Yanxiang Jiang

Frequency Offset Estimation and Training Sequence Design for MIMO OFDM

This paper addresses carrier frequency offset (CFO) estimation and training sequence design for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems over frequency selective fading channels. By exploiting the orthogonality of the training sequences in the frequency domain, integer. CFO (ICFO) is estimated. With the uniformly spaced non-zero pilots in the training sequences and the corresponding geometric mapping, fractional CFO (FCFO) is estimated through the roots of a real polynomial. Furthermore, the condition for the training sequences to guarantee estimation identifiability is developed. Through the analysis of the correlation property of the training sequences, two types of sub-optimal training sequences generated from the Chu sequence are constructed. Simulation results verify the good performance of the CFO estimator assisted by the proposed training sequences.

Training Sequence Assisted Frequency Offset Estimation for MIMO OFDM

New frequency domain training sequences are proposed sedfor carrier frequency offset (CFO) estimation in multipleinput multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system over frequency-selective fading channels. By exploiting frequency domain orthogonality of the training sequences, integer CFO (ICFO) can be estimated without matrix inversion operation. With the non-zero pilots in the training sequences uniformly spaced, fractional CFO (FCFO) can be estimated through the roots of a complex polynomial. Moreover, a simplified CFO estimator is also proposed which exploits a geometric mapping to transform the complex polynomial to a real one. Simulation results illustrate the good performances of the CFO estimators assisted by the proposed training sequences.

Preamble Design and Synchronization Algorithm for Cooperative Relay Systems

In the cooperative relay system, different frames from different relays are not aligned in the time domain, and have different carrier frequency offsets (CFOs). Estimation of these time offsets and multiple CFOs is a crucial and challenging task. In this contribution, a new preamble structure is proposed, and the corresponding timing and frequency synchronization algorithms are also presented for the cooperative relay systems. CAZAC sequence is utilized in the preamble design regarding of its correlation properties. The performance of the proposed algorithms is evaluated by simulations. The simulation results show that the proposed preamble structure and synchronization algorithms have a satisfactory performance in cooperative relay systems. (7), a time and CFO estimation of a new user is presented, for the situation where all other users have been synchronized. Pun et al. (8) gave a joint CFO and channel estimation based on the maximum-likelihood (ML) principle. The method needs a multidimensional optimization, which is very complicated. In (9) and (10), specially designed pilot symbols are proposed to turn the multi-dimensional optimization problem into independent 1-dimensional optimization problems. In this paper, we consider using one pilot OFDM symbol for the timing synchronization and two repeated pilot symbols for CFOs estimation in cooperative relay systems. The corresponding timing and CFO estimation algorithms are proposed. Coarse timing acquisition is realized by utilizing unequal period synchronization basic sequence (SBS), and then, the received samples are correlated with the transmitted sequence to implement fine time acquisition. Based on the specially designed preamble, the method in (3) for P2P OFDM is extended for cooperative relay systems. Utilizing the correlation properties of preamble sequence, the range of the estimated CFOs can be extended to integral frequency offsets. CAZAC sequence has been used to generate the preamble for its perfect correlation properties. The rest of the paper is organized as follows: Section Ⅱ presents the signal model for a cooperative relay system. The preamble structure and the proposed synchronization algorithms are described in Section Ⅲ, and our simulation results are discussed in Section Ⅳ. Finally, Section Ⅴ gives the conclusion.

Simplified Frequency Offset Estimation for MIMO OFDM Systems

This paper addresses a simplified frequency offset estimator for multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems over frequency-selective fading channels. By exploiting the good correlation property of the training sequences, which are constructed from the Chu sequence, carrier frequency offset (CFO) estimation is obtained through factor decomposition for the derivative of the cost function with great complexity reduction. The mean square error (MSE) of the CFO estimation is derived to optimize the key parameter of the simplified estimator as well as to evaluate the estimator performance. Simulation results confirm the good performance of the training-assisted CFO estimator.

