Intercarrier Interference Suppression for OFDMA Uplink in Time- and Frequency-Selective Fading Channels

To cope with interference in three-cell multiple relay systems, this paper proposes schemes that detect two users' signals while linearly suppressing one remaining user's signal. The proposed schemes do not require channel state information (CSI) feedback and can drastically reduce the computational complexity compared to the maximum likelihood detection (MLD), which is the optimal signal detection and detects all three users' signals. As one proposed scheme, a minimum mean-squared error (MMSE) scheme estimates weight coefficients for the interference suppression under the MMSE criterion, and thus needs to estimate CSI of all the users by using all the three preamble sequences like MLD. Another proposed scheme called a recursive least squares (RLS) scheme directly estimates the weight coefficients by the RLS algorithm. In contrast with the MMSE scheme and MLD, the RLS scheme needs to know only two preamble sequences and thus is more feasible. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions show that the proposed schemes can maintain good bit error rate in contrast with a conventional scheme for two-cell systems, and that the RLS scheme can outperform the MMSE scheme with estimated CSI when decision-directed estimation with error selection is applied.

In orthogonal frequency division multiplexing (OFDM) systems, channel variations within an OFDM block destroy orthogonality between subcarriers, resulting in intercarrier interference (ICl), which increases an error floor in proportional to normalized Doppler frequency. To mitigate the effects of channel variations, many schemes have been proposed, but they are computationally complex or at the price of sacrificing spectral efficiency. In this paper, we first provide an ICI analysis in both time- and frequency-domain while existing literatures analyze the ICI effects mainly in the frequency domain. Based on this analysis, we then propose a novel ICI suppression technique, which uses iterative ICI cancellation in time domain and has a computational complexity that is linear in the OFDM symbol length. Channel estimation in rapidly time-varying scenarios is critical for ICl suppression and coherent demodulation. We also propose a scheme for estimating the channel parameters varying within an OFDM block. Along with the channel estimation scheme, we investigate the issue of optimum pilot tone placement. Theoretical analysis and simulation results show that the proposed ICl suppression method and channel estimation scheme have low computational complexity and good performance for most Doppler frequency of practical importance.

Multiple-input/multiple-output (MIMO) frequency selective fading channels introduce both the intersymbol interference (ISI) and the inter-(sub)channel interference (ICI) that are the major performance limiting factors for MIMO wireless data communications. This paper focuses on joint suppression of such two interferences in receiver design under the criterion of the minimum mean-squared error (MMSE). The well-known Kalman filtering arises as a natural design tool to achieve the optimum joint suppression of the ISI and ICI in the sense of MMSE that results in a two-stage design method that suppresses the ISI and ICI in series. Specifically, a state-space solution is derived for the optimum decision-feedback equalizer (DFE) based on temporal Kalman filtering, and is shown to be equivalent to a conventional finite length DFE for ISI suppression. A novel spatial Kalman filtering scheme is proposed as the second stage to successively cancel the ICI. It is shown that the proposed two-stage method yields the realizable and optimum joint ISI and ICI suppression, while it admits lower computational complexity than the conventional finite length DFE for ISI suppression and the MMSE V-BLAST receiver for ICI suppression. The results are applicable to any linear channels that admit state-space realizations, including MIMO frequency selective time-varying channels, and are thus the most general. Simulation results show the effectiveness of the proposed two-stage method and its robustness to channel estimation uncertainties that may arise in practical systems.

In this paper, we propose a joint channel estimation and symbol detection (JCESD) algorithm relying on message-passing algorithms (MPA) for orthogonal frequency division multiple access (OFDMA) systems. The channel estimation and symbol detection leverage the framework of expectation propagation (EP) and belief propagation (BP) with the aid of Gaussian approximation, respectively. Furthermore, to reduce the computation complexity involved in channel estimation, the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula. Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%, compared with the traditional linear minimum mean square error (LMMSE) algorithm, and can approach to the bit error rate (BER) performance bound of perfectly known channel state information within 0.1 dB.

This paper considers the uplink of a single-cell large-scale multiuser multiple-input multiple-output (MU-MIMO) system. The transmitted data is detected by linear receivers at the base station (BS), that is, maximum ratio combining (MRC), zero-forcing (ZF) and minimum mean square error (MMSE). New non-asymptotic outage expressions that are valid for any number of BS antennas are derived. It is shown that the MMSE scheme always achieves the best outage performance, and the ZF scheme outperforms the MRC scheme in the high signal-to-noise-ratio (SNR) regime, while the opposite holds in the low SNR regime. We also demonstrate that when the number of BS antennas is very large and the number of users is fixed, the asymptotic outage probability tends to zero, providing that the channel state information (CSI) is perfect. However, if both the number of BS antennas and the number of users grow large, it would be a different matter. Extensive numerical results are presented to verify the theoretical analysis.

