Simultaneous Estimation of Multi-Relay MIMO Channels

This paper addresses training-based channel estimation in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation overhead and delay, a training algorithm that allows for simultaneous estimation of the entire MIMO cooperative network’s channel parameters at the destination node is proposed. The exact Cram´er- Rao lower bound (CRLB) for the problem is presented in closedform. Channel estimators that are capable of estimating the overall source-relay-destination channel parameters at the destination are also derived. Numerical results show that while reducing delay, the proposed channel estimators are close to the derived CRLB over a wide range of signal-to-noise ratio values and outperform existing channel estimation methods. Finally, extensive simulations demonstrate that the proposed training method and channel estimators can be effectively deployed in combination with cooperative optimization algorithms to significantly enhance the performance of AF relaying MIMO systems in terms of average-bit-error-rate

Time-varying phase noise and channel estimation in MIMO systems

Performance of high speed communication systems is negatively affected by oscillator phase noise (PN). In this paper joint estimation of channel gains and Wiener PN in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail. In order to reduce overhead, a low complexity data-aided least-squares (LS) estimator for jointly obtaining the channel gains and PN parameters is derived. In order to track PN processes over a frame, a new decision-directed extended Kalman filter (EKF) is proposed. Numerical results show that the proposed LS and EKF based PN estimator performances are close to the CRLB and simulation results indicate that by employing the proposed estimators the bit-error rate (BER) performance of a MIMO system can be significantly improved in the presence of PN

DSTBC based DF cooperative networks in the presence of timing and frequency offsets

In decode-and-forward (DF) relaying networks, the received signal at the destination may be affected by multiple impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs). This paper proposes novel optimal and sub-optimal minimum mean-square error (MMSE) receiver designs at the destination node to detect the signal in the presence of these impairments. Distributed space-time block codes (DSTBCs) are used at the relays to achieve spatial diversity. The proposed sub-optimal receiver uses the estimated values of multiple channel gains, MTOs, and MCFOs, while the optimal receiver assumes perfect knowledge of these impairments at the destination and serves as a benchmark performance measure. To achieve robustness to estimation errors, the estimates statistical properties are exploited at the destination. Simulation results show that the proposed optimal and sub-optimal MMSE compensation receivers achieve full diversity gain in the presence of channel and synchronization impairments in DSTBC based DF cooperative networks

Transceiver design for distributed STBC based AF cooperative networks in the presence of timing and frequency offsets

In multi-relay cooperative systems, the signal at the destination is affected by impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs). In this paper we account for all these impairments and propose a new transceiver structure at the relays and a novel receiver design at the destination in distributed space-time block code (DSTBC) based amplify-and-forward (AF) cooperative networks. The Cramér-Rao lower bounds and a least squares (LS) estimator for the multi-parameter estimation problem are derived. In order to significantly reduce the receiver complexity at the destination, a differential evolution (DE) based estimation algorithm is applied and the initialization and constraints for the convergence of the proposed DE algorithm are investigated. In order to detect the signal from multiple relays in the presence of unknown channels, MTOs, and MCFOs, novel optimal and sub-optimal minimum mean-square error receiver designs at the destination node are proposed. Simulation results show that the proposed estimation and compensation methods achieve full diversity gain in the presence of channel and synchronization impairments in multi-relay AF cooperative networks

Optimal training sequences for joint timing synchronization and channel estimation in distributed communication networks

For distributed multi-user and multi-relay cooperative networks, the received signal may be affected by multiple timing offsets (MTOs) and multiple channels that need to be jointly estimated for successful decoding at the receiver. This paper addresses the design of optimal training sequences for efficient estimation of MTOs and multiple channel parameters. A new hybrid Cramer-Rao lower bound (HCRB) for joint estimation of MTOs and channels is derived. Subsequently, by minimizing the derived HCRB as a function of training sequences, three training sequence design guidelines are derived and according to these guidelines, two training sequences are proposed. In order to show that the proposed design guidelines also improve estimation accuracy, the conditional Cramer-Rao lower bound (ECRB), which is a tighter lower bound on the estimation accuracy compared to the HCRB, is also derived. Numerical results show that the proposed training sequence design guidelines not only lower the HCRB, but they also lower the ECRB and the mean-square error of the proposed maximum a posteriori estimator. Moreover, extensive simulations demonstrate that application of the proposed training sequences significantly lowers the bit-error rate performance of multi-relay cooperative networks when compared to training sequences that violate these design guidelines