Presence Of Channel State Information Errors Research Articles

Robust Transceiver Design for Correlated MIMO Interference Channels in the Presence of CSI Errors under General Power Constraints

In this paper, we consider a new design problem of optimizing a linear transceiver for correlated multiple-input multiple-output (MIMO) interference channels in the presence of channel state information (CSI) errors, which is a more realistic and practical scenario than those considered in the previous studies on uncorrelated MIMO interference channels. By taking CSI errors into account, the optimization problem is initially formulated to minimize the average mean square error (MSE) under the general power constraints. Since the objective function is not jointly convex in precoders and receive filters, we split the original problem into two convex subproblems, and then linear precoders and receive filters are obtained by solving two subproblems iteratively. It is shown that the proposed algorithm is guaranteed to converge to a local minimum. The numerical results show that the proposed algorithm can significantly reduce the sensitivity to CSI errors compared with the existing robust schemes in the correlated MIMO interference channel.

Robust Design for Intelligent Reflecting Surfaces Assisted MISO Systems

In this work, we study the statistically robust beamforming design for an intelligent reflecting surfaces (IRS) assisted multiple-input single-output (MISO) wireless system under imperfect channel state information (CSI), where the channel estimation errors are assumed to be additive Gaussian. We aim at jointly optimizing the transmit/receive beamformers and IRS phase shifts to minimize the average mean squared error (MSE) at the user. In particular, to tackle the non-convex optimization problem, an efficient algorithm is developed by capitalizing on alternating optimization and majorization-minimization techniques. Simulation results show that the proposed scheme achieves robust MSE performance in the presence of CSI error, and substantially outperforms conventional non-robust methods.

Robust THP Design for Energy Efficiency of Multibeam Satellite Systems with Imperfect CSI

In this letter, we investigate a robust zero-forcing (ZF) Tomlinson-Harashima Precoding (THP) scheme for multibeam satellite downlink systems to improve the energy efficiency (EE) when the channel state information (CSI) at the transmitter is imperfect. By using a norm-bounded error (NBE) model with unknown statistical characterization, the worst case EE optimization problem under transmit power constraint is solved with two steps. Firstly, the optimal CSI uncertainty parameter minimizing the EE is obtained, then sequential convex approximation (SCA) is used to obtain the solution via a nested iteration method. The proposed robust algorithm achieves better EE performance in comparison with the nonrobust one in the literature in the presence of CSI error, which can be shown from simulation results.

In-Band Full-Duplex Relay-Assisted Millimeter-Wave System Design

Millimeter-wave (mmWave) communication is a promising technology for future wireless systems due to the availability of huge unlicensed bandwidth. However, the need for large number of radio frequency (RF) chains associated with the antenna array and the corresponding increase in hardware complexity and power consumption are major stumbling blocks to its implementability. In this paper, we propose a low-complexity in-band full-duplex relay-assisted mmWave communication system design. We obtain the proposed multiple-input multiple-output analog–digital hybrid transceivers and relay filters by minimizing the overall sum-mean-square-error while mitigating the effect of residual loopback self-interference (LSI) in the system. The number of RF chains required in the proposed design is less than the number of antennas. We first present a design assuming the availability of perfect channel state information (CSI) at all the nodes. Later, we extend it to a robust design assuming a more realistic scenario, where the available CSI is imperfect. Furthermore, the LSI channel knowledge is assumed to be imperfect for both the designs rendering them robust to errors in loopback CSI. We employ sparse approximation technique to reduce the hardware complexity in the proposed system designs. The proposed algorithms are shown to converge to a limit even though the global convergence is hard to prove since the overall problem is non-convex. The hardware complexity-performance tradeoff of the proposed design is analyzed. Furthermore, the resilience of the robust design in the presence of CSI errors and the performance of both the proposed designs over various parameters are illustrated via numerical simulations.

Robust Designs of Beamforming and Power Splitting for Distributed Antenna Systems With Wireless Energy Harvesting

In this paper, we investigate a multiuser distributed antenna system with simultaneous wireless information and power transmission under the assumption of imperfect channel state information (CSI). In this system, a distributed antenna port with multiple antennas supports a set of mobile stations who can decode information and harvest energy simultaneously via a power splitter. To design robust transmit beamforming vectors and the power splitting (PS) factors in the presence of CSI errors, we maximize the average worst-case signal-to-interference-plus- noise ratio (SINR) while achieving individual energy harvesting constraint for each mobile station. First, we develop an efficient algorithm to convert the max-min SINR problem to a set of "dual" min-max power balancing problems. Then, motivated by the penalty function method, an iterative algorithm based on semi-definite programming (SDP) is proposed to achieve a local optimal rank-one solution. Also, to reduce the computational complexity, we present another iterative scheme based on the Lagrangian method and the successive convex approximation (SCA) technique to yield a suboptimal solution. Simulation results are shown to validate the robustness and effectiveness of the proposed algorithms.

