Muhammad S. Sohail

Enhanced channel estimation using Cyclic Prefix in MIMO STBC OFDM sytems

Channel estimation is an important part of any receiver design. This paper presents an improved iterative joint channel estimation and data detection algorithm for Space Time Block Coded (STBC) MIMO OFDM systems in fast fading environments. The algorithm utilizes both time and frequency correlation information. We show how the Cyclic Prefix (CP) can be used to enhance the joint channel estimation and data detection process. We present two variations of the Expectation Maximization (EM) based Forward Backward (FB) Kalman filter algorithm utilizing the CP information and provide their performance comparison. Simulation results show that the proposed use of CP to aid the EM based FB Kalman algorithm results in improved performance.

An EM based frequency domain channel estimation algorithm for multi-access OFDM systems

Channel estimation is an important prerequisite for receiver design. In this paper we present a semi-blind low complexity frequency domain based channel estimation algorithm for multi-access Orthogonal Frequency Division Multiplexing (OFDM) systems. Our algorithm is based on eigenvalues interpolation and makes a collective use of data and channel constraints. We exploit these constraints to derive a frequency domain maximum a posteriori (MAP) channel estimator. Furthermore, we develop a data aided (expectation maximization based) estimator incorporating frequency correlation information. The estimator is further enhanced by utilizing the time correlation information through a forward backward (FB) Kalman filter. We also explore various implementation for the FB Kalman filter. The simulation results are provided validating the applicability of the proposed algorithm.

Narrowband Interference Mitigation in SC-FDMA Using Bayesian Sparse Recovery

This paper presents a novel narrowband interference (NBI) mitigation scheme for single carrier-frequency division multiple access systems. The proposed NBI cancellation scheme exploits the frequency-domain sparsity of the unknown signal and adopts a low complexity Bayesian sparse recovery procedure. At the transmitter, a few randomly chosen data locations are kept data free to sense the NBI signal at the receiver. Furthermore, it is noted that in practice, the sparsity of the NBI signal is destroyed by a grid mismatch between the NBI sources and the system under consideration. Toward this end, first, an accurate grid mismatch model is presented that is capable of assuming independent offsets for multiple NBI sources, and second, the sparsity of the unknown signal is restored prior to reconstruction using a sparsifying transform. To improve the spectral efficiency of the proposed scheme, a data-aided NBI recovery procedure is outlined that relies on adaptively selecting a subset of data-points and using them as additional measurements. Numerical results demonstrate the effectiveness of the proposed scheme for NBI mitigation.

Low-Complexity Blind Equalization for OFDM Systems With General Constellations

This paper proposes a low-complexity algorithm for blind equalization of data in orthogonal frequency division multiplexing (OFDM)-based wireless systems with general constellations. The proposed algorithm is able to recover the transmitted data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information about the channel and thus does not suffer from latency normally associated with blind methods. The paper demonstrates how to reduce the complexity of the algorithm, which becomes especially low at high signal-to-noise ratio (SNR). Specifically, it is shown that in the high SNR regime, the number of operations is of the order O(LN), where L is the cyclic prefix length and N is the total number of subcarriers. Simulation results confirm the favorable performance of the proposed algorithm.

Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach

This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations.

Mean Weight Behavior of the NLMS Algorithm for Correlated Gaussian Inputs

This letter presents a novel approach for evaluating the mean behavior of the well known normalized least mean squares (NLMS) adaptive algorithm for a circularly correlated Gaussian input. The mean analysis of the NLMS algorithm requires the calculation of some normalized moments of the input. This is done by first expressing these moments in terms of ratios of quadratic forms of spherically symmetric random variables and finding the cumulative density function (CDF) of these variables. The CDF is then used to calculate the required moments. As a result, we obtain explicit expressions for the mean behavior of the NLMS algorithm.

A non-iterative channel estimation and equalization method for TDS-OFDM systems

Channel estimation is a significant component of any receiver implementation. This paper presents a fast non-iterative channel estimation and equalization algorithm for TDS-OFDM systems. The proposed method is a hybrid of CP-OFDM and ZP-OFDM systems. By discarding the initial portion of the PN-sequence that absorbs all the ISI, the channel can be estimated from the remaining PN-sequence by using the concepts of CP-OFDM. After completely removing the current PN-sequence and the ISI from the PN-sequence of the previous symbol, the concepts of ZP-OFDM can be utilized to detect the data using single tap equalization. Moreover, the proposed method involves no latency and thus is applicable to fast fading channels. The performance of the proposed method is demonstrated by simulation over two Brazilian field tests channels on DTTB.

Analyzing IEEE 802.11 DCF for FU-FB Systems under Multipath Fading Channels Using TUA

This paper presents the performance analysis of IEEE 802.11 DCF (distributed coordination function) using tagged user analysis (TUA). Performance of IEEE 802.11 DCF has been widely studied, mostly using Markov chains. Markov analysis becomes practically intractable for systems with finite users/stations (STAs) each having a finite buffer capacity. The analysis becomes even complicated under realistic channel models where multipath fading is encountered. This paper uses TUA, an approximate technique, for the analysis of quality of service (QoS) parameters like system throughput, wait delay, response time, packet blocking probability and average queue size. Simulation results show that TUA accurately predicts the performance of IEEE 802.11 DCF.

Application of Tagged User Analysis to FU-FB Slotted ALOHA Performance over Frequency Selective Fading Channels

Slotted ALOHA (S-ALOHA) is a simple random multiple access technique used in many data and cellular networks for random access phase. We use tagged user analysis (TUA), an approximate analysis technique, for evaluation of performance parameters of finite user finite buffer (FU-FB) S-ALOHA system over frequency selective fading channels. We also derive analytical expressions for several performance metrics. TUA does not suffer from the complexity issues normally associated with Markov model, where a state space of complexity in the exponential order of buffer size and the number of users must be solved. On comparison of analytical results with simulations, it is observed that TUA is able to accurately analyze the system for a much lower computational cost.

Slotted ALOHA performance for FU-FB in frequency selective fading environment

Slotted ALOHA is a simple and straightforward random multiple access technique, which has been used extensively in data and cellular networks as the protocol for random access. The complexity of state space-based analysis methods for finite user finite buffer systems increases exponentially with buffer size and number of users. The presence of multipath frequency selective fading channel further adds to the complexity, making the analysis practically intractable. This paper uses an approximate analysis technique called tagged user analysis TUA to analyze the performance parameters of slotted ALOHA over multipath and frequency selective fading channels for finite user finite buffer systems. In TUA, the steady state system performance is evaluated from the analysis of a single user. Moreover, the state flow graph of TUA has just four states, thus reducing the complexity of the analysis. Simulation results confirm the validity of the TUA analysis. Copyright