Capacity Of Multiple Antenna System Research Articles

On the capacity of multiple antenna systems

On the capacity of multiple antenna systems

Comments and Corrections to “Capacity of Multiple-Antenna Systems With Both Receiver and Transmitter Channel State Information”

The correspondence cited in the above article derived ergodic capacity of the coherent multiple-input multiple-output (MIMO) channel in independent and identically distributed (IID) Rayleigh fading. While the theoretical results are correct, several plots in the paper are incorrect. In this correspondence, we correct the plots. More importantly, the corrected plots present an interesting and compelling contrast between performances of the coherent MIMO systems with and without channel state information at the transmitter; whereas this view is somewhat limited in the above article because of flaws in the capacity curves.

On the Capacity of Multiple-Antenna Systems and Parallel Gaussian Channels With Amplitude-Limited Inputs

We propose upper and lower bounds on the capacity of multiple-input multiple-output (MIMO) systems with amplitude-limited inputs. The results are derived by considering an equivalent channel via singular value decomposition, and by enlarging and reducing the corresponding feasible region of the channel input vector, for the upper and lower bounds, respectively. We analytically characterize the asymptotic behavior of the derived bounds for high and low noise levels, and study the gap between them. We also consider parallel Gaussian channels with peak and average power-constrained inputs. For such channels, the capacity-achieving distribution has been reported in the literature to be discrete, which can be computed using numerical optimization techniques. However, there is no closed-form expression and finding the capacity-achieving distribution is computationally tedious. With this motivation, we derive approximate expressions for the capacity at low and high noise variance levels. We illustrate our findings on both MIMO channels and parallel Gaussian channels via several numerical examples.

A Receive Antenna Subarray Formation Algorithm for MIMO Systems

Antenna selection techniques have been proposed to reduce the hardware complexity of MIMO wireless systems, while being efficient in terms of information rate achieved. Recently, an alternative method has been introduced to maximize the capacity of multiple antenna systems with reduced available RF chains, called antenna subarray formation. The method is based on the grouping of properly weighted antenna elements and initially was implemented with the use of an evolutionary optimization technique using the link capacity as a cost function. In this paper we propose an analytic algorithm for the subarray formation concept allowing for a more compact and tractable implementation

On the capacity of multiple-antenna systems in Rician fading

The effect of Rician-ness on the capacity of multiple-antenna systems is investigated under the assumption that channel state information (CSI) is available only at the receiver. The average-power-constrained capacity of such systems is considered under two different assumptions on the available knowledge about fading at the transmitter: the case in which the transmitter has no knowledge of fading at all, and the case in which the transmitter has knowledge of the distribution of the fading process but not the instantaneous CSI. The exact capacity is given for the former case, while capacity bounds are derived for the latter case. A new signaling scheme is also proposed for the latter case and it is shown that by exploiting the knowledge of Rician-ness at the transmitter via this signaling scheme, significant capacity gain can be achieved. The derived capacity bounds are evaluated explicitly to provide numerical results in some representative situations.

Capacity of multiple antenna systems in free space and above perfect ground

Multiple input-multiple output (MIMO) systems are a promising technique for wireless applications that require high data rates. We theoretically study their capacity potential for propagation in free-space and over a ground surface. We investigate how this depends on the array geometry and the electric field polarization. Moreover, we validate our theoretical predictions with measurements above a nearly perfectly flat surface. The experiment shows good agreement with the theory for a large range of distances and deviates from it when secondary effects (roughness etc.) become more significant.

A new approach to layered space-time coding and signal processing

The information-theoretic capacity of multiple antenna systems has been shown to be significantly higher than that of single antenna systems in Rayleigh-fading channels. In an attempt to realize this capacity, Foschini (1996) proposed the layered space-time architecture. This scheme was argued to asymptotically achieve a lower bound on the capacity. Another line of work has focused on the design of channel codes that exploit the spatial diversity provided by multiple transmit antennas (Tarokh et al. 1998, Hammons and Gamal 2000). In this paper, we take a fresh look at the problem of designing multiple-input-multiple-output (MIMO) wireless systems. First, we develop a generalized framework for the design of layered space-time systems. Then, we present a novel layered architecture that combines efficient algebraic code design with iterative signal processing techniques. This novel layered system is referred to as the threaded space-time (TST) architecture. The TST architecture provides more flexibility in the tradeoff between power efficiency, bandwidth efficiency, and receiver complexity. It also allows for exploiting the temporal diversity provided by time-varying fading channels. Simulation results are provided for the various techniques that demonstrate the superiority of the proposed TST architecture over both the diagonal layered space-time architecture in Foschini (1996) and the multilayering approach (Tarokh et al. (1999).