上下界来联合估计用户接收到的有用信号功率,得到了一种误差较小的SINR估计式,并基于该式给出了一种用户选择新算法。仿真结果表明,新的用户选择算法可以在低信噪比和高信噪比下同时达到较优性能,且复杂度较低。     

Novel SINR‐Based User Selection for an MU‐MIMO System with Limited Feedback

This paper presents a novel user selection method based on the signal‐to‐interference‐plus‐noise ratio (SINR), which is approximated using limited feedback data at the base stations (BSs) of multiple user multiple‐input multiple‐output (MU‐MIMO) systems. In the proposed system, the codebook vector index, the quantization error obtained from the correlation between the measured channel and the codebook vector, and the measured value of the largest singular value are fed back from each user to the BS. The proposed method not only generates precoding vectors that are orthogonal to the precoding vectors of the previously selected users and are highly correlated with the codebook vector of each user but also adopts the quantization error in approximating the SINR, which eventually provides a significantly more accurate SINR than the conventional SINR‐based user selection techniques. Computer simulations show that the proposed method enhances the sum rate of the conventional SINR‐based methods by at least 2.4 (2.62) bps/Hz when the number of transmit antennas and number of receive antennas per user terminal is 4 and 1(2), respectively, with 100 candidate users and an SNR of 30 dB.     

Power Allocation Algorithms for GMD or UCD Based Joint Transceiver Designs

In a downlink multiuser multiple-input multiple-output channel, joint transceiver designs based on geometric mean decomposition and uniform channel decomposition can provide a BER performance enhancement by making all substreams of each user have the same SINR. However, if a user power allocation (uPA) algorithm is not applied in their designs, they actually make the same SINR for all substreams in each user while causes different SINR with one another, and therefore the average BER is dominated by the user with the worst SINR. In this regards, it is possible to enhance BER performance further provided that the uPA algorithm is taken into account under a total power constraint. The objective of this paper is to maximize the worst user’s SINR by applying the uPA algorithm with the total power constraint. Because of proposed uPA algorithms, all substreams across all users can have the same SINR, which leads to minimization of average BER. Simulation results show that joint transceiver designs with proposed uPA algorithms have an SNR gain about 2 dB at the BER of \(10^{-3}\).     

SINR Driven Joint Network Selection Policy in the Heterogeneous Internet of Things

In the heterogeneous Internet of things (IoT), the Signal to interference plus noise ratio (SINR) and delay constraint are two important factors that influ-ence the throughput of IoT and the performance of users. Until recently, most network selection policy researches were based on either the Shannon theory or the signal strength, while the combined influence of the delay con-straint and the SINR, which has a significant impact on re-source utilization, is hardly considered. We therefore pro-pose an SINR driven joint network selection policy, which incorporates the delay constraint and the signal strength into the SINR. This policy permits IoT users to access the network with the maximum of SINR from all the available networks under the delay and signal strength constraints. Theoretical analysis and the simulation results show that the joint network selection policy can obtain the higher throughput of IoT and average SINR comparing with other polices.     

Performance evaluation of channel inversion precoding for downlink multi-user MIMO system

In downlink multi-user multi-input multi-output (MU-MIMO) system, not every user (user equipment (UE)) can calculate accurately signal to interference and noise ratio (SINR) without prior knowledge of the other users' precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of SINR and zero-forcing (ZF) algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding (AMC). As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output (SU-MIMO) at high signal-to-noise ratio (SNR) (>14 dB), due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.     

A preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks

This paper considers the co-channel interference mitigation problem and proposes a preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks. The proposed cross-tier handover algorithm introduces a preset threshold cross-tier handover policy, which takes into account both the time-to-stay (TTS) of a macrocell user equipment (MUE)/femtocell user equipment (FUE) in a femtocell/the macrocell, and the received signal to interference plus noise ratio (SINR) at a femtocell access point (FAP)/the macrocell base station (MBS) in making a cross-tier handover decision for an MUE/FUE. A cross-tier handover decision is made by comparing the TTS of an MUE/FUE in a femtocells/the macrocell and the SINR at a FAP/the MBS with a preset TTS threshold and different SINR thresholds. The objective of the preset threshold based cross-tier handover algorithm is to increase the received SINR at the MBS/FAPs and thus improve the network performance. The performance of the proposed cross-tier handover algorithm with the minimum power transmission and the optimal power transmission is analyzed, respectively. Numerical results show that the proposed preset threshold based cross-tier handover algorithm can significantly improve the network performance in terms of the outage probability, user sum rate, and network capacity.     

多用户毫米波MIMO系统中基于信道互易性的混合模数预编码算法

本文针对多用户毫米波多输入多输出(Multiple Input Multiple Output,MIMO)系统,首次提出了分离子阵列MIMO混合模数预编码架构毫米波系统的一种模拟接收方案。将最大化和速率求解混合模数预编码的三元联合优化问题分成模拟和数字两部分求解,进一步提出了基于信道互易性的混合模数预编码算法。该算法通过最大化下行各个用户和上行各个子阵列的接收信干噪比分别求解模拟合并矢量和模拟预编码矢量;优化模拟部分后,设计发射端数字预编码器消除多用户数据流之间的干扰。数值仿真表明所提算法收敛速度快,且可获得接近最优纯数字预编码算法的性能。      

Efficient cell selection algorithm in hierarchical cellular networks: multi-user coordination

In a hierarchical cellular network employing universal frequency reuse, the level of both intra- and intercell interference largely depends on the selection of a serving cell for the users in the overlapping area of multiple cells. We propose an efficient cell selection algorithm that is suitable for hierarchical cellular networks. In the proposed algorithm, uplink transmit power is used as a key parameter and cells are selected on the basis of the coordination of multiple users, rather than the choice of a single user. Simulation results show that the proposed algorithm improves performance with respect to the number of supportable users and the transmit power that each user needs in order to achieve a given target SINR.     

