Channel State Information At The Transmitter Error Research Articles

Link Adaptation for Rate Splitting Systems With Partial CSIT

Rate Splitting (RS) has emerged as a flexible multiple-access scheme for Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems, generalizing more conventional approaches such as linear precoding or Non-Orthogonal Multiple Access (NOMA), and providing additional robustness against imperfect channel state information at the transmitter. Actual achievable rates cannot be pre-calculated when facing imperfect and/or outdated channel state information at the transmitter (CSIT), so practical real-time mechanisms in the form of link adaptation (LA) are required. The available CSIT is used to design the RS precoders, which can accommodate some degree of robustness, whereas the physical layer feedback reports the outcome of the decoding of the codewords, in the form of acknowledgement (ACK) or negative ACK (NACK), providing the additional meta-robustness needed when the statistical model of CSIT errors is not accurate, and/or the precoders cannot fully track the channel dynamics. We characterize the outage rate region of RS and analyze the convergence of the complete LA-RS system under partial CSIT (non-accurate and non-permanent), providing relevant insights for addressing the adaptation of private and common rates, designing robust precoders with throughput as relevant metric, and handling the time-variant CSIT quality.

Distributed Precoding Using Local CSIT for MU-MIMO Heterogeneous Cellular Networks

Cell densification is a key driver to increase area spectral efficiencies in multi-antenna cellular systems. As increasing the density of base stations (BSs) and users that share the same spectrum, however, both inter-user-interference (IUI) and inter-cell interference (ICI) problems give rise to a significant loss in spectral efficiencies in such systems. To resolve this problem under the constraint of local channel state information per BS, in this paper, we present a novel noncooperative multi-user multiple-input multiple-output (MIMO) precoding technique, called signal-to-interference-pulse-leakage-pulse-noise-ratio (SILNR) maximization precoding. The key innovation of our distributed precoding method is to maximize the product of SILNRs of users per cell using local channel state information at the transmitter (CSIT). We show that our precoding technique only using local CSIT can asymptotically achieve the multi-cell cooperative bound attained by cooperative precoding using global CSIT in some cases. We also present a precoding algorithm that is robust to CSIT errors in multi-cell scenarios. By multi-cell system-level simulations, we demonstrate that our distributed precoding technique outperforms all existing noncooperative precoding methods considerably and can also achieve the multi-cell bound very tightly even with not-so-many antennas at BSs.

Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems With Partial CSIT: A Rate-Splitting Approach

This paper considers the sum-rate (SR) maximization problem in downlink multi-user multiple input simgle output (MU-MISO) systems under imperfect channel state information at the transmitter (CSIT). Contrary to existing works, we consider a rather unorthodox transmission scheme. In particular, the message intended to one of the users is split into two parts: a common part which can be recovered by all users, and a private part recovered by the corresponding user. On the other hand, the rest of users receive their information through private messages. This rate-splitting (RS) approach was shown to boost the achievable degrees of freedom when CSIT errors decay with increased SNR. In this paper, the RS strategy is married with linear precoder design and optimization techniques to achieve a maximized ergodic SR (ESR) performance over the entire range of SNRs. Precoders are designed based on partial CSIT knowledge by solving a stochastic rate optimization problem using means of sample average approximation coupled with the weighted minimum mean square error approach. Numerical results show that in addition to the ESR gains, the benefits of RS also include relaxed CSIT quality requirements and enhanced achievable rate regions compared with conventional transmission with no rate-splitting.

Outage Bound for Max-Based Downlink Scheduling With Imperfect CSIT and Delay Constraint

We consider downlink max-based scheduling in which the base station and each user are equipped with a single antenna. In each time slot, the base station obtains channel gains of all users and selects the user with the largest squared channel gain. Assuming that channel state information at the transmitter (CSIT), i.e., squared channel gain, can be inaccurate, we derive lower bounds for probability of outage, which occurs when a required data rate is not satisfied under a delay constraint. The bounds are tight for Rayleigh fading and show how required rate and CSIT error affect outage performance.

Probabilistic constrained multicast beamforming in cognitive relay systems

AbstractIn this paper, multicast beamforming in cognitive relay systems is investigated with the consideration of imperfect channel state information at the transmitter (CSIT). We focus at the design of the optimal signal forwarding matrix at the cognitive relay in both centralized relay mode (CRM) and distributed relay mode (DRM). The problem is formulated aiming at minimizing the total consumed power at the relay node with suitable QoS guarantee for secondary users and strict interference control for primary users. Due to the uncertainty of transmission channel gains, constraints for QoS guarantee and interference control cannot be expressed in closed forms, making it extremely difficult to solve the problem directly. To circumvent this, we first employ the Bernstein-type inequality to convert the probabilistic constraints into closed-form expressions and then present both the semi-definite relaxation (SDR) algorithm and the penalty function (PenFun) algorithm to accomplish the non-convex problem optimization. Simulation results show that CRM is more resource efficient than DRM, and the PenFun algorithm can achieve a much better solution than the SDR algorithm at the cost of complexity. Meanwhile, compared with existing schemes which do not consider the CSIT error, the proposed schemes can support a much lower outage probability and enjoy perfect interference control for primary users.

