Hung Nguyen-Le

RLS-Based Joint Estimation and Tracking of Channel Response, Sampling, and Carrier Frequency Offsets for OFDM

This paper proposes a pilot-aided joint channel estimation and synchronization scheme for burst-mode orthogonal frequency division multiplexing (OFDM) systems. Based on the received signal samples containing pilot tones in the frequency domain, a cost function that includes the carrier frequency offset (CFO), sampling clock frequency offset (SFO) and channel impulse response (CIR) coefficients is formulated and used to develop an accompanying recursive least-squares (RLS) estimation and tracking algorithm. By estimating the channel CIR coefficients instead of the channel frequency response in the frequency domain, the proposed scheme eliminates the need for an IFFT block while reducing the number of parameters to be estimated, leading to lower complexity without sacrificing performance and convergence speed. Furthermore, a simple maximum-likelihood (ML) scheme based on the use of two long training symbols (in the preamble) is developed for the coarse estimation of the initial CFO and SFO to suppress dominant ICI effects introduced by CFO and SFO and to enhance the performance and convergence of the fine RLS estimation and tracking. Simulation results demonstrate that, over large ranges of CFO and SFO values, the proposed pilot-aided joint channel estimation and synchronization scheme provides a receiver performance that is remarkably close to the ideal case of perfect channel estimation and synchronization in both AWGN and Rayleigh multipath fading channels.

Joint Channel Estimation and Synchronization for MIMO–OFDM in the Presence of Carrier and Sampling Frequency Offsets

A pilot-aided scheme is proposed for the joint estimation and tracking of channel impulse response (CIR), carrier frequency offset (CFO) and sampling frequency offset (SFO) in burst mode, multiple-input-multiple-output (MIMO), and orthogonal frequency division multiplexing(OFDM) systems. First, a received signal model that takes into account nonlinear CFO/SFO effects is formulated. Then, based on the derived signal model and the received multicarrier signal samples containing the pilot tones in the frequency domain, an objective function that includes MIMO CIR, CFO, and SFO is introduced to develop a vector recursive-least-square (RLS)-based joint channel estimation and synchronization algorithm. The analysis and simulation results show that, over the large ranges of the CFO and SFO values, the proposed estimation and tracking scheme offers fast convergence, high stability, and a near-optimum receiver performance that is remarkably close to the ideal performance in the case of perfect channel estimation and synchronization over quasi-static Rayleigh multipath fading channels.

Pilot-Aided Joint CFO and Doubly-Selective Channel Estimation for OFDM Transmissions

This paper studies the problem of pilot-aided joint carrier frequency offset (CFO) and channel estimation using Fisher and Bayesian approaches in orthogonal frequency division multiplexing (OFDM) transmissions over time- and frequency-selective (doubly selective) channels. In particular, the recursive-least-squares (RLS) and maximum-likelihood (ML) techniques are used to facilitate the Fisher estimation implementations. For the Bayesian estimation, the maximum-a-posteriori (MAP) principle is employed in formulating the joint estimation problem. With known channel statistics, the MAP-based estimation is expected to provide better performance than the RLS- and ML-based ones. To avoid a possible identifiability issue in the joint estimation problem, various basis expansion models (BEMs) are deployed as fitting parametric models for capturing the time-variation of the channels. Numerical results and related Bayesian Cramér Rao bounds (BCRB) demonstrate that the deployment of BEMs is able to alleviate performance degradation in the considered estimation techniques using the conventional block-fading assumption over time-varying channels. Among the considered schemes, the MAP-based estimation using the discrete prolate spheroidal (DPS) or Karhuen Loève (KL) basis functions would be the best choice that can provide mean-squared-error (MSE) performance comparable to BCRB in low signal-to-noise ratio (SNR) conditions (e.g., coded OFDM transmissions).

Block-Diagonalization Precoding in a Multiuser Multicell MIMO System: Competition and Coordination

This paper studies a multiuser multicell system where block-diagonalization (BD) precoding is utilized on a per-cell basis. We examine and compare the multicell system under two operating modes: competition and coordination. In the competition mode, the paper considers a strategic non-cooperative game (SNG), where each base-station (BS) greedily determines its BD precoding strategy in a distributed manner, based on the knowledge of the inter-cell interference at its connected mobile-stations (MS). Via the game-theory framework, the existence and uniqueness of a Nash equilibrium in this SNG are subsequently studied. In the coordination mode, the BD precoders are jointly designed across the multiple BSs to maximize the network weighted sum-rate (WSR). Since this WSR maximization problem is nonconvex, we consider a distributed algorithm to obtain at least a locally optimal solution. Finally, we extend our analysis of the multicell BD precoding to the case of BD-Dirty Paper Coding (BD-DPC) precoding. We characterize BD-DPC precoding game for the multicell system in the competition mode and propose an algorithm to jointly optimize BD-DPC precoders for the multicell system in the coordination mode. Simulation results show significant network sum-rate improvements by jointly designing the BD or BD-DPC precoders across the multicell system in the coordination mode over the competition mode.

Cognitive underlay communications with imperfect CSI: Network design and performance analysis

This paper is concerned with performance analysis of cognitive underlay partial relay networks with imperfect channel state information (CSI). To assure the required quality of service (QoS) at primary receivers, transmit power at secondary nodes is adjusted by using a back-off power scheme under imperfect CSI condition. The back-off power strategy reduces transmit power at secondary nodes and in turn degrades the secondary network performance. Under the performance tradeoff between primary and secondary networks, this paper considers the use of multiple antennas at destination node and partial relay selection to enhance the secondary network performance without sacrificing the performance of the primary network. To justify the benefit of using the network design, several analytical and simulated results of the network performance are provided under various system settings.

