Impact of channel estimation error on channel capacity of multiple input multiple output system

In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output (MIMO) system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to-noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.

Channel capacity of multiple-input multiple-output systems with transmit and receive correlation

In order to investigate the impact of channel model parameters on the channel capacity of a multipleinput multiple-output （MIMO） system, a novel method is proposed to explore the channel capacity under Rayleigh fiat fading with correlated transmit and receive antennas. The optimal transmitting direction which can achieve maximum channel capacity is derived using random matrices theory. In addition, the closed-form expression for the channel capacity of MIMO systems is given by utilizing the properties of Wishart distribution when SNR is high. Computer simulation results show that the channel capacity is maximized when the antenna spacing increases to a certain point, and furthermore, the larger the scattering angle is, the more quickly the channel capacity converges to its maximum. At high SNR （〉12 dB）, the estimation of capacity is close to its true wlue. And, when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher channel capacity than ULA.

Performance analysis on channel capacity in cooperative MIMO system

Recent years, cooperative technology has taken a lot of attention since it can improve the bit error rate （BER） and lower the transmit power in radio mobile networks, especially when the direct channel between the source and the destination is poor. Cooperative multiple input multiple output （Co-lVlIMO） is a kind of MI- MO technique, where the multiple inputs and outputs are formed via cooperation. The capacity of Co-MIMO system over wireless channel has been investigated a lot, however few papers pay attention to the locations of the channel that may affect the probability distributions of the variable and the effect of antenna spatial correlation. The results can be achieved by choosing sub-channels that is not related to other sub-channels. This paper focu- ses on this problem. The simulation results show that once we search the partner we should consider trade offs cooperation get optimum system performance. It further investigates that cooperation between different terminals can reduce antenna spatial correlation, thereby increase the capacity and throughput of the system, and even reach the ideal capacity of MIMO system.

Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

The lattice-reduction （LR） has been developed to im- prove the performance of the zero-forcing （ZF） precoder in multiple input multiple output （MIMO） systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter （CSIT）, an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex Lenstra- Lenstra-Lov^sz （LLL） algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error （LMMSE） pre- coder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate （BER）. Assuming a time division duplexing （TDD） MIMO system, correlated block flat fad- ing channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying （QPSK） modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when Eb-No is greater than 10 dB and 12 dB at all correlation coefficients.

Analytical Investigation of Channel Capacity of UWB-MIMO Systems

Ultra-wide-band (UWB) technology combined with multiple input and multiple output (MIMO) provides a viable solution for achieving high data transmission rates of more than 1 Gb/s in wireless communications. UWB is typically applied to short-range indoor environments and is therefore characterized by dense multipath propagation. In this type of environment, MIMO systems allow for a substantial improvement in the spectral efficiency by exploiting the inherent array gain and spatial multiplexing gain of UWB systems. This paper investigates the channel capacity of UWB-MIMO wireless technology and shows that UWB and MIMO designs improve the spectral efficiency logarithmically and linearly, respectively.

Statistical-mechanical analysis of multiuser channel capacity with imperfect channel state information

In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.

Channel Capacity Optimization Based on Riemannian Trust Region Algorithm in IRS-Aided Communication System

Intelligent Reflecting Surface (IRS) can offer unprecedented channel capacity gains since it can reconfigure the signal propagation environment. We decide to maximize the channel capacity by jointly optimizing the transmit-power-constrained precoding matrix at the base station and the unit-modulus-constrained phase shift vector at the IRS in IRS-assisted multi-user downlink communication. We first convert the resulting non-convex problem into an equivalent problem, then use the alternate optimization algorithm. While fixing the phase shift vector, we can obtain the optimal precoding matrix directly by adopting standard optimization packages. While fixing the precoding matrix, we propose the Riemannian Trust-Region (RTR) algorithm to solve this optimization problem. And the key of the RTR algorithm is the solution of the trust-region sub-problem. We first adopt the accurate solution based on Newton's (ASNT) method to solve this sub-problem, which can obtain the global solution but cannot guarantee that the solution is optimal since the initial iteration point is difficult to choose. Then, we propose the Improved-Polyline (IPL) method, which can avoid the difficulty of the ASNT method and improve convergence speed and calculation efficiency. The numerical results show that the RTR algorithm has more significant performance gains and faster convergence speed compared with the existing approaches.