Low complexity soft decision equalization for block transmission systems

This paper addresses the problem of the soft decision equalization. We show the relation between the iterative soft decision interference cancellation (ISDIC) and probabilistic data association (PDA) multiuser detector (PDA-MUD). We prove that ISDIC is equivalent to PDA-MUD, and give the block-wise implementation of them. We also present a soft interference cancellation algorithm for the polynomial expansion linear detector. With its low complexity, simple implementations, and impressive performance offered by iterative soft-decision processing, it is an attractive candidate to deliver efficient reception solutions to practical wireless transmission systems. Simulation comparisons of the new method with ISDIC are presented under the frequency selective channels.

MIMO OFDM Frequency Offset Estimator with Low Computational Complexity

This paper addresses a low complexity frequency offset estimator for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems over frequency selective fading channels. By exploiting the good correlation property of the training sequences, which are constructed from the Chu sequence, carrier frequency offset (CFO) estimation is obtained with great complexity reduction through factor decomposition for the derivative of the cost function. The CFO estimates variance and Cramer-Rao bound (CRB) are developed to optimize the parameter of the simplified estimator and also to evaluate the estimation performance. Simulation results verify the good performance of the training-assisted CFO estimator.

Research of synchronization and training sequence design for cooperative D2D communications underlaying hyper-cellular networks

In this paper, new training sequence structure with adjustable parameters is proposed for the multiple timing offsets and frequency offsets estimation of cooperative device-to-device (D2D) systems underlaying hyper-cellular networks. By using the proposed training sequences, timing offsets can be estimated using a cross-correlation approach with good performance, and frequency offsets can be estimated using a signal subspace decomposition approach with low complexity. By designing the parameters of the proposed training sequences properly, estimation outliers can be effectively avoided.

SNR Degradation due to Carrier Frequency Offset in Amplify-and-Forward Relay System for Fading Channels

In this paper, we analyze signal-to-noise ratio (SNR) performance of amplify-and-forward (AF) relay system in the presence of carrier frequency offset (CFO) for fading channels. The expression for the average SNR is derived under one-relay-node scenario, and is further extended to multiple-relay-node scenario. It is shown that the SNR is very sensitive to CFO and the sensitivity of SNR to CFO is mainly determined by the power of the corresponding link channel and gain factor. The analytical results are validated through Monte Carlo simulations for both flat and frequency-selective fading channels. Keywords—SNR, CFO, amplify-and-forward, OFDM

Pattern Division Multiple Access with Large-Scale Antenna Array

In this paper, pattern division multiple access with large-scale antenna array (LSA-PDMA) is proposed as a novel non-orthogonal multiple access (NOMA) scheme. In the proposed scheme, pattern is designed in both beam domain and power domain in a joint manner. At the transmitter, pattern mapping utilizes power allocation to improve the system sum rate and beam allocation to enhance the access connectivity and realize the integration of LSA into multiple access spontaneously. At the receiver, hybrid detection of spatial filter (SF) and successive interference cancellation (SIC) is employed to separate the superposed multiple-domain signals. Furthermore, we formulate the sum rate maximization problem to obtain the optimal pattern mapping policy, and the optimization problem is proved to be convex through proper mathematical manipulations. Simulation results show that the proposed LSA-PDMA scheme achieves significant performance gain on system sum rate compared to both the orthogonal multiple access scheme and the power-domain NOMA scheme.

Energy Efficient Power Allocation in Massive MIMO Systems Based on Standard Interference Function

In this paper, energy efficient power allocation for downlink massive MIMO systems is investigated. A constrained non-convex optimization problem is formulated to maximize the energy efficiency (EE), which takes into account the quality of service (QoS) requirements. By exploiting the properties of fractional programming and the lower bound of the user data rate, the non-convex optimization problem is transformed into a convex optimization problem. The Lagrangian dual function method is utilized to convert the constrained convex problem into an unconstrained convex one. Due to the multi-variable coupling problem caused by the intra-user interference, it is intractable to derive an explicit solution to the above optimization problem. Exploiting the standard interference function, we propose an implicit iterative algorithm to solve the unconstrained convex optimization problem and obtain the optimal power allocation scheme. Simulation results show that the proposed iterative algorithm converges in just a few iterations, and demonstrate the impact of the number of users and the number of antennas on the EE.