Optimizing Zero-Forcing Precoders for MIMO Broadcast Systems

In this paper, we develop optimization techniques for linear zero-forcing (ZF) multiple-input, multiple-output (MIMO) broadcast (BC) precoders. A computationally efficient technique based on QR-update algorithms for implementing this optimization is then proposed. The application of the proposed ZF precoders and decoders to systems with both large and small numbers of users is considered. The proposed optimization technique is also shown to perform very well in conjunction with nonlinear Tomlinson--Harashima precoding. Both coded and uncoded performances are considered.     

MIMO系统中基于ZF/MMSE检测的自适应功率分配方案

 本文研究了MIMO系统中的功率分配技术.针对基于ZF/MMSE检测的MIMO系统,提出了一种简单的自适应功率分配方案.该方案在不使用预编码技术对MIMO信道进行对角化的前提下,遵循最小化系统BER的准则,为发送数据流分配发射功率.与采用SVD预编码的功率分配方案相比,本文提出的方法减少了系统需要的反馈信息量.仿真表明该方法能够有效地提高系统的BER性能,而且基于MMSE检测的系统性能接近于采用SVD预编码的功率分配性能.     

多用户MIMO下行链路中线性预编码器和译码器的联合优化

文章研究多用户MIMO下行链路中线性预编码器和译码器的联合优化问题。采用的优化准则是在总发射功率约束下最小化系统的和均方误差（Sum MSE,SMSE）,提出了一种启发式的迭代算法。通过在接收端引入相同的自动增益控制因子,该算法对预编码器和译码器进行交替优化,直到SMSE达到最小值。分析和仿真结果表明：该算法具有较低的复杂度和良好的收敛特性,符号差错率也优于现有算法。     

Code Design for MIMO Broadcast Channels

Recent information-theoretic results show the optimality of dirty-paper coding (DPC) in achieving the full capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This paper presents a DPC based code design for BCs. We consider the case in which there is an individual rate/signal-to-interference-plus-noise ratio (SINR) constraint for each user. For a fixed transmitter power, we choose the linear transmit precoding matrix such that the SINRs at users are uniformly maximized, thus ensuring the best bit-error rate performance. We start with Cover's simplest two-user Gaussian BC and present a coding scheme that operates 1.44 dB from the boundary of the capacity region at the rate of one bit per real sample (b/s) for each user. We then extend the coding strategy to a two-user MIMO Gaussian BC with two transmit antennas at the base-station and develop the first limit-approaching code design using nested turbo codes for DPC. At the rate of 1 b/s for each user, our design operates 1.48 dB from the capacity region boundary. We also consider the performance of our scheme over a slow fading BC. For two transmit antennas, simulation results indicate a performance loss of only 1.4 dB, 1.64 dB and 1.99 dB from the theoretical limit in terms of the total transmission power for the two, three and four user case, respectively.     

MIMO系统中ZF算法实现

MIMO技术中一个关键的方面是接收机的接收算法,本文主要描述了ZF求伪逆解MIMO算法的定点化实现过程,仿真实验结果表明,定点化链路的性能非常接近浮点链路的性能。     

Massive MIMO广播波束场景化研究

Massive MIMO和波束赋形是5G的一项关键技术。5G将LTE时期的MIMO进行了扩展和延伸,即LTE的MIMO最多8天线,到5G扩增为16/32/64/128天线,被称为“大规模”的MIMO。本案通过对不同场景Massive MIMO波束调整方案进行研究,输出场景化的设置方案,以期为后期Massive MIMO优化提供参考。     

On the User Selection for MIMO Broadcast Channels

In this paper, a downlink communication system, in which a base station (BS) equipped with $M$ antennas communicates with $N$ users each equipped with $K$ receive antennas, is considered. An efficient suboptimum algorithm is proposed for selecting a set of users in order to maximize the sum–rate throughput of the system, in a Rayleigh-fading environment. For the asymptotic case when $N$ tends to infinity, the necessary and sufficient conditions in order to achieve the maximum sum–rate throughput, such that the difference between the achievable sum–rate and the maximum value approaches zero, is derived. The complexity of our algorithm is investigated in terms of the required amount of feedback from the users to the BS, as well as the number of searches required for selecting the users. It is shown that the proposed method is capable of achieving a large portion of the sum–rate capacity, with a very low complexity.      