A Correlation-Based Stochastic Model for Massive MIMO Channel

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.

Investigation into the Performance of a MIMO System Equipped with ULA or UCA Antennas: BER, Capacity and Channel Estimation

This paper reports on investigations into the performance of a Multiple Input Multiple Output (MIMO) wireless communication system employing a uniform linear array (ULA) at the transmitter and either a uni-form linear array (ULA) or a uniform circular array (UCA) antenna at the receiver. The transmitter is as-sumed to be surrounded by scattering objects while the receiver is postulated to be free from scattering ob-jects. The Laplacian distribution of angle of arrival (AOA) of a signal reaching the receiver is postulated. The performance of bit error rate (BER), capacity and channel estimation for a MIMO system are evaluated for the two cases that the receiver is equipped with ULA or with UCA antennas.

Achievable Rate Regions for Orthogonally Multiplexed MIMO Broadcast Channels with Multi-Dimensional Modulation

In this work, we consider a multi-antenna channel with orthogonally multiplexed non-cooperative users, and present its achievable information rate regions with and without channel knowledge at the transmitter. With an informed transmitter, we maximize the rate for each user. With an uninformed transmitter, we consider the optimal power allocation that causes the fastest convergence to zero of the fraction of channels whose mutual information is less than any given rate as the transmitter channel knowledge converges to zero. We assume a deterministic space and time dispersive multipath channel with multiple transmit and receive antennas, generating an orthogonally multiplexed Multiple-Input Multiple-Output (MIMO) broadcast system. Under limited transmit power;we consider different user specific space-time modulation formats that represent assignments of signal dimensions to transmit antennas. For the two-user orthogonally multiplexed MIMO broadcast channels, the achievable rate regions, with and without transmitter channel knowledge, evolve from a triangular region at low SNR to a rectangular region at high SNR. We also investigate the maximum sum rate for these regions and derive the associated power allocations at low and high SNR. Furthermore, we present numerical results for a two-user system that illustrate the effects of channel knowledge at the transmitter, the multi-dimensional space-time modulation format and features of the multipath channel.

On the Capacity of CPM MIMO Systems over Band-Limited Channels

Capacity analysis is a fundamental and important issue for continuous phase modulation (CPM) signals. In the letter, we investigate the capacity formula of CPM MIMO systems. Using Finite State Machine (FSM), the CPM symbols can be modeled as Markov source by combining channel and CPM modulation. Thus the capacity of CPM signals can be derived in form of the erroneous probability and normalized CPM bandwidth. In addition, the capacity of CPM MIMO systems is derived over Gaussian channels and Rayleigh channels. Finally, numerical simulations are implemented according to various parameters such as modulation scheme, modulation index h, memory length L, and antenna configuration.

ERGODIC CAPACITY FORMULA OF MIMO-OFDM SYSTEMS UNDER CORRELATED FREQUENCY SELECTIVE RAYLEIGH FADING CHANNELS

An explicit formula for the ergodic capacity of Orthogonal Frequency Division Multiplexing (OFDM)-based Multiple-Input Multiple-Output (MIMO) systems under correlated frequency selective Rayleigh channels is derived,by simplifying the channel response matrix in frequency domain into the so-called Kronecker model composed of three kinds of correlations,i.e.multipath tap gain correlation and spatial fading correlations at both transmitter and receiver.The derived formula is very simple and convenient for one to estimate the effects of all three kinds of correlations on MIMO-OFDM capacity.If taps are independent,there is a very simple expression for the ergodic capacity.In case of tap correlation,the capacity formula could be further given in an integral expression.The validity of the new formula is verified and the effects of correlations,delay spread as well as the number of subcarriers on the ergodic capacity are evaluated via Monte Carlo simulations.

