Capacity of multiple-antenna systems with both receiver and transmitter channel state information

The capacity of multiple-antenna systems operating in Rayleigh flat fading is considered under the assumptions that channel state information (CSI) is available at both transmitter and receiver, and that the transmitter is subjected to an average power constraint. First, the capacity of such systems is derived for the special case of multiple transmit antennas and a single receive antenna. The optimal power-allocation scheme for such a system is shown to be a water-filling algorithm, and the corresponding capacity is seen to be the same as that of a system having multiple receive antennas (with a single transmitter antenna) whose outputs are combined via maximal ratio combining. A suboptimal adaptive transmission technique that transmits only over the antenna having the best channel is also proposed for this special case. It is shown that the capacity of such a system under the proposed suboptimal adaptive transmission scheme is the same as the capacity of a system having multiple receiver antennas (with a single transmitter antenna) combined via selection combining. Next, the capacity of a general system of multiple transmitter and receiver antennas is derived together with an equation that determines the cutoff value for such a system. The optimal power allocation scheme for such a multiple-antenna system is given by a matrix water-filling algorithm. In order to eliminate the need for cumbersome numerical techniques in solving the cutoff equation, approximate expressions for the cutoff transmission value are also provided. It is shown that, compared to the case in which there is only receiver CSI, large capacity gains are available with optimal power and rate adaptation schemes. The increased capacity is shown to come at the price of channel outage, and bounds are derived for this outage probability.     

Linear and nonlinear preequalization/equalization for MIMO systems with long-term channel state information at the transmitter

A transceiver structure for frequency-flat multiple-input multiple-output (MIMO) systems that comprises linear/nonlinear preequalization/equalization is optimized according to the minimum mean square error (MMSE) criterion under the assumption that only long-term channel state information (i.e., correlation matrices of fading channel and noise) is available at the transmitter. The structure generalizes different techniques known from the literature, such as BLAST, linear preequalization and equalization, and Tomlinson-Harashima precoding (THP). Simulations show that relevant benefits can be obtained by exploiting the long term channel state information at the transmitter in both dense multipath channels with relatively large correlation at the transmitter side and in sparse multipath channels.     

Capacity of fading channels with channel side information

We obtain the Shannon capacity of a fading channel with channel side information at the transmitter and receiver, and at the receiver alone. The optimal power adaptation in the former case is “water-pouring” in time, analogous to water-pouring in frequency for time-invariant frequency-selective fading channels. Inverting the channel results in a large capacity penalty in severe fading     

Capacity bounds and estimates for the finite scatterers MIMO wireless channel

We consider the limits to the capacity of the multiple-input-multiple-output wireless channel as modeled by the finite scatterers channel model, a generic model of the multipath channel which accounts for each individual multipath component. We assume a normalization that allows for the array gain due to multiple receive antenna elements and, hence, can obtain meaningful limits as the number of elements tends to infinity. We show that the capacity is upper bounded by the capacity of an identity channel of dimension equal to the number of scatterers. Because this bound is not very tight, we also determine an estimate of the capacity as the number of transmit/receive elements tends to infinity which is asymptotically accurate.     

Capacity of memoryless channels and block-fading channels with designable cardinality-constrained channel state feedback

A coding theorem is proved for memoryless channels when the channel state feedback of finite cardinality can be designed. Channel state information is estimated at the receiver and a function of the estimated channel state is causally fed back to the transmitter. The feedback link is assumed to be noiseless with a finite feedback alphabet, or equivalently, finite feedback rate. It is shown that the capacity can be achieved with a memoryless deterministic feedback and with a memoryless device which select transmitted symbols from a codeword of expanded alphabet according to current feedback. To characterize the capacity, we investigate the optimization of transmission and channel state feedback strategies. The optimization is performed for both channel capacity and error exponents. We show that the design of the optimal feedback scheme is identical to the design of scalar quantizer with modified distortion measures. We illustrate the optimization using Rayleigh block-fading channels. It is shown that the optimal transmission strategy has a general form of temporal water-filling in important cases. Furthermore, while feedback enhances the forward channel capacity more effectively in low-signal-to noise ratio (SNR) region compared with that of high-SNR region, the enhancement in error exponent is significant in both high- and low-SNR regions. This indicates that significant gain due to finite-rate channel state feedback is expected in practical systems in both SNR regions.     