In this paper, a pilot-assisted minimum mean square error (MMSE) multiuser channel estimation algorithm is proposed for quasi-synchronous code-division multiple-access (CDMA) systems that undergo frequency-selective channel fading. The frequency-selective multiuser fading channel is represented as a symbol-wise time-varying chip-spaced tapped delay line filter with correlated filter taps. The multiuser channel tap coefficients at pilot symbol positions are estimated under the MMSE criterion with the help of the channel intertap correlation matrix, which is determined by the combined effects of the physical fading channel, transmit filter, and receive filter. In the development of the estimation algorithm, the channel intertap correlation matrix is deemed as an essential factor, and a novel iterative method is proposed for the joint estimation of the channel intertap correlation and filter tap timing based on the received pilot samples. Simulations show that the information of the channel intertap correlation is critical to the performance of the channel estimation, and the channel taps at different delays cannot be assumed uncorrelated for CDMA systems experiencing frequency-selective fading.

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We derive a recursion to approach the MMSE solution. We present a structure-wise and performance-wise comparison of this recursive MMSE solution with a linear PIC receiver as well as other detectors recently proposed in the literature. We show that the proposed recursive MMSE solution encompasses several known detectors in the literature as special cases.

This paper proposes an enhanced decision feedback equalizer (DFE) for filter bank multicarrier (FBMC) systems over offset quadrature amplitude modulation (OQAM) based on a minimal mean square error (MMSE) criterion. For each subcarrier, besides one feedforward (FF) filter and one feedback (FB) filter, we add two intercarrier interference (ICI)-suppressing filters, which feed back detected precursors extracted from neighboring subchannels to enhance ICI suppression in the presence of multipath channels. Our simulation results indicate our proposal makes a considerable improvement comparing with MMSE-DFE under a severe ICI and ISI scenario despite few extra costs in computational complexity.

In high mobility orthogonal frequency division multiplexing systems, subcarriers are no longer orthogonal, causing Inter-Carrier Interference (ICI). Equalization then becomes more challenging and requires an accurate estimate of the time-variant channel. In this paper, we propose a novel Minimum Mean Squared Error (MMSE) estimation of the sampled time-variant transfer function. Based on such channel estimation, we propose an iterative three step ICI mitigation technique whereby each step increases the channel estimation accuracy and, consequently, the performance of our MMSE equalization. In Step 1, we consider ICI as an additional noise term. In Step 2, we reduce the ICI at pilot positions and finally, in Step 3, we treat all estimated data symbols, obtained from Step 2, as if they were pilot symbols. We evaluate the Bit Error Ratio (BER) of our ICI mitigation technique by means of simulation and testbed measurements (up to 400 km/h). In both cases, we achieve a BER close to perfect channel knowledge and zero ICI.

In orthogonal frequency-division multiplexing (OFDM) systems, it is generally assumed that the channel response is static in an OFDM symbol period. However, the assumption does not hold in high-mobility environments. As a result, intercarrier interference (ICI) is induced and the system performance is degraded. A simple remedy for this problem is the application of the zero-forcing (ZF) and minimum mean square error (MMSE) equalizers. Unfortunately, the direct ZF method requires the inversion of an NxN ICI matrix, where N is the number of subcarriers. When N is large, the computational complexity can become prohibitively high. As for the direct MMSE method, in addition to an NxN matrix inverse, it requires an extra NxN matrix multiplication, making the required computational complexity higher compared to the direct ZF method. In this dissertation, we first propose a low-complexity ZF method to solve the problem in single-input-single-output (SISO) OFDM systems. The main idea is to explore the special structure inherent in the ICI matrix and to apply Newton's iteration for matrix inversion. With our formulation, fast Fourier transforms (FFTs) can be used in the iterative process, reducing the complexity from O(N^3) to O(Nlog_2 N) . Also, the required number of the iteration is typically one or two. We also analyze the convergence behavior of the proposed method and derive the theoretical output signal-to-interference-noise-ratio (SINR). For the MMSE method, we first reformulate the MMSE solution in a way that the extra matrix multiplication can be avoided. Similar to the ZF method, we then exploit the structure of the ICI matrix and apply Newton's iteration to reduce the complexity of the matrix inversion. For a multiple-input-multiple-output (MIMO) OFDM system, the required complexity of the ZF and MMSE methods becomes more intractable. We then manage to extend the proposed ZF and MMSE methods for SISO-OFDM systems to MIMO-OFDM systems. It turns out that the computational complexity can be reduced even more significantly. Simulation results show that the performance of the proposed methods is almost as good as that of the direct ZF and MMSE methods, while the required computational complexity is reduced dramatically. Finally, we explore the application of the proposed methods in mobility-induced ICI mitigation for OFDM multiple access (OFDMA) systems, and in carrier frequency offset (CFO) induced ICI mitigation for OFDMA uplink systems. As that in OFDM systems, the proposed methods can reduce the required computational complexity, effectively.