Channel Capacity Estimation in TDMS-Based MIMO Measurements

Time-division multiplexed switching （TDMS）-based multiple-input multiple-output （MIMO） channel sounders are widely used for wireless channel measurements due to their effective costs. However, meas- urement noise such as phase noise in the local oscillators as well as additive white Gaussian noise （AWGN） can result in significant errors in channel capacity estimates. This study analyzes the impact of phase noise and AWGN on channel capacity in TDMS-based MIMO measurements, with a channel capacity estimator presented that reduces the impact of noise on both the spatial multiplexing gain and on the power gain. Simulations demonstrate that the estimator consistently obtains the true capacity for various MIMO channel scenarios, even if only a limited number of observations are available.

低复杂度的大规模MIMO分布式信道估计

针对大规模多输入多输出(multiple-input multiple-output,MIMO)系统传统信道矩阵获取方式导频开销大、计算复杂度高的问题,提出了一种低复杂度的二阶段分布式信道估计方案。该方案的初始阶段在基站侧采用传统压缩感知算法恢复信道矩阵,第2阶段在用户端利用信道的时间相关性,将大规模MIMO的角度域信道分解为密集部分和稀疏部分,并分别估计以实现连续信道追踪。稀疏部分信道通过所提的分布式自适应弱匹配追踪(distributed adaptive weak matching pursuit,DAWMP)算法,利用子信道的联合稀疏性进行多维重建。相比于线性最小均方误差(linear minimum mean square error,LMMSE)算法,所提方案的信道分解策略有效减少了在用户端进行信道估计的计算复杂度。仿真结果表明,所提算法与经典压缩感知信道估计算法相比,计算复杂度降低了约33%,算法性能提升了约0.5 dB。

Power optimization for maximum channel capacity in MIMO relay system

Introducing multiple-input multiple-output（MIMO） relay channel could offer significant capacity gain. And it is of great importance to develop effective power allocation strategies to achieve power efficiency and improve channel capacity in amplify-and-forward relay system. This article investigates a two-hop MIMO relay system with multiple antennas in relay node （RN） and receiver （RX）. Maximizing capacity with antenna selection（MCAS） and maximizing capacity with eigen-decomposition （MCED） schemes are proposed to efficiently allocate power among antennas in RN under first and second hop limited scenarios. The analysis and simulation results show that both MCED and MCAS can improve the channel capacity compared with uniform power allocation （UPA） scheme in most of the studied areas. The MCAS bears comparison with MCED with an acceptable capacity loss, but lowers the complexity by saving channel state information （CSI） feedback to the transmitter （TX）. Moreover, when the RN is close to RX, the performance of UPA is also close to the upper bound as the performance of first hop is limited.

Spatial Coded Modulation:Coding over Antennas

In spatial modulation systems,the reliability of the active antenna detection is of vital importance since the modulated symbols tend to be correctly demodulated when the active antennas are accurately identified.In this paper,we propose a spatial coded modulation(SCM)scheme,which improves the accuracy of the active antenna detection by coding over the transmit antennas.Specifically,the antenna activation pattern in the SCM corresponds to a codeword in a properly designed codebook with a larger minimum Hamming distance than the conventional spatial modulation.As the minimum Hamming distance increases,the reliability of the active antenna detection is directly enhanced,which yields a better system reliability.In addition to the reliability,the proposed SCM scheme also achieves a higher capacity with the identical antenna configuration compared to the conventional counterpart.The optimal maximum likelihood detector is first formulated.Then,a low-complexity suboptimal detector is proposed to reduce the computational complexity.Theoretical derivations of the channel capacity and the bit error rate are presented in various channel scenarios.Further derivation on performance bounding is also provided to reveal the insight of the benefit of increasing the minimum Hamming distance.Numerical results validate the analysis and demonstrate that the proposed SCM outperforms the conventional spatial modulation techniques in both channel capacity and system reliability.