Dirty-paper coding versus TDMA for MIMO Broadcast channels

We compare the capacity of dirty-paper coding (DPC) to that of time-division multiple access (TDMA) for a multiple-antenna (multiple-input multiple-output (MIMO)) Gaussian broadcast channel (BC). We find that the sum-rate capacity (achievable using DPC) of the multiple-antenna BC is at most min(M,K) times the largest single-user capacity (i.e., the TDMA sum-rate) in the system, where M is the number of transmit antennas and K is the number of receivers. This result is independent of the number of receive antennas and the channel gain matrix, and is valid at all signal-to-noise ratios (SNRs). We investigate the tightness of this bound in a time-varying channel (assuming perfect channel knowledge at receivers and transmitters) where the channel experiences uncorrelated Rayleigh fading and in some situations we find that the dirty paper gain is upper-bounded by the ratio of transmit-to-receive antennas. We also show that min(M,K) upper-bounds the sum-rate gain of successive decoding over TDMA for the uplink channel, where M is the number of receive antennas at the base station and K is the number of transmitters.     

MIMO Broadcast Channels With Finite-Rate Feedback

Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e., multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this correspondence, a system where each receiver has perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well-known zero-forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite-rate feedback are derived. A key finding is that the feedback rate per mobile must be increased linearly with the signal-to-noise ratio (SNR) (in decibels) in order to achieve the full multiplexing gain. This is in sharp contrast to point-to-point multiple-input multiple-output (MIMO) systems, in which it is not necessary to increase the feedback rate as a function of the SNR     

MIMO Broadcast Scheduling with Limited Feedback

We consider multiuser scheduling with limited feedback of partial channel state information in MIMO broadcast channels. By using spatial multiplexing at the base station (BS) and antenna selection for each user, we propose a multiuser scheduling method that allocates independent information streams from all M transmit antennas to the M most favorable users with the highest signal-to-interference-plus-noise ratio (SINR). A close approximation of the achievable sum-rate throughput for the proposed method is obtained and shown to match the simulation results very well. Moreover, two reduced feedback scheduling approaches are proposed. In the first approach, which we shall refer to as selected feedback scheduling, the users are selected based on their SINR compared to a predesigned threshold. Only those selected users are allowed to feed back limited information to the BS. The resultant feedback load and achievable throughput are derived. It will then be demonstrated that with a proper choice of the threshold, the feedback load can be greatly reduced with a negligible performance loss. The second reduced feedback scheduling approach employs quantization for each user, in which only few bits of quantized SINR are fed back to the BS. Performance analysis will show that even with only 1-bit quantization, the proposed quantized feedback scheduling approach can exploit the multiuser diversity at the expense of slight decrease of throughput.     

Fundamental Limits in MIMO Broadcast Channels

This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system parameters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling.     

Analysis of Energy Efficiency and Area Throughput in Large Scale MIMO Systems with MRT and ZF Precoding

The large-scale multiple input multiple output (LS-MIMO) systems are equipped with a large number of antennas at the base station. These systems are capable of serving a larger number of user terminals, with massive gains in the form of energy and bandwidth efficiency. The energy efficiency of LS-MIMO system depends on the overall power consumption and data rate. In this paper, we have improved the energy efficiency of the LS-MIMO system by using maximum ratio transmission/combining and zero forced linear pre-coding schemes in single and multi-cell scenarios. We have jointly considered the uplink and downlink communications to propose an improved, more practical and more realistic power consumption model. The proposed model deliberates the power required for the power amplifier, linear processing and the circuit components at the base stations and user terminals. The outcome of this work provides a significant improvement in terms of energy efficiency and area throughput. The analytical results illustrate that the LS-MIMO systems achieve the maximum energy efficiency and area throughput wherein larger number of transmit antennas are installed at the base station to serve comparatively greater number of users terminals. The mathematical results depict the similar performance for imperfect channel state information in multi-cell setups. All aspects of power consumption during bidirectional communication are considered to provide precise results. Hence, the improvements in simulations results support the accuracy of the proposed model.     

