Reinforcement-based data transmission in temporally-correlated fading channels: Partial CSIT scenario

Reinforcement algorithms refer to the schemes where the results of the previous trials and a reward-punishment rule are used for parameter setting in the next steps. In this paper, we use the concept of reinforcement algorithms to develop different data transmission models in wireless networks. Considering temporally-correlated fading channels, the results are presented for the cases with partial channel state information at the transmitter (CSIT). As demonstrated, the implementation of reinforcement algorithms improves the performance of communication setups remarkably, with the same feedback load/complexity as in the state-of-the-art schemes.Comment: Accepted for publication in ISWCS 201

Diversity Order Gain with Noisy Feedback in Multiple Access Channels

In this paper, we study the effect of feedback channel noise on the diversity-multiplexing tradeoff in multiuser MIMO systems using quantized feedback, where each user has m transmit antennas and the base-station receiver has n antennas. We derive an achievable tradeoff and use it to show that in SNR-symmetric channels, a single bit of imperfect feedback is sufficient to double the maximum diversity order to 2mn compared to when there is no feedback (maximum is mn at multiplexing gain of zero). Further, additional feedback bits do not increase this maximum diversity order beyond 2mn. Finally, the above diversity order gain of mn over non-feedback systems can also be achieved for higher multiplexing gains, albeit requiring more than one bit of feedback.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

On the DMT of TDD-SIMO Systems with Channel-Dependent Reverse Channel Training

This paper investigates the Diversity-Multiplexing gain Trade-off (DMT) of a training based reciprocal Single Input Multiple Output (SIMO) system, with (i) perfect Channel State Information (CSI) at the Receiver (CSIR) and noisy CSI at the Transmitter (CSIT), and (ii) noisy CSIR and noisy CSIT. In both the cases, the CSIT is acquired through Reverse Channel Training (RCT), i.e., by sending a training sequence from the receiver to the transmitter. A channel-dependent fixed-power training scheme is proposed for acquiring CSIT, along with a forward-link data transmit power control scheme. With perfect CSIR, the proposed scheme is shown to achieve a diversity order that is quadratically increasing with the number of receive antennas. This is in contrast with conventional orthogonal RCT schemes, where the diversity order is known to saturate as the number of receive antennas is increased, for a given channel coherence time. Moreover, the proposed scheme can achieve a larger DMT compared to the orthogonal training scheme. With noisy CSIR and noisy CSIT, a three-way training scheme is proposed and its DMT performance is analyzed. It is shown that nearly the same diversity order is achievable as in the perfect CSIR case. The time-overhead in the training schemes is explicitly accounted for in this work, and the results show that the proposed channel-dependent RCT and data power control schemes offer a significant improvement in terms of the DMT, compared to channel-agnostic orthogonal RCT schemes. The outage performance of the proposed scheme is illustrated through Monte-Carlo simulations.Comment: Accepted for publication in IEEE Transactions on Communication

Bits About the Channel: Multi-round Protocols for Two-way Fading Channels

Most communication systems use some form of feedback, often related to channel state information. In this paper, we study diversity multiplexing tradeoff for both FDD and TDD systems, when both receiver and transmitter knowledge about the channel is noisy and potentially mismatched. For FDD systems, we first extend the achievable tradeoff region for 1.5 rounds of message passing to get higher diversity compared to the best known scheme, in the regime of higher multiplexing gains. We then break the mold of all current channel state based protocols by using multiple rounds of conferencing to extract more bits about the actual channel. This iterative refinement of the channel increases the diversity order with every round of communication. The protocols are on-demand in nature, using high powers for training and feedback only when the channel is in poor states. The key result is that the diversity multiplexing tradeoff with perfect training and K levels of perfect feedback can be achieved, even when there are errors in training the receiver and errors in the feedback link, with a multi-round protocol which has K rounds of training and K-1 rounds of binary feedback. The above result can be viewed as a generalization of Zheng and Tse, and Aggarwal and Sabharwal, where the result was shown to hold for K=1 and K=2 respectively. For TDD systems, we also develop new achievable strategies with multiple rounds of communication between the transmitter and the receiver, which use the reciprocity of the forward and the feedback channel. The multi-round TDD protocol achieves a diversity-multiplexing tradeoff which uniformly dominates its FDD counterparts, where no channel reciprocity is available.Comment: Submitted to IEEE Transactions on Information Theor

Distortion Outage Minimization in Rayleigh Fading Using Limited Feedback

In this paper we investigate the problem of distortion outage minimization in a clustered sensor network where sensors within each cluster send their noisy measurements of a random Gaussian source to their respective clusterheads (CH) using analog forwarding and a non-orthogonal multi-access scheme under the assumption of perfect distributed beamforming. The CHs then amplify and forward their measurements to a remote fusion center over orthogonal Rayleigh distributed block-fading channels. Due to fading, the distortion between the true value of the random source and its reconstructed estimate at the fusion center becomes a random process. Motivated by delay-limited applications, we seek to minimize the probability that the distortion exceeds a certain threshold (called the "distortion outage" probability) by optimally allocating transmit powers to the CHs. In general, the outage minimizing optimal power allocation for the CH transmitters requires full instantaneous channel state information (CSI) at the transmitters, which is difficult to obtain in practice. The novelty of this paper lies in designing locally optimal and sub-optimal power allocation algorithms which are simple to implement, using limited channel feedback where the fusion center broadcasts only a few bits of feedback to the CHs. Numerical results illustrate that a few bits of feedback provide significant improvement over no CSI and only 6-8 bits of feedback result in outages that are reasonably close to the full CSI performance for a 6-cluster sensor network. We also present results using a simultaneous perturbation stochastic approximation (SPSA) based optimization algorithm that provides further improvements in outage performance but at the cost of a much greater computational complexity

Power-Controlled Feedback and Training for Two-way MIMO Channels

Most communication systems use some form of feedback, often related to channel state information. The common models used in analyses either assume perfect channel state information at the receiver and/or noiseless state feedback links. However, in practical systems, neither is the channel estimate known perfectly at the receiver and nor is the feedback link perfect. In this paper, we study the achievable diversity multiplexing tradeoff using i.i.d. Gaussian codebooks, considering the errors in training the receiver and the errors in the feedback link for FDD systems, where the forward and the feedback are independent MIMO channels. Our key result is that the maximum diversity order with one-bit of feedback information is identical to systems with more feedback bits. Thus, asymptotically in $\mathsf{SNR}$, more than one bit of feedback does not improve the system performance at constant rates. Furthermore, the one-bit diversity-multiplexing performance is identical to the system which has perfect channel state information at the receiver along with noiseless feedback link. This achievability uses novel concepts of power controlled feedback and training, which naturally surface when we consider imperfect channel estimation and noisy feedback links. In the process of evaluating the proposed training and feedback protocols, we find an asymptotic expression for the joint probability of the $\mathsf{SNR}$ exponents of eigenvalues of the actual channel and the estimated channel which may be of independent interest.Comment: in IEEE Transactions on Information Theory, 201