We present novel soft-input soft-output (SISO) multiple-input multiple-output (MIMO) detectors based on the Chase detection principle [1] in the context of iterative and decoding (IDD). The proposed detector complexity is linear in the signal modulation constellation size and the number of spatial streams. Two variants of the SISO detector are developed, referred to as SISO B-Chase and SISO L-Chase. An efficient method is presented that uses the decoder output to modulate the signal constellation decision boundaries inside the detector leading to the SISO detector architecture. The performance of these detectors significantly improves with just a few number of IDD iterations. The effect of transmit and receive antenna correlation is simulated. For the high-correlation case, the superiority of SISO B-Chase over the SISO L-Chase is demonstrated.

We analyze the EVM performance of OFDM-based relay-assisted amplify-and-forward systems in the presence of I/Q imbalance. We show analytically that the MRC detector suffers from an error floor due to mutual interference between image subcarriers. We prove analytically that a simple zero-forcing two-tap per subcarrier equalizer eliminates this error floor. Simulation results demonstrate its significant performance gain over MRC detection for different I/Q imbalance levels, SNR levels, and relay positions.

We investigate the spectrum sensing problem in orthogonal frequency-division multiplexing-based cognitive radio networks under I/Q imbalance. We start by deriving the likelihood ratio test in the presence of I/Q imbalance at the analog front-ends of both the primary and secondary users. In addition, we derive closed-form expressions for the probabilities of detection and false alarm and the receiver operating characteristics and examine their dependence on both transmit and receive I/Q imbalance levels. Furthermore, we compare the performance of the likelihood ratio test with that of the energy detector and demonstrate the superiority of the former over the latter. Next, we generalize our analysis to the blind case where we derive simple closed-form expressions for the generalized likelihood ratio test and its false alarm probability as a function of the received signal only, i.e. without requiring any knowledge of the primary-to-secondary channel response, noise statistics, or I/Q imbalance parameters. Our results demonstrate that the correlation properties of the primary user's signal induced by transmit I/Q imbalance are signal features that can be exploited in a blind fashion at the secondary user to enhance the detection probability significantly compared to the conventional energy detector.

We study the problem of per-stream joint maximum sum-rate (MSR) precoder and minimum mean-squared error (MMSE) equalizer design for interference alignment in the multi-input multi-output interference channel. We consider the general case of more than three users with more than one stream per user. We propose a new generalized iterative algorithm which directly maximizes the average overall sum-rate without assuming the signal-to-noise ratio to be infinite. The receivers' implementation complexity increases proportional to the square of the number of equalizer taps which becomes prohibitive as the network size increases. To address this issue, we examine the performance-complexity tradeoffs involved in a sparse equalizer design. Our numerical results demonstrate that, for the full-complexity MMSE equalizer design, our proposed algorithm achieves higher overall sum-rate compared to previously proposed interference alignment algorithms. In addition, we reduce the MMSE linear equalizer complexity by 30% while limiting the sum-rate loss to about 10%, at most, compared to the full-complexity design.

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.

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.

We analyze the outage performance of relay-assisted amplify-and-forward systems under uncompensated I/Q imbalance effects and derive accurate analytical approximations for both cases. In addition, we compare the outage probability for amplify-and-forward systems 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. Furthermore, we propose a low-complexity receiver-based digital baseband I/Q imbalance compensation scheme for the amplify-and-forward mode. Numerical results show its performance superiority to the conventional maximal-ratio combining scheme even under imperfect channel state information (CSI).

In this paper, we present a novel approach for the design of rate-maximizing channel shortening detectors with soft feedback side information for frequency-selective channels. The detector is a soft-input soft-output detector and constitutes one of the components of an iterative receiver. The design optimization is performed from an information-theoretic perspective where we maximize the achievable rate during each step of the iterative process. Our proposed detector consists of a front-end filter whose coefficients are given in closed form in addition to a convex optimization procedure which provides the branch labels of the trellis and the feedback filter coefficients. The detector can be implemented as a BCJR-type algorithm operating on a trellis where the number of states is a user-defined parameter.

