Ahmad Gomaa

A Sparsity-Aware Approach for NBI Estimation in MIMO-OFDM

In this paper, we present a novel approach based on compressive sensing theory to estimate and mitigate asynchronous narrow-band interference (NBI) in orthogonal frequency division multiplexing systems with multiple transmit and/or multiple receive antennas. We consider the practical scenarios where one or multiple asynchronous NBI signals experience fast fading and/or frequency-selective fading channels. Furthermore, we propose a novel technique for estimating the desired signals channel in the presence of unknown NBI. Our approach does not require any prior information about the NBI. Simulation results demonstrate the effectiveness of our proposed techniques in mitigating NBI and approaching the interference-free performance limit over practical ranges of NBI power levels, spectral widths, and mobility levels.

OFDM AF Relaying Under I/Q Imbalance: Performance Analysis and Baseband Compensation

We analyze the outage performance of half-duplex amplify-and-forward relaying in an OFDM system with MRC detection in the presence of I/Q imbalance and compare it with that of the direct transmission mode. Both analytical and numerical results demonstrate that the direct mode can outperform the amplify-and-forward mode even under moderate levels of uncompensated I/Q imbalance. The cross-over I/Q imbalance levels are determined analytically to be inversely proportional to the cube of the signal constellation size. In addition, we present a low-complexity receiver-based digital baseband I/Q imbalance compensation scheme for the amplify-and-forward mode and analyze its EVM performance. Furthermore, we derive accurate analytical approximations for the EVM performance as a function of relay location and I/Q imbalance level with and without compensation.

A New Design Framework for Sparse FIR MIMO Equalizers

In this paper, we propose a new framework for the design of sparse finite impulse response (FIR) equalizers. We start by formulating greedy and convex-optimization-based solutions for sparse FIR linear equalizer tap vectors given a maximum allowable loss in the decision-point signal-to-noise ratio. Then, we extend our formulation to decision feedback equalizers and multiple-antenna systems. This is followed by further generalization to the channel shortening setup which is important for communication systems operating over broadband channels with long channel impulse responses. We propose a novel approach to design a sparse target impulse response. Finally, as an application of current practical interest, we consider self far-end crosstalk cancellation on vectored very high-speed digital subscriber line systems for cellular backhaul networks.

Training Signal Design and Tradeoffs for Spectrally-Efficient Multi-User MIMO-OFDM Systems

In this paper, we design MMSE-optimal training sequences for multi-user MIMO-OFDM systems with an arbitrary number of transmit antennas and an arbitrary number of training symbols. It addresses spectrally-efficient uplink transmission scenarios where the users overlap in time and frequency and are separated using spatial processing at the base station. The robustness of the proposed training sequences to residual carrier frequency offset and phase noise is evaluated. This analysis reveals an interesting design tradeoff between the peak-to-average power ratio of a training sequence and the increase in channel estimation mean squared error over the ideal case when these two impairments are not present.

A Compressive Sensing Approach to NBI Cancellation in Mobile OFDM Systems

We propose a novel algorithm based on compressive sensing (CS) theory to estimate narrow band interference (NBI) signals experiencing time-varying frequency-selective fading channels in orthogonal frequency division multiplexing (OFDM) systems. In addition, we investigate the case of asynchronous jamming where there is a frequency offset between the NBI and desired signals. Furthermore, we propose a reduced-complexity implementation for our proposed algorithm with negligible performance loss. Finally, we show that our proposed approach can be applied to both cyclic-prefix and zero-padding OFDM systems. Simulation results show the effectiveness of our proposed algorithm in mitigating NBI.

Likelihood-based spectrum sensing of OFDM signals in the presence of Tx/Rx I/Q imbalance

We consider the spectrum sensing problem in orthogonal frequency-division multiplexing-based cognitive radio networks under I/Q imbalance. We derive the likelihood ratio test in the presence of colored noise and I/Q imbalance at the analog front-ends of both of the primary and secondary users. Furthermore, we derive the probabilities of detection and false alarm and develop the receiver operating characteristics. We also examine the impacts of both transmit and receive I/Q imbalance on the performance of the likelihood ratio test. We compare the performance of our likelihood ratio test with that of the energy detector through extensive simulations and show the superiority of the former over a wide range of signal-to-noise ratios.

Multi-User SC-FDMA Systems under IQ Imbalance: EVM and Subcarrier Mapping Impact

In this paper, we derive an analytical expression for the error vector magnitude (EVM) under joint transmit-receive Inphase-Quadrature imbalance (IQI). IQI is a major radio frequency impairment in direct- conversion transceivers. We consider multi-user uplink transmission with single-carrier frequency- division-multiple access as in the long-term evolution standard. The derived EVM expression reveals an interesting relationship between the spectral allocation of a users subcarriers and the immunity of this user to IQI. Furthermore, we verify the accuracy of our derived EVM expression through Monte-Carlo simulations for various IQI levels.

Two novel compressed-sensing algorithms for NBI detection in OFDM systems

We propose two novel algorithms based on compressed-sensing theory to estimate and cancel narrow band interference (NBI) in orthogonal frequency division multiplexing (OFDM) systems. Simulation results demonstrate the effectiveness of our proposed algorithms in estimating the NBI frequency support and approaching the performance with no NBI.

Phase noise in asynchronous SC-FDMA systems: Performance analysis and data-aided compensation

Carrier frequency offset (CFO) and phase noise (PN) are major oscillator impairments in direct-conversion transceivers, and single-carrier frequency-division multiple access (SC-FDMA) is the uplink transmission scheme in the Long-Term Evolution (LTE) standard. We derive a new analytical expression for the normalized mean square error (NMSE) in asynchronous SC-FDMA systems under CFO and joint transmit-receive PN. The derived NMSE expression reveals an interesting cross-layer relationship between the subcarrier mapping scheme at the medium-access-control layer and the immunity to CFO and PN at the physical layer. Furthermore, we propose an iterative reduced-complexity joint decoding and PN compensation scheme that does not require any pilots in PN tracking and exploits the low-pass nature of the PN process without assuming a specific PN model. Simulation results show the effectiveness of our proposed digital baseband compensation scheme in PN mitigation.

Data-Aided I/Q Imbalance Estimation and Compensation in OFDM Systems

We propose a novel approach for data-aided estimation of the mixer gain and phase imbalances in the analog front-end of direct-conversion receivers. We estimate the inphase and quadrature imbalance (IQI) parameters isolated from the fading channel estimate and use the estimated IQI parameters for time-domain compensation. The motivation behind this approach is the scenario where the training symbols used for IQI estimation are transmitted from different antenna ports than those used for data transmission. In this scenario, the conventional composite IQI and channel estimate cannot be used for signal detection because the training and data symbols experience different channels. An example of this scenario is the long-term evolution (LTE) standard where the synchronization and broadcast signals are transmitted from different antenna ports than those used for data transmission. Numerical results show that our approach achieves up to 10 dB improvement using only two training symbols.