Optimal Transmission Strategy Research Articles

Channel Capacity and Capacity-Range of Beamforming in MIMO Wireless Systems Under Correlated Fading With Covariance Feedback

We study the optimal transmission strategy of a single-user multiple-input/multiple-output communication system with covariance feedback. We consider the situation with correlated receive and correlated transmit antennas in Rayleigh flat fading. Furthermore, we assume that the receiver has perfect channel state information, while the transmitter knows only the transmit correlation matrix and the receive correlation matrix. We show that transmitting in the direction of the eigenvectors of the transmit correlation matrix is the optimal transmission strategy. In addition to this, the optimal power allocation is studied and a necessary and sufficient condition for optimality of beamforming is derived. All theoretical results are illustrated by numerical simulations.

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.

Multiple Antenna Transmission With Channel State Information: A Low-Rate Feedback Approach

This paper presents a novel multiple antenna transmission scheme that depends on channel state information. The proposed approach uses low-rate feedback to adaptively estimate the downlink fading channel at the base-station. The optimal transmission scheme given channel state information can in turn be determined from these channel estimates. It is shown that the channel estimation requires selective feedback of the adaptive filter prediction errors, that can be computed at the mobile by receiving a beamformed pilot signal. To this end, a randomized channel inversion pilot beamforming scheme is developed that makes possible this feedback of prediction errors possible. Further, this method is shown to be relatively insensitive to feedback quantization effects for a given average feedback rate. Simulation results indicate that the feedback scheme provides significant closed-loop beamforming gains with low bit rate feedback even for large number of transmit antennas.

The optimality of beamforming in uplink multiuser wireless systems

This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error.

Optimum transmission strategy for power saving in fading channels

An optimum transmission strategy in a fading channel with known channel side information at the transmitter and receiver is addressed. The Shannon channel capacity is reformulated based on dynamic programming and it is demonstrated how this model can extend the information-theoretic domain for solving the channel capacity when a closed-form solution cannot be found.

Optimal Transmission with Imperfect Channel State Information at theTransmit Antenna Array

We study the optimal transmission strategy of a multiple-input single-output wireless communication link. The receiver has perfect channel state information while the transmitter has only long-term channel state information in terms of the channel covariance matrix. It was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvalues of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We study the properties of these optimal capacity achieving eigenvalues, and present a necessary and sufficient condition for the optimal eigenvalues of the transmit covariance matrix. Furthermore, we develop a necessary and sufficient condition for achieving capacity when transmitting in all directions. We compare the capacity gain of an optimal diversity system with a system which works with beamforming, and we derive an upper bound. We answer the main questions regarding the system design using the developed results. Additionally, we show in which way the multiplexing gain can be computed in case the channel covariance matrix is given. We compute the maximum number of required parallel data streams, and we define a multiplexing function in order to obtain a measure for the available multiplexing gain. Furthermore, we show that the capacity gain is small considering the additional complexity at the receiver. We illustrate all results by numerical simulations.

Self-organizing packet radio ad hoc networks with overlay (SOPRANO)

The SOPRANO project involves a novel adaptive and scalable wireless network architecture utilizing a mixture of cellular and multihop packet radio system topologies with the potential to support a variety of applications including high-data rate Internet and multimedia traffic at a reasonable degree of implementation complexity. This article discusses the potential benefits of this structure and addresses several relevant issues necessary to support such a network. More specifically, it focuses on connection establishment and self-organization, investigates the formulation of an optimum transmission strategy, and examines some of the techniques by which we can augment the capacity or enhance the system performance in this multihop network. We also present capacity bounds that illustrate how these techniques help in trading off conserved power for a multifold capacity advantage.

Space-time transmit precoding with imperfect feedback

The use of channel feedback from receiver to transmitter is standard in wireline communications. While knowledge of the channel at the transmitter would produce similar benefits for wireless communications as well, the generation of reliable channel feedback is complicated by the rapid time variations of the channel for mobile applications. The purpose of this paper is to provide an information-theoretic perspective on optimum transmitter strategies, and the gains obtained by employing them, for systems with transmit antenna arrays and imperfect channel feedback. The spatial channel, given the feedback, is modeled as a complex Gaussian random vector. Two extreme cases are considered: mean feedback, in which the channel side information resides in the mean of the distribution, with the covariance modeled as white, and covariance feedback, in which the channel is assumed to be varying too rapidly to track its mean, so that the mean is set to zero, and the information regarding the relative geometry of the propagation paths is captured by a nonwhite covariance matrix. In both cases, the optimum transmission strategies, maximizing the information transfer rate, are determined as a solution to simple numerical optimization problems. For both feedback models, our numerical results indicate that, when there is a moderate disparity between the strengths of different paths from the transmitter to the receiver, it is nearly optimal to employ the simple beamforming strategy of transmitting all available power in the direction which the feedback indicates is the strongest.

Optimal transmission and jamming strategies in a communication channel

AbstractA zero‐sum differential game model is presented for two players who are both transmitting information and jamming their opponent at the same time, under channel capacity constraints. The problem for each player is to find an optimal policy for allocating this capacity over the duration of the game. Given a cost function for the game, conditions are determined under which equilibrium strategies exist. These (pure) strategies are found to be of the bang‐bang variety and depend on game parameters such as the channel capacity and jamming effectiveness of the players, as well as the duration of the game.