On the capacity of some channels with channel state information

We study the capacity of some channels whose conditional output probability distribution depends on a state process independent of the channel input and where channel state information (CSI) signals are available both at the transmitter (CSIT) and at the receiver (CSIR). When the channel state and the CSI signals are jointly independent and identically distributed (i.i.d.), the channel reduces to a case studied by Shannon (1958). In this case, we show that when the CSIT is a deterministic function of the CSIR, optimal coding is particularly simple. When the state process has memory, we provide a general capacity formula and we give some more restrictive conditions under which the capacity has still a simple single-letter characterization, allowing simple optimal coding. Finally, we turn to the additive white Gaussian noise (AWGN) channel with fading and we provide a generalization of some results about capacity with CSI for this channel. In particular, we show that variable-rate coding (or multiplexing of several codebooks) is not needed to achieve capacity and, even when the CSIT is not perfect, the capacity achieving power allocation is of the waferfilling type     

Simplified transmitter design for MIMO systems with channel uncertainty

This article investigates transmitter design in Rayleigh fading multiple input multiple output (MIMO) channels with spatial correlation when there are channel uncertainties caused by a combined effect of channel estimation error and limited feedback. To overcome the high computational complexity of the optimal transmit power allocation, a simple and suboptimal allocation is proposed by exploiting the transmission constraint and differentiating a bound based on Jensen inequality on the channel capacity. The simulation results show that the mutual information corresponding to the proposed power allocation closely approaches the channel capacity corresponding to the optimal one and meanwhile the computational complexity is greatly reduced.     

MIMO中继系统中基于不完全信道信息的线性预编码算法

针对采用放大转发中继技术的多输入多输出系统,提出一种基于不完全信道状态信息的中继预编码设计方案.假设在中继端已知源-中继的全部信道状态信息,在中继-目的端的信道考虑信道估计误差及发射天线相关性,根据最小均方误差设计准则,推导获得目的端线性处理矩阵.在中继端最大发射功率约束条件下,通过理论推导求得中继端线性预编码矩阵的闭式解.数值仿真结果表明,在存在信道估计误差和天线相关性的条件下,所提方案能有效降低系统的误比特率和均方误差.     

Capacity of correlated MIMO Rayleigh channels

Abstract-This paper presents some exact results on the capacity of multiple-input-multiple-output (MIMO) channels subject to correlated Rayleigh fading when perfect channel state information (CSI) is known at the receiver. The authors focus on the semicorrelated scenario in which correlation exists either at the transmitter or at the receiver., They consider two cases: 1) the transmitter does not have any CSI and as such allocates power equally among transmitter antennas and 2) the transmitter only knows the statistical distribution of the channel. The first case derives the moment generating function (MGF) of the mutual information (MI) and then deduces from this MGF the mean MI. The authors also study the cumulative distribution function (CDF) of the MI, which can serve as an upper bound to the outage probability under the capacity versus outage formulation when the channel is nonergodic. The second case studies the capacity achieved by optimum power-loading and beamforming schemes based on covariance feedback. Numerical results illustrate that the full capacity of MIMO systems can be preserved even for relatively high values of correlation coefficients.     

16-QAM BICM-ID in fading channels with imperfect channel state information

We analyze the impact of imperfect channel state information (CSI) on the performance of bit-interleaved coded modulation with iterative decoding (BICM-ID) over fading channels. We develop a general, accurate and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic bit-error rate (BER) of BICM-ID with imperfect CSI, and predict the BER floor due to channel estimation error. The convergence to the EF bound and the accuracy of the BER floor prediction are verified by simulation with various sets of code and channel parameters. These results are canonical, in that they apply to a variety of system configurations. Pilot symbol assisted modulation is used as a particular example for Rayleigh-fading channels.     