Satellite Communication (SatCom) systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever-increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co-channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed-form solution, we propose a beamforming algorithm based on maximizing the users’ Signal-to-Leakage-and-Noise Ratio (SLNR) served by a Low Earth Orbit (LEO) satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on Channel State Information (CSI) at the transmitter, i.e., Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF), and those only requiring the users’ locations, i.e., Switchable Multi-Beam (MB). Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per-user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed SLNR beamforming technique is able to outperform both MMSE and ZF schemes in the presented SatCom scenario.

This paper presents a novel approach, based on the whale optimization algorithm (WOA), for channel estimation in wireless communication systems. The proposed method provides a means to accurately estimate the wireless channel, while not requiring the statistical characteristics of the channel. This method uses the WOA to search for the best channel statistical characteristics toward the ultimate goal of having the smallest bit error rate (BER). The proposed approach is aimed at enhancing the efficiency of pilot-based OFDM systems under frequency-selective fading channels used in the performance testing of 5G New Radio gNodeB. In terms of BER and mean square error (MSE), the performance of the proposed WOA-based channel estimation algorithm is evaluated and compared with the conventional least square (LS) and minimum mean square error (MMSE) algorithms. The simulation results demonstrate that the proposed algorithm provides highly competitive performance over the MMSE algorithm and significantly outperforms the LS algorithm in a variety of system configurations. Since the requirement on prior channel statistics information makes the MMSE algorithm impractical or extremely complex, the proposed WOA-based channel estimation algorithm should be a suitable and promising candidate for dealing with channel estimation problems. The simulation framework is implemented in MATLAB and available upon request.

In recent years, multiple-input multiple-output (MIMO) systems, which use several transmit and receive antennas, have attracted much attention for high performance radio systems. In MIMO systems, the channel estimation is important to distinguish transmit signals from multiple transmit antennas. While the space-alternating generalized expectation-maximization (SAGE) algorithm is known to offer good channel estimation and data detection. We proposed earlier the minimum mean square error (MMSE)-based SAGE algorithm for MIMO systems where the MMSE estimation is used for channel estimation. We showed that the proposed MMSE-based SAGE algorithm can achieve the better bit error rate (BER) than the maximum likelihood (ML) detection with training symbols. The MMSE channel estimation needs the knowledge of the maximum Doppler frequency F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> for deriving the covariance matrix of the channel and the variance sigma <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of additive white Gaussian noise (AWGN). Additionally, the computation of the MMSE channel estimation requires O(L <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) operations where L is the transmitted frame length. Thus, its computational complexity is high. In this paper, we propose a zero-forcing (ZF)-based SAGE algorithm for channel estimation and data detection in MIMO systems that does not need the knowledge of Fd and sigma <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Since the computation of the proposed ZF-based SAGE algorithm requires O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) operations where N is the number of transmit antennas, its computational complexity is low. We show that the proposed ZF-based tracking SAGE algorithm with less computational complexity can achieve almost the same BER as that of the MMSE-based tracking SAGE algorithm

We consider the detection of multi-carrier-code division multiple access (MC-CDMA) signals in frequency selective fading channels using partial channel equalization. By partially compensating for the fading channel amplitude we can reduce the multi-user interference without considerably enhancing the additive noise level. As a result the MC-CDMA scheme can exploit the frequency diversity of the channel without the need for very complicated detection schemes. The obtained results show considerable performance improvement as compared to that of conventional detection schemes that try to fully compensate for the channel variations. In fact, the performance of this partial channel compensation based detector is not far from that of the optimum minimum mean square error (MMSE) combining detector.

Similar to the orthogonal frequency division multiple access (OFDMA) system, the single-carrier frequency division multiple access (SC-FDMA) system also suffers from frequency mismatches between the transmitter and the receiver. As a result, in this system, the carrier frequency offsets (CFOs) disrupt the orthogonality between subcarriers and give rise to inter-carrier interference (ICI) and multiple access interference (MAI) among users. The authors present a new minimum mean square error (MMSE) equaliser, which jointly performs equalisation and carrier frequency offsets (CFOs) compensation. The mathematical expression of this equaliser has been derived taking into account the MAI and the channel noise. A low complexity implementation of the proposed equalisation scheme using a banded matrix approximation is presented here. From the obtained simulation results, the proposed equalisation scheme is able to enhance the performance of the SC-FDMA system, even in the presence of estimation errors.