ML-based follower jamming rejection in slow FH/MFSK systems with an antenna array

The jamming robustness of frequency hopping (FH) systems with M-ary frequency shift keying (MFSK) modulation may be potentially neutralized by a follower partial-band jammer. In this paper, a maximum likelihood (ML)-based algorithm that uses a two-element array is proposed for joint follower jamming rejection and symbol detection in slow FH/MFSK systems over quasi-static flat Rayleigh fading channels. The algorithm is derived by treating both the received jamming components and the unknown data symbols as deterministic quantities to be jointly estimated in an integrated ML operation. In addition, an approximate expression for the symbol error rate (SER) of the proposed scheme is derived when BFSK signaling is employed in a jamming dominant scenario. Analytical and simulated results show that the proposed approach is able to remove jamming and outperform the conventional and sample matrix inversion (SMI)-based beam-formers in the presence of a follower partial-band jammer.

Cascaded doubly-selective channel estimation in multi-relay AF OFDM transmissions

This paper studies the problem of channel estimation in amplify-and-forward (AF) multi-relay transmissions over time- and frequency-selective (doubly selective) channels. To avoid two separate channel estimation processes of source-to-relay and relay-to-destination links, a cascaded doubly selective channel model is formulated to characterize the source-to-relay-to-destination (SRD) channel. Time-varying SRD channel gains are projected onto different basis expansion functions to attain dimension reduction in the formulated channel model. In estimating the cascaded SRD channel responses at the destination, the presence of multiple relays gives rise to the ambiguity problem due to the use of a single pilot signal transmitted from the source. To circumvent this problem, time-variant amplifying factors at relays are introduced to be used in maximum-likelihood-based cascaded multi-relay channel estimation. Simulation results show that basis expansion models (BEMs) and time-variant amplifying factors can efficiently facilitate a single estimation process of different cascaded doubly selective SRD channels in a multi-relay system. Furthermore, for a fixed pilot overhead, a relationship between space diversity gains (with multiple relays) and channel estimation accuracy is also numerically illustrated.

Iterative Receiver Design With Joint Doubly Selective Channel and CFO Estimation for Coded MIMO-OFDM Transmissions

This paper is concerned with the problem of turbo (iterative) processing for joint channel and carrier frequency offset (CFO) estimation and soft decoding in coded multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexing (OFDM) systems over time- and frequency-selective (doubly selective) channels. In doubly selective channel modeling, a basis expansion model (BEM) is deployed as a fitting parametric model to reduce the number of channel parameters to be estimated. Under pilot-aided Bayesian estimation, CFO and BEM coefficients are treated as random variables to be estimated by the maximum a posteriori technique. To attain better estimation performance without sacrificing spectral efficiency, soft bit information from a soft-input-soft-output (SISO) decoder is exploited in computing soft estimates of data symbols to function as pilots. These additional pilot signals, together with the original signals, can help to enhance the accuracy of channel and CFO estimates for the next iteration of SISO decoding. The resulting turbo estimation and decoding performance is enhanced in a progressive manner by benefiting from the iterative extrinsic information exchange in the receiver. Both extrinsic information transfer chart analysis and numerical results show that the iterative receiver performance is able to converge fast and close to the ideal performance using perfect CFO and channel estimates.

Joint Channel Estimation and Synchronization with Inter-carrier Interference Reduction for OFDM

This paper proposes a pilot-aided joint channel estimation and synchronization scheme for burst-mode orthogonal frequency division multiplexing (OFDM) systems. The scheme eliminates the need of an IFFT block while keeping the low number of parameters to be estimated for low complexity without sacrificing the performance and convergence speed. For fast convergence and high performance, we develop a linearized cost function of the carrier frequency offset (CFO), sampling clock frequency offset (SFO) and channel impulse response (CIR) coefficients based on received signal samples and pilot tones in frequency domain and the corresponding recursive least square (RLS) estimation and tracking algorithm. For channel responses, CIR coefficients are estimated to benefit their low number and then transformed to the channel transfer function in order to keep low complexity. The ICI introduced by rotation due to CFO and SFO is analyzed and modeled, and a simple maximum-likelihood (ML) scheme based on the preamble is developed for coarse estimation of initial CFO and SFO values to be used in suppression of dominant ICI effects and in fine RLS estimation and tracking. Simulation results demonstrate that, in large practical ranges of CFO and SFO values, the proposed pilot-aided joint channel estimation and synchronization scheme provides a receiver performance remarkably close to the ideal case of perfect channel estimation and synchronization.

Joint Synchronization and Channel Estimation for OFDM Transmissions over Doubly Selective Channels

This paper proposes a pilot-aided joint channel estimation and synchronization scheme for burst-mode orthogonal frequency division multiplexing (OFDM) systems over time- and frequency-selective (doubly selective) channels. Based on the basis expansion model (BEM) for representing doubly-selective channels, a least-square (LS) cost function of carrier frequency offset (CFO) and BEM coefficients is formulated for the joint estimation problem. By applying the first-order Taylor series expansion, an approximately linearized estimation error is obtained to facilitate a recursive least-square (RLS)-based joint CFO and BEM estimation with the aid of pilot OFDM symbols. Simulation results demonstrate that, over a wide range of Doppler spreads, the proposed estimation scheme offers a high robustness against the time variation of fast fading channels and outperforms the linear minimum mean-square (LMMSE) algorithm [6] using CFO estimates provided by the CFO estimation technique in [11].