Capacity of nearly decomposable Markovian fading channels under asymmetric receiver-sender side information

We investigate the following issue: if fast fades are Markovian and known at the receiver, while the transmitter has only a coarse quantization of the fading process, what capacity penalty comes from having the transmitter act on the current coarse quantization alone? For time-varying channels which experience rapid time variations, sender and receiver typically have asymmetric channel side information. To avoid the expense of providing, through feedback, detailed channel side information to the sender, the receiver offers the sender only a coarse, generally time-averaged, representation of the state of the channel, which we term slow variations. Thus, the receiver tracks the fast variations of the channel (and the slow ones perforce) while the sender receives feedback only about the slow variations. While the fast variations (micro-states) remain Markovian, the slow variations (macro-states) are not. We compute an approximate channel capacity in the following sense: each rate smaller than the "approximate" capacity, computed using results by Caire and Shamai, can be achieved for sufficiently large separation between the time scales for the slow and fast fades. The difference between the true capacity and the approximate capacity is O(/spl epsi/log/sup 2/(/spl epsi/)log(-log(/spl epsi/))), where /spl epsi/ is the ratio between the speed of variation of the channel in the macro- and micro-states. The approximate capacity is computed by power allocation between the slowly varying states using appropriate water filling.     

General random coding bounds: AWGN channels to MIMO fading channels

Random coding bounds are obtained for multiple-input multiple-output (MIMO) fading channels. To derive the result in a compact and easy-to-evaluate form, a series of combinatorial codeword enumeration problems are solved for input-constrained MIMO fading channels. The bounds obtained in this paper are shown useful as performance prediction measures for MIMO systems which employ turbo-like block codes as the outer code to derive the space-time inner code. The error exponents for MIMO channels are also derived from the bounds, and then compared with the classical Gallager error exponents as well as the channel capacities. The random coding bounds associated with the maximum likelihood receiver exhibit good match with the extensive system simulation results obtained with a turbo-iterative receiver.     

基于发射端获知部分信道状态信息MIMO系统线性预编码的设计

在现实通信系统中,由于各种原因在发送端获知很难获得完全的信道状态信息,只能获得部分信道状态信息,这样接收端的检测就非常复杂。在MIMO系统中,为了提高系统的性能和降低接收端算法的复杂度,可以通过把正交空时分组与线性预编码结合。本文提出了一种在MIMO非相关信道中,在部分信道状态信息的条件下,把正交空时分组码与线性预编码结合的方案。仿真结果表明,提高了MIMO系统的性能,降低系统误码率,获得了很好的性能增益。     

On the bounds of frequency-selective channel capacity with doubly correlated geometrical MIMO channel model

The multi-input multi-output (MIMO) technology plays an important role in link transmissions. This article considers the general case for the ergodic capacity in doubly correlated frequency-selective MIMO channel. In the study, the geometrical MIMO channel model is presented. Based on the formula of MIMO ergodic capacity, the capacity limits are studied with arbitrary finite number of antennas in the frequency-selective MIMO channel. It first derives the exact expressions for the upper bound and lower bound in doubly correlated MIMO channel. The results for the single-ended correlation and independent identically distributed (i.i.d.) MIMO channel are also obtained as special cases. Then the simple expressions of the capacity bounds are attained at high SNR. Finally, results are provided by Monte Carlo simulations to verify the tightness of the derived bounds.     

Outage mutual information of space-time MIMO channels

We derive analytical expressions for the probability density function (pdf) of the random mutual information between transmitted and received vector signals of a random space-time independent and identically distributed (i.i.d.) multiple-input multiple-output (MIMO) channel, assuming that the transmitted signals from the multiple antennas are Gaussian i.i.d.. We show that this pdf can be well approximated by a Gaussian distribution, and such a Gaussian approximation is based on expressions for the given pdfs mean and variance that we derive. We prove that at high signal-to-noise ratio (SNR), every factor of 2 increase in SNR leads to an increase in outage rate in the amount of min(M,N) bits, where M and N denote the number of transmit and receive antennas, respectively. A simple expression for the moment generating function (MGF) of the mutual information pdf is also provided, based on which we establish normality of the pdf, when both M and N are large, and the SNR is large.     

Sum capacity of MIMO Gaussian broadcast channels with channel energy constraints

The motivation of this paper is to find the class of channels that provides the best sum capacity of a MIMO Gaussian broadcast channel with both transmit power and channel energy constraints when N/sub t//spl ges/KN/sub r/, where N/sub t/, N/sub r/, and K denote the number of transmit antennas, the number of receive antennas, and the number of users in the system, respectively. The best sum capacity is achieved when the user channels are mutually orthogonal to each other. For each individual user, equal energy is distributed to all non-zero spatial eigenmodes. Further, we optimize the number of non-zero eigenmodes for all users and the optimal power distribution among users. Although, we only study the case of N/sub t//spl ges/KN/sub r/ in this paper, we conjecture that similar results still hold for N/sub t/相似文献