Capacity and power allocation for fading MIMO channels with channel estimation error (original) (raw)
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MIMO capacity with channel uncertainty: does feedback help?
IEEE Global Telecommunications Conference, 2004. GLOBECOM '04., 2004
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The capacity of Multiple Input Multiple Output (MIMO) Rayleigh fading channels with full knowledge of channel state information (CSI) at both the transmitter and the receiver (CSI-TR) has been shown recently to scale at low Signal-to-Noise Ratio (SNR) essentially as SNR log(1/SNR), independently of the number of transmit and receive antennas. In this paper, we investigate the ergodic capacity of MIMO Rayleigh fading channel with estimated channel state information at the transmitter (CSI-T) and possibly imperfect channel state information at the receiver (CSI-R). Our framework can be seen as a generalization of previous works as it can capture the perfect CSI-TR as a special case when the estimation error variance goes to zero. In our work, we mainly focus on the low SNR regime and we show that the capacity scales as (1−α) SNR log(1/SNR), where α is the estimation error variance. This characterization shows the loss of performance due to error estimation over the perfect channel state information at both the transmitter and the receiver. As a by-product of our new analysis, we show that our framework can also be extended to characterize the capacity of MIMO Rician fading channels at low SNR with possibly imperfect CSI-T and CSI-R.
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The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring., 2003
1-Distributed antenna system (DAS) can reduce the access distance and so lower the required transmit power compared with the conventional multiple input multiple out (MIMO) system. This paper investigated the information-theoretic capacity of DAS based on the channel model considering path loss, log-normal shadowing fading and Rayleigh fading. We find that the location of the receiver affects the DAS capacity and the difference between capacity with water-filling power allocation and that with equal-power allocation is significant. Furthermore, simulation results show that DAS offers large capacity gains over the traditional MIMO system. I.
IEEE Transactions on Information Theory, 2007
Multiple-antenna concepts for wireless communication systems promise high spectral efficiencies and improved error rate performance by proper exploitation of the randomness in multipath propagation. In this paper, we investigate the impact of channel uncertainty caused by channel estimation errors on the capacity of Rayleigh and Ricean block-fading channels. We consider a training-based multiple-antenna system that reserves a portion of time to sound the channel. The training symbols are used to estimate the channel state information (CSI) at the receiver by means of an arbitrary linear estimation filter. No CSI is assumed at the transmitter. Our analysis is based on an equivalent system model for training-based multiple-antenna systems which specifies the channel by the estimated (and hence, known) channel coefficients and an uncorrelated, data-dependent, multiplicative noise. This model includes the special cases of perfect CSI and no CSI. We present new upper and lower bounds on the maximum instantaneous mutual information to compute ergodic and outage capacities, and extend previous results to arbitrary (and possibly mismatched) linear channel estimators and to correlated Ricean fading. Several numerical results for single-and multiple-antenna systems with estimated CSI are included as illustration. Index Terms-Ergodic and outage capacity, fading channels, linear channel estimation, maximum mutual information, multiple-antenna systems. I. INTRODUCTION M ULTIPLE-antenna concepts for fading channels have received considerable attention in the recent history of wireless communication systems. Significant increases in spectral efficiency [1] and large improvements in terms of error rate performance [2] can by achieved by properly exploiting the randomness in multipath propagation, without increase in transmit power or bandwidth. Information-theoretic work on the capacity of single and multiple-antenna fading channels originally assume perfect channel state information (CSI) available at the receiver [1]-[5]. Ericson [3] considered a Gaussian channel with slow fading and gave an explicit capacity expression. A generalization for multiple-an-Manuscript
Ergodic capacity of MIMO channels with statistical channel state information at the transmitter
2004
It is well known that with the availability of statistical channel state information at the transmitter, the capacity-achieving transmission strategy is transmission on the long-term eigen-modes of the transmit correlation matrix with adequate power allocation. However, the optimum power allocation strategy is not known in general. Using recent analytical results on mean mutual information of MIMO channels with transmit as well as receive correlation, We study the behavior of the capacity-achieving power allocation strategy. To this end, we also make use of asymptotical results for a large number of transmit or receive antennas and the high as well as low SNR regime, which in certain cases allows for a closed-form analysis. Furthermore, we investigate two low complexity power allocation schemes, which are based on certain upper bounds on mean mutual information.
Near-optimal power allocation for MIMO channels with mean or covariance feedback
IEEE Transactions on Communications, 2000
With mean or covariance channel feedback, the input covariance matrix can be designed to achieve the ergodic capacity of a MIMO fading channel. It is known that the eigenvectors of the optimal input covariance matrix are the same as the eigen-vectors of the channel mean or covariance matrix. However, the optimal power allocation across the eigen-vectors is much less understood. In this paper, two scenarios are investigated: 1) Rician MIMO channels with mean channel feedback, and 2) Rayleigh MIMO channels with covariance channel feedback. We first derive a suboptimal power allocation algorithms in the spatial domain for expected mutual information maximization for two transmit antennas systems, based on an upper bound for the ergodic capacity of a MIMO channel with either channel mean or covariance information at the transmitter. Then, we extend heuristically the results to systems with multiple antennas at both the transmitter and receiver side. The proposed power allocation solution permits a closed-form expression and has a water-filling interpretation. Simulation results reveal that the proposed method performs nearly the same as the optimal solution (which requires highly complex optimization routines over random processes) with inappreciable difference.