Low Complexity Delay-Constrained Beamforming for Multi-User MIMO Systems With Imperfect CSIT

In this paper, we consider the delay-constrained beamforming control for downlink multi-user MIMO (MU- MIMO) systems with imperfect channel state information at the transmitter (CSIT). The delay-constrained control problem is formulated as an infinite horizon average cost partially observed Markov decision process. To deal with the curse of dimensionality, we introduce a virtual continuous time system and derive a closed-form approximate value function using perturbation analysis w.r.t. the CSIT errors. To deal with the challenge of the conditional packet error rate (PER), we build a tractable closed- form approximation using a Bernstein-type inequality. Based on the closed-form approximations of the relative value function and the conditional PER, we propose a conservative formulation of the original beamforming control problem. The conservative problem is non-convex and we transform it into a convex problem using the semidefinite relaxation (SDR) technique. We then propose an alternating iterative algorithm to solve the SDR problem. Finally, the proposed scheme is compared with various baselines through simulations and it is shown that significant performance gain can be achieved.

Linear precoding in distributed MIMO systems with partial CSIT

We study the transmission problem in a distributed multiple-input multiple-output (MIMO) system consisting of several distributed transmitters and a common receiver. Assuming partial channel state information at the transmitter (CSIT), we propose a low-cost weighted channel matching and scattering (WCMS) linear precoding strategy. The proposed precoder can be decomposed into two parallel modules: channel matching (CM) and energy scattering. The signals generated by the CM modules from different transmitters provide a coherent gain with improved power efficiency. The use of the scattering modules provides robustness against CSIT uncertainty. By properly combining these two modules, WCMS can achieve coherent gain proportional to the accuracy of the available CSIT as well as robustness against CSIT error. WCMS is simple and fully decentralized and thus is highly suitable for a distributed MIMO system. Numerical results demonstrate that WCMS indeed achieves significant gains in distributed MIMO environments with partial CSIT.

Robust THP Transceiver Designs for Multiuser MIMO Downlink with Imperfect CSIT

In this paper, we present robust joint non-linear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for inter-user interference pre-cancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust i) minimum SMSE, ii) MSE-constrained, and iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semi-definite programs (SDP). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints.

Design and Analysis of Delay-Sensitive Cross-Layer OFDMA Systems with Outdated CSIT

It is well known that cross-layer scheduling can boost the spectral efficiency of multi-user OFDMA systems through multi-user selection diversity but existing designs usually have two important assumptions - users are delay-insensitive and channel state information at the transmitter (CSIT) is perfect. In practice, users have heterogeneous delay requirements and CSIT usually becomes outdated in time varying channel, which in turns leads to systematic packet errors and hence results in significant degradation on the throughput and delay performance in the OFDMA systems. In this paper, a novel cross-layer design problem is formulated as a convex optimization problem, on which a delay-sensitive jointly optimal power, rate and subcarrier allocation scheme is proposed so as to maintain heterogeneous users' delay requirement as well as achieving a target packet outage probability through combining queueing theory and information theory. Furthermore, we obtain closed-form asymptotic performance of the proposed delay-sensitive scheduler. Unlike the well-known SNR gain of Theta(log - sigma2 DeltaH) in conventional cross-layer scheduler with perfect CSIT, we demonstrate a cross-layer SNR gain of Theta((1 - sigma2 DeltaH)log K)can still be achieved under heterogeneous delay constraints and outdated CSIT with error variance sigma2 DeltaH. Finally, simulation results show that our proposed delay-sensitive CSIT error considerate schemes provide robust system performance enhancement over conventional CSIT error inconsiderate opportunistic scheduler and naive queue length based MAX-Weight scheduler while satisfying heterogeneous delay requirements even at moderate to high CSIT errors.

Closed-loop cross-layer SDMA designs with outdated CSIT

In this paper, we propose a novel closed-loop approach for robust downlink multi-antenna cross-layer design with outdated channel state information at the transmitter (CSIT). Based on the ACK/NAK feedbacks from the mobiles, the proposed cross-layer design does not require the knowledge of CSIT error statistics. We formulate the cross-layer design as a mixed combinatorial search and Markov decision process (MDP). While it is well-known that general solutions for MDP are very complex, one important contribution of this paper is that we obtain simple closed-form power, rate and user allocation policies which are asymptotically optimal for small target frame error rate (FER). Simulation results illustrate that the performance of the proposed closed-loop cross-layer design is very robust with respect to the outdated CSIT, CSIT error model mismatch as well as channel variations due to Doppler.

Cross Layer Design of Downlink Multi-Antenna OFDMA Systems with Imperfect CSIT for Slow Fading Channels

In most existing works, perfect knowledge of channel state information at the transmitter (CSIT) is assumed to realize the potential benefit of cross-layer scheduling and spatial multiplexing gains of MIMO/OFDMA systems. However, perfect knowledge of CSIT is not easy to achieve in practice due to estimation noise or delay in feedback. In this paper, we shall focus on the cross-layer design of downlink multi-antenna OFDMA systems with imperfect CSIT for slow fading channels. We shall show that our proposed cross-layer scheduler can exploit the multiuser diversity and spatial multiplexing gain even in the presence of moderate CSIT error.