Sajjad Beygi

Space Modulation With CSI: Constellation Design and Performance Evaluation

In this paper, we investigate the effect of channel state information at the transmitter (CSIT) on the performance of a class of transmission schemes for multi-input–multi-output (MIMO) systems that can be collectively called space modulation (SMod) schemes. Space shift keying (SSK) is a simple example of SMod. In SMod, multiple antennas at the transmitter are employed to spatially modulate the information. The constellation vectors at the receiver are linear combinations of columns of the channel matrix, and therefore, the symbol error rate (SER) performance of the system highly depends on the Euclidean distance between each pair of these vectors. In this paper, we propose two novel methods to design the transmit vectors using CSIT such that the distance between each pair of constellation vectors at the receiver becomes larger, which, in turn, reduces the SER. Whereas in the first method we do not impose any constraint on the structure of the transmit vectors, in the second method, we confine the transmit vectors to have only one nonzero entry, and as such, it can be looked at as a modified SSK (MSSK) transmission scheme. This is to avoid interantenna synchronization (IAS) as only one transmit antenna is active at a time. Compared to SSK, the first method provides a significant performance improvement at the expense of increased complexity at the transmitter due to IAS. The second method provides an appealing SER improvement while keeping the complexity the same as that of SSK. Therefore, one can look at the second method as a modified version of SSK in which instead of transmitting a fixed symbol from one of the transmit antennas, in our proposed method, different transmit powers and phases are assigned to different transmit antennas. As acquiring full CSIT is difficult in some cases, we also consider the case of imperfect CSIT and derive alternative SMod transmission schemes in this case. By simulation, we show that the proposed SMod transmission schemes provide a significant performance improvement in terms of the SER in the presence of full or imperfect CSIT.

RF Impairments Compensation and Channel Estimation in MIMO-OFDM Systems

The application of multi-input-multi-output (MIMO) technology in orthogonal frequency division multiplexing (OFDM) systems provides better spectral efficiency with high capacity gain. It also introduces significant complexity at the transceivers which can be partially reduced using homodyne or zero-IF receivers. However, those transceivers are very sensitive to imperfections of analog components at the RF front end and suffer severe performance degradation in the presence of RF impairments. Two of the most common impairments that significantly limit the performance of MIMO-OFDM transceivers are IQ-Imbalance and phase noise. In this paper, we propose a joint estimation and compensation technique to estimate channel, phase noise and IQ-Imbalance parameters in MIMO-OFDM systems under multipath slow fading channels. A subcarrier multiplexed preamble structure to estimate the channel and impairment parameters with minimum overhead is introduced and used in the estimation of IQ-Imbalance parameters as well as the initial estimation of effective channel matrix including common phase error (CPE). We then use a novel tracking method using pilot subcarriers to update the effective channel matrix throughout an OFDM frame. Simulation results for a variety of scenarios indicate that the proposed estimation and compensation technique efficiently improves the performance of MIMO-OFDM systems in terms of bit- error-rate (BER) as compared with the non- compensated case.

A Low-Complexity Method to Compensate IQ-Imbalance and Phase Noise in MIMO-OFDM Systems

The degrading effect of RF impairments on the performance of wireless communication systems is more pronounced in MIMO- OFDM transmission. Two of the most common impairments that significantly limit the performance of MIMO-OFDM transceivers are IQ-imbalance and phase noise. Low-complexity estimation and compensation techniques that can jointly remove the effect of these impairments are highly desirable. In this paper, we propose a simple joint estimation and compensation technique to estimate channel, phase noise and IQ-imbalance parameters in MIMO-OFDM systems under multipath slow fading channels. A subcarrier multiplexed preamble structure to estimate the channel and impairment parameters with minimum overhead is introduced and used in the estimation of IQ-imbalance parameters as well as the initial estimation of effective channel matrix including common phase error (CPE). We then use a novel tracking method based on the second order statistics of the inter-carrier interference (ICI) and noise to update the effective channel matrix throughout an OFDM frame. Simulation results for a variety of scenarios show that the proposed low-complexity estimation and compensation technique can efficiently improve the performance of MIMO-OFDM systems in terms of bit-error-rate (BER).