Multi-Dimensional Adaptive SINR Based Vertical Handoff for Heterogeneous Wireless Networks

Vertical handoff in next generation heterogeneous wireless networks is a multi-dimensional issue. In this article we propose a multi-dimensional adaptive SINR based vertical handoff algorithm (MASVH) which uses the combined effects of SINR, user required bandwidth, user traffic cost and utilization from participating access networks to make handoff decisions for multi-attribute QoS consideration. Simulation results confirm that the new MASVH algorithm improves the system performance in terms of higher throughput and lower dropping probability, as well as reduces the user traffic cost for accessing the integrated wireless networks.     

一种分布式多点协同波束成形和用户调度算法

为了高效实现多点协同下行链路的协同传输,该文基于最大化最小信干噪比准则提出了一种单层迭代分布式协同波束成形算法,并且证明了该算法的全局收敛性;利用该算法中优化波束的特征,进而提出了一种分布式协同用户调度算法。仿真结果表明,所提分布式协同波束成形和用户调度算法可获得明显优于已有算法的最小信干噪比性能,且只需要很少量的基站间信息交互。     

基于信干噪比的D2D通信功率控制与资源分配

为了优化长期演进(LTE)系统引入设备直传(D2D)通信后带来的同频干扰、系统边缘用户性能恶化问题,提出一种基于信干噪比(SINR)的多小区D2D通信资源分配方案,通过调整信干噪比阈值将部分蜂窝用户(CU)转化为D2D用户并释放频谱资源进而获得较佳的资源分配策略,同时提出一种基于小区间D2D竞争机制的配置算法有效降低小区间干扰.仿真表明,算法能够有效提升系统容量,并提升小区边缘D2D用户公平性.     

TD LTE-A系统下的中继规划技术

LTE-A通过使用中继技术达到提升小区边缘用户吞吐量、拓展小区覆盖和提升小区频谱效率等效果。文中针对中继在小区中配置和使用的问题,在TD LTE-A系统下提出了一种中继规划方案。结合中继位置选择和中继服务基站选择两种方法得到中继规划方法;考虑两跳中继场景下的链路信干燥比,并得到最优频率效率的中继选择算法;结合两者得到中继规划方案并进行仿真。仿真结果显示,采用了中继规划方案的回溯链路的信干燥比得到平均约2 dB的提升,且使小区吞吐量提升了约13%。     

SINR loss and user selection in massive MU‐MISO systems with ZFBF

Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple‐input multiple‐output (MU‐MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal‐to‐interference‐plus‐noise ratio (SINR) loss to characterize it in multiuser multiple‐input single‐output (MU‐MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU‐MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU‐MISO systems.     

Adaptive power control and beam-forming joint optimization in cognitive radio networks

A novel adaptive power control and beam-forming joint optimization algorithm is proposed in cognitive radio(CR) underlay networks,where cognitive network share spectrum with primary network which spectrum is licensed.In this paper,both primary base station(PBS) and cognitive base station(CBS) are all equipped with multi antennas,while each primary user(PU) and cognitive user(CU) has only one antenna.Different from traditional algorithms,an adaptive weight factor generating solution is supplied to different access users(both PUs and CUs) in this paper,and the different priority of users is also considered,because PUs have higher priority,the weight factor of PUs is fixed as constant and signal-to-interference and noise ratio(SINR) threshold is unchanged,while for CUs,it is set adaptively and SINR threshold is also changed accordingly.Using this algorithm,the transmit power is decreased,which relax the strict requirements for power amplifier in communication systems.And moreover,owing to PUS has fixed SINR threshold,the calculated SINR at receiver is nearly unchanged,but for CUs,the SINR is changing with the adaptive weight factor.Under the assurance of quality of service(QoS) of PUs,the solution in this paper can enable CRs access to the CR network according to adaptive SINR threshold,therefore which supplies higher spectrum utilization efficiency.     

Low-complexity joint beamforming and power allocation for SINR balancing in cognitive radio networks

We consider the Signal-to-Interference plus Noise Ratio (SINR) balancing problem involving joint beamfoming and power allocation in the Cognitive Radio (CR) network, wherein the Single-Input Multi-Output Multiple Access Channels (SIMO-MAC) are assumed. Subject to two sets of constraints: the interference temperature constraints of Primary Users (PUs) and the peak power constraints of Cognitive Users (CUs), a low-complexity joint beamforming and power allocation algorithm called Semi-Decoupled Multi-Constraint Power Allocation with Constraints Preselection (SDMCPA-CP) for SINR balancing is proposed. Compared with the existing algorithm, the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigen decompositions significantly, especially when large numbers of PUs and CUs are active, while still providing the optimal balanced SINR level for all the CUs.     

Ergodic capacity analysis for SIMO cognitive fading channel in spectrum sharing environment

We consider the Signal-to-Interference plus Noise Ratio (SINR) balancing problem involving joint beamfoming and power allocation in the Cognitive Radio (CR) network, wherein the Single-Input Multi-Output Multiple Access Channels (SIMO-MAC) are assumed. Subject to two sets of constraints: the interference temperature constraints of Primary Users (PUs) and the peak power constraints of Cognitive Users (CUs), a low-complexity joint beamforming and power allocation algorithm called Semi-Decoupled Multi-Constraint Power Allocation with Constraints Preselection (SDMCPA-CP) for SINR balancing is proposed. Compared with the existing algorithm, the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigen decompositions significantly, especially when large numbers of PUs and CUs are active, while still providing the optimal balanced SINR level for all the CUs.     

一种新的认知无线电功率分配算法（英文）

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.