We propose an iterative joint detection and phase noise compensation scheme for single-carrier frequency-division-multiple-access systems. Our proposed scheme does not require any pilots in tracking the phase noise and assumes no knowledge about the phase noise model to avoid model mismatch problems. Simulation results show the effectiveness of our proposed scheme in compensating phase noise effects with only few iterations.

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 user's 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.

We derive an analytical expression for the error vector magnitude under carrier frequency offset (CFO) and joint transmit-receive phase noise (PN). CFO and PN are major oscillator impairments in direct-conversion transceivers. As a case study, we consider multi-user uplink transmission with single- carrier frequency-division-multiple access as in the long-term evolution standard. The derived expression reveals an interesting relationship between the subcarrier mapping scheme and the immunity to CFO and PN. Furthermore, we verify the accuracy of our derived expression through Monte-Carlo simulations for various CFO and PN levels.

We propose two novel algorithms based on compressive sensing theory to estimate and cancel narrow band interference (NBI) and estimate the channel in the presence of NBI for multiple-antenna orthogonal frequency division multiplexing systems. We also consider the case of multiple asynchronous NBI signals experiencing unknown independent frequency- selective fading channels. Simulation results demonstrate the effectiveness of our proposed algorithm in mitigating NBI and approaching the interference-free performance limit over practical ranges of NBI power and spectral widths.

In this paper, we present a new approach to design sparse finite impulse response (FIR) equalizers. We consider linear equalizers, decision feedback equalizers (DFEs), and multiple-input multiple-output DFEs. We formulate greedy and convex-optimization-based solutions for sparse FIR equalizers given a maximum allowable loss in the decision-point signal-to-noise ratio. Simulation results demonstrate substantial reductions in the number of equalizer taps at small performance loss.

This paper addresses spectrally-efficient multiantenna multi-carrier 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 analytically. 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.

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.

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.

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 signal's 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.

The complexity of maximum-likelihood (ML) or maximum-a-posteriori (MAP) detectors grows exponentially with the number of channel impulse response (CIR) taps. This makes the implementation of ML or MAP detectors over broadband channels with long CIRs prohibitively complex. Channel shortening is a widely-used technique to solve this problem by implementing a front-end finite impulse response (FIR) filter to shorten the CIR. In this paper, we propose a novel approach based on compressive sensing theory to design low-complexity FIR channel shortening filters. The superiority of our new approach is proven analytically and illustrated via simulations.

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.

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.

In this paper we propose a novel technique for hybrid automatic repeat request (HARQ) systems where turbo codes are used as the forward error correction (FEC) techniques. This technique uses the histogram of the soft values generated by the turbo decoder to control the size and the contents of the retransmissions needed when the packet can not be decoded correctly. These soft values represent the reliabilities of the information bits; hence the proposed technique is a reliability-based (RB) HARQ technique. The proposed technique is compared to the conventional RBHARQ and the conventional rate compatible punctured turbo (RCPT) codes, and is shown to achieve higher throughput and/or less number of transmissions.

In this paper we study diversity combining for turbo-coded frequency hopped spread-spectrum (FH/SS) communication systems in the presence of fading and partial band interference. For a fixed channel to information bit rate we compare different diversity order and code rate combinations for coherent binary phase shift keying (CBPSK) and non-coherent binary frequency shift keying (NCBFSK). We find that it is always better to use a low-rate code and no repetition for both CBPSK and NCBFSK. We apply a well-known approximation to the LLR for NCBFSK and find that it results in very similar performance to the exact LLR. We also propose a simple method for signal-to-noise ratio (SNR) estimation in NCBFSK without training symbols that offers performance near that of the case of exact knowledge of the SNR even for small hop sizes. In the case of CBPSK we propose an iterative method for estimating the SNR, also without training symbols, that offers performance near that of the case of perfect knowledge of the SNR when there is no interference, but otherwise requires large hop sizes to accurately estimate the SNR.