基于改进广义正交匹配追踪的低地球轨道卫星MIMO-OTFS系统的信道估计方法

针对基于多输入多输出(MIMO)技术和正交时频空间(OTFS)调制的低地球轨道卫星系统的复杂性带来的信道估计困难问题,提出一种基于改进广义正交匹配追踪(GOMP)的信道估计方法。根据单输入单输出(SISO)-OTFS系统的输入输出关系和低地球轨道卫星信道的传播特性,建立一种基于MIMO-OTFS的低地球轨道卫星信道模型,并将系统的信道估计问题转化为稀疏信号的恢复问题。考虑到传统的GOMP算法存在对稀疏度的过度依赖和对稀疏信号的重构精度差等问题,所提方法结合了分段弱正交匹配追踪(SWOMP)的弱选择思想和广义Jaccard系数的相似性准则,以快速准确地重建稀疏信号。仿真结果表明,当天线数为16且导频开销比为0.5时,与正交匹配追踪(OMP)算法相比,所提方法的归一化均方误差(NMSE)降低了约2.5 dB,误码率(BER)降低了约5 dB。

Capacity and Spatial Correlation Measurements of Compact MIMO Antennas

The dual-port compact multiple-input multiple-output(MIMO)dipole antennas with close spacing d of 0.5λand 0.3λare designed,and some electromagnetic band gap(EBG)structures are inserted between them to reduce mutual coupling.Those MIMO antennas with d=0.5λand 0.3λ,and with different mutual couplings are fabricated and measured,the channel capacity and correlation coefficient(CC)are analyzed and compared in a rich multipath reverberation chamber(RC),an office and a conference room.Results show that if d is reduced from 0.5λto 0.3λ,in the RCs,channel capacities of all the antennas are very close to that of the i.i.d.Rayleigh channel,although the average CCs are increased from 0.168 in the nonlossy RC to 0.269 in the lossy RC.In the office and conference rooms,compared with the RC,the average capacities of those antennas get a slight reduction,however,in most cases,the capacity of d=0.5λis larger than that of d=0.3λ,and the antennas with EBG have a larger capacity compared with the antennas without EBG,with a corresponding reduction of CC.A non-line-of-sight(NLOS)scenario of through-the-wall is also investigated.

基于莱斯信道的大规模MIMO协作中继网络设计与优化

随着移动通信技术的不断发展,大规模多输入多输出(Multiple Input Multiple Output,MIMO)系统被广泛应用于提高网络容量和性能。而协作中继网络作为一种有效提高通信覆盖能力和网络容量的手段,也受到越来越多的关注。文章基于莱斯信道模型,针对大规模MIMO协作中继网络进行设计与优化,旨在提升网络的可靠性和传输效率。通过对信道特性的分析和系统参数的优化,可以实现更好的性能表现。

On Dynamic Channel Emulation in Sector MPAC for Over-the-Air Testing of Beamformed Massive MIMO Devices

In this article,novel emulation strategies for the sectored multiple probe anechoic chamber(SMPAC)are proposed to enable the reliable evaluation of the massive multiple-input multiple-output(MIMO)device operating at beamforming mode,which requires a realistic non-stationary channel environment.For the dynamic propagation emulation,an efficient closed-form probe weighting strategy minimizing the power angular spectrum(PAS)emulation errors is derived,substantially reducing the associated computational complexity.On the other hand,a novel probe selection algorithm is proposed to reproduce a more accurate fading environment.Various standard channel models and setup configurations are comprehensively simulated to validate the capacity of the proposed methods.The simulation results show that more competent active probes are selected with the proposed method compared to the conventional algorithms.Furthermore,the derived closedform probe weighting strategy offers identical accuracy to that obtained with complicated numerical optimization.Moreover,a realistic dynamic channel measured in an indoor environment is reconstructed with the developed methodologies,and 95.6%PAS similarity can be achieved with 6 active probes.The satisfactory results demonstrate that the proposed algorithms are suitable for arbitrary channel emulation.