珠海电视台高清频道播出系统设计与应用

在全球高清大背景下,珠海电视台前瞻性规划,新建两套高清播出系统,主要介绍新改造的珠海电视台高清频道和标清频道的现状,一些重要硬件设备的选型和主要技术指标、型号、规格和参数,以及一些软硬件需要注意的问题。     

Performance Comparison of Linear Precoders for TDD Large Scale MIMO System with Imperfect Reciprocity and Channel Estimations

Wireless Personal Communications - Channel estimation is an essential component, in which channel state information playing very important role in wireless communications. But acquiring CSI in...     

Performance analysis of ZF receivers with imperfect CSI for uplink massive MIMO systems

We consider the uplink of massive multiple-input multiple-output systems in a multicell environment. Since the base station (BS) estimates the channel state information (CSI) using the pilot signals transmitted from the users, each BS will have imperfect CSI in practice. Assuming zero-forcing method to eliminate the multi-user interference, we derive the exact analytical expressions for the probability density function of the signal-to-interference-plus-noise ratio, the corresponding achievable rate, the outage probability, and the symbol error rate (SER) when the BS has imperfect CSI. An upper bound of the SER is also derived for an arbitrary number of antennas at the BS. Moreover, we derive the upper bound of the achievable rate for the case where the number of antennas at the BS goes to infinity, and the analysis is verified by presenting numerical results.     

Low Complexity Antenna Selection Scheme for Multicarrier MIMO Broadcast Communication

A low complexity antenna selection scheme for multicarrier MIMO (Multiple Input Multiple Output) broadcast systems is proposed in this paper. Under special condition of single user in the system or when the number of subcarrier is only one, the system reduces to conventional MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system or MIMO-BC (Broadcast Channel) system respectively. By analysing sub-optimal antenna selection schemes developed earlier for single user MIMO-OFDM systems and single carrier MIMO-BC systems, one can see many similarities which can be extended to multicarrier MIMO broadcast systems. The proposed method exploits these similarities to obtain a low complexity system design with acceptable performance. The performance of the proposed scheme is studied via extensive simulation, and the computational complexity involved is compared to the conventional scheme. A selection gain of approximately 0.5 b/s/Hz is shown to be achievable using only two out of three antennas, and the proposed scheme is able to achieve up to 90% of the gain. This is achieved at a complexity that is significantly lower than the conventional methods, hence the practical implementation of the proposed scheme can be justified.     

Practical Vector Dirty Paper Coding for MIMO Gaussian Broadcast Channels

Recently, the vector dirty paper coding (DPC) achievable rate region has been shown to be the capacity region of a multiple-input multiple-output Gaussian broadcast channel (MIMO GBC). With DPC, the multiuser interference noncausally known at the transmitter can be completely removed. In this paper, we present a vector DPC structure for MIMO GBC. It is a generalization of the single antenna superposition dirty paper coding for the scalar Gaussian dirty paper problem proposed by Bennatan et al. In a theoretical random code setting, this construction is shown to be able to achieve the promised rate performance of the MIMO GBC. We also implement it with existing vector quantizer and capacity-achieving channel coding. Combined with iterative decoding, a design example validates the effectiveness of our methods.     

用于MIMO广播信道的带多波束选择的正交随机波束成形算法

本文提出一种基于有限反馈的波束和用户选择方案,在这种方案中,用户端利用一个随机正交码本对其信道方向信息(CDI)进行量化,计算其最大信号与干扰加噪声功率比(SINR),并把这些信息反馈给基站;基站根据接收到的这些反馈信息,按照和容量最大的准则选择出多个正交波束以及相应的多个用户.和sharif等人最近提出的方案相比,我们提出的方案能根据系统参数,如用户数和信噪比(SNR),对选择的波束成形矢量及其对应的用户的数量和集合进行调整,当用户数量较小时,和容量性能得到了很大的提升,同时避免了选择波束成形矢量时的用户冲突,另外,基站也不需要广播波束成形矢量给各个用户.     

Performance evaluation and implementation complexity analysis framework for ZF based linear massive MIMO detection

Wireless Networks - This paper discusses a framework for algorithm-architecture synergy for (1) performance evaluation and (2) FPGA implementation complexity analysis of linear massive MIMO...