On the Energy Efficient Multi-Pair Two-Way Massive MIMO AF Relaying With Imperfect CSI and Optimal Power Allocation

In this paper, we consider multipair two-way massive multiple-input and multiple-output (MIMO) communication system, in which multiple pairs of source nodes exchange messages with the help of one shared amplify-and-forward relay provisioned with large number of antennas. Unlike the perfect channel state information (CSI) assumption, the practical minimum mean-squared error-based channel estimation is considered. And the asymptotic signal to interference plus noise ratio (SINR) analysis of four power-scaling scenarios is presented to show that, even with the imperfect CSI, the interpair interference can still be eliminated, the small-scale fading as well as the noise at source nodes and the relay can be averaged out in the regime of very large number of antenna. It is unveiled that the impact of the channel estimation error will present in the effective large-scale fading coefficient, which explicates the degradation by the imperfect CSI estimate and consumes the results with perfect CSI as special cases. On the basis of the asymptotic SINR analysis results, the optimal power allocation problem is formulated to derive the energy efficient relaying scheme for the maximum ratio combining-maximum ratio transmission precoding scheme. Finally, numerical results are presented to validate that the energy efficient design can effectively reduce the power consumption while maintaining a reasonable sum rate in the multipair two-way massive MIMO relaying system, even in the presence of CSI error.

Impact of estimation error on two-way relaying with relay antenna selection

Abstract This paper presents the performance analysis of two-time-slot two-way relaying while considering dual antennas at the relay and imperfect channel state information (CSI) at the receivers. We consider the Max–Min antenna selection scheme at the relay. For this scheme, we show the analytical symbol error probability in the presence of imperfect CSI and observe a close match between the analytical and numerical results. We also find that Max–Min antenna selection scheme is robust against CSI error and performs better than the maximum ratio transmission (MRT) based beamforming scheme in the presence of CSI error.

A New Transmit Beamforming Scheme for Bidirectional Relaying

In this paper, we study the bidirectional/two-way relaying while considering dual antennas at the relay. With detect-and-forward relaying, we propose a transmit beamforming scheme using equal gain transmission (EGT) principle in the bidirectional relaying. Analytical outage probability and symbol error probability for the proposed scheme are presented and a close match with the numerical results is observed. Through numerical results, we show that EGT based transmit beamforming performs slightly worse than the optimum transmit beamforming scheme, while EGT is simpler to implement and requires partial channel state information (CSI). We also show that EGT based transmit beamforming outperforms existing transmission schemes in the presence of CSI error .

Joint Optimization of Transceiver Matrices for MIMO-Aided Multiuser AF Relay Networks: Improving the QoS in the Presence of CSI Errors

This paper addresses the problem of amplify-and-forward (AF) relaying for multiple-input-multiple-output (MIMO) multiuser relay networks, where each source transmits multiple data streams to its corresponding destination with the assistance of multiple relays. Assuming realistic imperfect channel state information (CSI) of all the source-relay and relay-destination links, we propose a robust optimization framework for the joint design of the source transmit precoders (TPCs), relay AF matrices and receive filters. Specifically, two well-known CSI error models are considered, namely, the statistical and the norm-bounded error models. We commence by considering the problem of minimizing the maximum per-stream mean square error (MSE) subject to the source and relay power constraints (min-max problem). Then, the statistically robust and worst-case robust versions of this problem, which take into account the statistical and norm-bounded CSI errors, respectively, are formulated. Both of the resultant optimization problems are nonconvex (semi-infinite in the worst-case robust design). Therefore, algorithmic solutions having proven convergence and tractable complexity are proposed by resorting to the iterative block coordinate update approach along with matrix transformation and convex conic optimization techniques. We then consider the problem of minimizing the maximum per-relay power subject to the quality-of-service (QoS) constraints for each stream and the source power constraints (QoS problem). Specifically, an efficient initial feasibility search algorithm is proposed based on the relationship between the feasibility check and the min-max problems. Our simulation results show that the proposed joint transceiver design is capable of achieving improved robustness against different types of CSI errors when compared with nonrobust approaches.

On the Impact of Antenna Correlation and CSI Errors on the Pilot-to-Data Power Ratio

In systems employing pilot-symbol aided channel estimation, the pilot-to-data power ratio is known to have a large impact on performance. Therefore, previous works proposed methods setting the pilot power such that either the weighted sum of the mean squared error (MSE) of the estimated data symbols is minimized or the overall spectral efficiency (SE) is maximized. However, previous works did not take into account the impact of correlated antennas and channel state information (CSI) errors on the optimal pilot power setting. In this paper, we consider the uplink of a multiuser multiple-input multiple-output (MU MIMO) system employing a receiver that minimizes the MSE of the received data symbols in the presence of CSI errors and derive closed-form expressions for the MSE and the achievable SE. These expressions take into account the impact of antenna correlation and CSI errors, and are a function of pilot power and the number of receive antennas. The analytical and numerical results can help set the pilot power, minimizing the MSE in multiple antenna systems.

On Minimizing the MSE in the Presence of Channel State Information Errors

We consider the uplink of a multiuser multiple input multiple output (MU MIMO) system, in which the base station acquires channel state information (CSI) for which the estimation error depends on the resources assigned to the uplink pilot symbols. For this system, we first derive the receiver that minimizes the mean square error (MSE) of the uplink detected data symbols, as opposed to the naive receiver that does not minimize the MSE in the presence of CSI errors. We then derive a closed form expression for the MSE as a function of the employed pilot-to-data power ratio, number of antennas and the MU MIMO interference power. This expression allows us to gain the insight that the gain of using the actual MMSE receiver as opposed to the naive receiver becomes particularly important when the number of BS antennas is large.