Jianwu Chen

Joint CFO and Channel Estimation for Multiuser MIMO-OFDM Systems With Optimal Training Sequences

This paper addresses the problem of joint carrier frequency offset (CFO) and channel estimation in multiuser multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. To choose the optimal training sequences with the goal of providing the smallest estimation mean square error (MSE), the asymptotic Cramer-Rao bounds (asCRBs) are derived. The optimal training sequences are designed that minimize the asCRBs for both CFO and channel estimation under the constraint that the asCRBs being channel independent. A joint CFO and channel estimator is derived based on the maximum likelihood (ML) criterion. A computationally efficient method using importance sampling technique is proposed to solve the highly demanding multidimensional exhaustive search required by the ML multi-CFO estimation. Simulation results illustrate the merits of the proposed training sequences and also verify the effectiveness of the proposed estimation scheme.

Joint Maximum-Likelihood CFO and Channel Estimation for OFDMA Uplink Using Importance Sampling

In this paper, the optimal carrier frequency offset (CFO) and channel estimator for an orthogonal frequency-division multiple-access (OFDMA) uplink based on a joint maximum-likelihood (ML) criterion is derived. Direct implementation of the resultant estimation scheme is challenging due to the need for a multidimensional exhaustive search in multi-CFO estimation. To solve this problem, an optimization theorem is exploited, and a computationally efficient method using an importance sampling technique is proposed. Without the need to provide an initial estimate, the proposed estimator guarantees the generation of the global optimal solution. Simulation results clearly verify the effectiveness of the proposed estimation scheme.

Ml joint CFO and channel estimation in OFDM systems with timing ambiguity

This letter addresses the problem of joint estimation of carrier frequency offset (CFO) and channel for OFDM systems in the presence of timing ambiguity. Based on two signal models for quasi-synchronized OFDM systems, two joint CFO and channel estimators are derived from the Maximum Likelihood (ML) criterion. The first estimator obtained is a joint estimator for all unknown parameters, which needs a multi-dimensional search. The second estimator has a reduced complexity, but its performance slightly degrades compared with the first one. Through MSE analyses, we find that when the number of subcarriers is large, the two estimators are equivalent.

Timing Robust Joint Carrier Frequency Offset and Channel Estimation for OFDM Systems

For orthogonal frequency division multiplexing (OFDM) systems, the frequency synchronization and channel estimation are always tightly coupled with timing synchronization. In this paper, we investigate the effects of timing offset on the performance of a recently proposed subspace based joint carrier frequency offset (CFO) and channel estimation scheme. It is found that this scheme is highly sensitive to timing offsets. An improved timing robust scheme is then proposed. In the proposed CFO estimation scheme, the orthogonality loss between two subspaces due to timing offset is restored by exploiting a reduced null-subspace. The missing taps in the original channel estimate are recovered by using an upper bound of the channel length instead of the actual value. The effectiveness of the proposed scheme is verified by simulations.

Training Design for Joint CFO and Channel Estimation in Multiuser MIMO OFDM System

This paper addresses the problem of optimal training for joint carrier frequency offset (CFO) and channel estimation in multiuser MIMO OFDM systems, where each user can utilize all available subcarriers. To choose the training sequence with the goal of providing the smallest estimation mean square error (MSE), the Cramer-Rao bound (CRB) is derived in close-form. However, little insight on the sequence selection can be obtained from the CRB directly due to its complicated dependence on training sequence and channel parameters. To proceed, asymptotic CRB, which has a much simpler dependence on the training, is derived. It is found that the optimal training sequences should be individually white and uncorrelated with each other. Simulation results illustrate the merits of the proposed training design.

Optimal Joint CFO and Channel Estimation in Quasi-Synchronized OFDM Systems

This paper addresses the problem of joint estimation of carrier frequency offset (CFO) and frequency-selective channel in quasi-synchronized orthogonal frequency division multiplexing (OFDM) systems. Two equivalent signal models with embedded timing ambiguity are introduced first, and then two joint CFO and channel estimators are derived from the Maximum Likelihood (ML) criterion. The first estimator obtained is a joint estimator for timing, CFO and channel, which needs a two dimension search for parameter estimation. The second estimator has a reduced complexity, but its performance slightly degrades compared with the first estimator due to more unknown parameters required to be estimated. We analyze and compare the MSE performance of the two estimators and find that when the number of subcarriers is large, the two estimators are equivalent.

Optimal Joint CFO and Channel Estimation for Multiuser MIMO-OFDM Systems

This paper addresses the problem of joint carrier frequency offset (CFO) and channel estimation in multiuser multiple-input multiple-output (MIMO) orthogonal frequency- division multiplexing (OFDM) systems. A joint CFO and channel estimator is derived based on the maximum likelihood (ML) criterion. A computationally efficient method using importance sampling technique is proposed to solve the highly demanding multi-dimensional exhaustive search required by the ML multi- CFO estimation. Simulation results verify the effectiveness of the proposed estimation scheme.

Frequency synchronization for OFDM systems over doubly-selective channels

In this paper, we investigate the problem of carrier frequency offset (CFO) estimation for orthogonal frequency division multiplexing (OFDM) system over doubly-selective channels. Representing the doubly-selective channels with basis expansion, the signal model is reformulated and one CFO estimator is derived. Furthermore, the Cramer-Rao bound (CRB) for the estimation problem is derived in closed form. The effectiveness of the proposed scheme is verified by simulations.

Optimal CFO and channel estimation for OFDMA uplink using importance sampling

In this paper, we derive the optimal carrier frequency offset (CFO) and channel estimator for OFDMA uplink based on joint maximum likelihood (ML) criterion. Direct implementation of the resultant estimation scheme is quite challenging due to the need of multi-dimensional exhaustive search in multi-CFO estimation. To solve this problem, a computationally efficient method using importance sampling technique is proposed. Without the need of providing initial estimate, the proposed estimator guarantees to generate the global optimal solution. Simulation results clearly verify the effectiveness of the proposed estimation scheme.

QoS constrained robust MIMO transceiver design under unknown interference

We study the robust transceiver optimization in multiple-input multiple-output (MIMO) systems aiming at minimizing transmit power under probabilistic quality-of-service (QoS) requirements. Owing to the unknown distributed interference, the channel estimation error can be arbitrary distributed. Under this situation, the QoS requirements should account for the worst-case channel estimation error distribution. While directly finding the worst-case distribution is challenging, two methods are proposed to solve the robust transceiver design problem. One is based on the Chebyshev inequality, the other is based on a novel duality method. Simulation results show that the QoS requirement is satisfied by both proposed algorithms. Furthermore, among the two proposed methods, the duality method shows a superior performance in transmit power, while the Chebyshev method demonstrates a lower computational complexity.