The iterative shrinkage method for impulsive noise reduction from images

In this paper, we present a novel scheme to compensate impulsive noise from images using the sparse shrinkage method. In this scheme, we assume the remaining noise after using a simple median filtering in place of corrupted pixels, found by boundary discriminative noise detection method, to be Gaussian additive noise. This assumption will later be verified by the means of simulation. Knowing that the pure image in the discrete wavelet transform (DWT) domain is a sparse vector, we define an optimization problem to minimize the l0-norm of the estimated image vector from the noisy one in the DWT domain. l0-norm makes the optimization problem a combinatorial optimization problem which is NP-hard to solve. To come up with a solution for our optimization problem, we convert the l0-norm problem to a continuous optimization problem which is then solved to find the estimated image with reduced noise. In the simulation and discussion part, the performance of our proposed method in reducing impulsive noise is compared to that of existing methods in the literature. We show that our proposed algorithm generally performs better in terms of both subjective and objective evaluations and is less complex.

Blind structural similarity estimation of digital images using quantized discrete cosine transform coefficients

Objective image quality assessment is used to develop a quantitative measure in order to predict perceived image quality by exploiting a variety of known properties of the human visual system (HVS). A new paradigm for quality assessment of the image is based on the structural similarity (SSIM) index, which takes advantage of characteristics of the HVS. In order to estimate SSIM, we need to know the source image to quantify the visibility of errors between the distorted image and the referenced image. In many practical applications, however, the reference image is not available and a blind quality assessment should be utilized. In this paper, an algorithm for statistical estimation of the SSIM based on the probability density functions (pdfs) of quantized discrete cosine transform (DCT) coefficients is presented. In the proposed method, we assume that the pdfs of the original DCT coefficients follow a specific distribution. The parameters of this distribution are then obtained from the quantization step size and quantized DCT coefficients of the distorted image, which are then used to calculate the SSIM metric. Our proposed method is, therefore, applicable to the encoding schemes that involve DCT quantization such as JPEG encoding. Numerical results show that the proposed SSIM estimation method provides relative errors that are generally smaller than those of the available peak signal-to-noise ratio estimation schemes for DCT-based images.

Space–Time Trellis Codes for Two-Way Relay MIMO Channels With Single-Antenna Relay Nodes

In this paper, the analysis and design of space-time trellis codes (STTCs) for two-way relay channels (TWRCs) with multiantenna source and destination and single-antenna relay nodes, assuming perfect channel state information (CSI) at the destination nodes, is considered. We derive a pairwise error probability (PEP) expression for the performance of STTCs in this type of channels. A simple upper bound on the PEP is then derived and used to find optimum STTCs. We prove that the designed STTCs based on the derived criterion achieve full diversity and significant coding gain in TWRCs, particularly at high signal-to-noise ratios (SNRs).

Energy production cost and PAR minimization in multi-source power networks

We study the problem of minimizing the power generation cost and peak-to-average (PAR) of sources energy production for a network of multiple energy sources. We consider a power distribution network in which each load is connected to multiple sources and, depending on network connectivity, can be fed by more than one power source. We assume that the power generation cost changes from one power source to another. We also assume that the power generation cost for each source is a function of its load. Based on the network model and assuming the power consumption schedule for all the loads is available, we then introduce two different optimization problems to minimize the overall cost of energy production throughout the network and to minimize the PAR of sources energy. We also introduce a hybrid optimization problem that combines the energy production cost and PAR objective functions with a proper wight. By solving these optimization problems using convex optimization techniques, we find out the best load sharing schemes that minimize the derived objective functions. In practice, each load shares its consumption schedule hourly (or daily) with the central power network administrator over a wired or wireless area network. This information can then be used to solve the formulated optimization problems. Simulation results confirm that the resulting load sharing schemes bring about significant reduction in the energy production cost as well as the PAR of the required generated energy throughout the network.

Null Space Precoding for Downlink Network MIMO Systems with No CSI

Multicell coordination increases the cell-edge users throughput in cellular wireless communication if the inter-cell interference (ICI) is mitigated properly. In this paper, we use the null space concept to design precoders and decoders to remove ICI for cell-edge users in the downlink of a network MIMO system. We propose two novel methods that are able to eliminate ICI assuming no channel state information (CSI) is available at the basestations. Calculating signal-to-interference-ratio (SINR), we show that our proposed methods reaches to higher SINR in comparison to the block diagonalization (BD) with full CSI. By simulations, we show our methods outperform the BD method with full CSI in terms of BER since the SINR is higher for our proposed methods. We also show that to obtain most of sumrate provided by coordination strategy, it is not necessary to have global coordination and having four cells coordinating with each other is enough to reach more than 85 percent of maximum achievable sum-rate.

Exploiting Multiuser Diversity in OFDMA Systems with Limited Feedback

In this paper, we extend the results of [12] by proposing a joint polling and contention scheduling scheme that reduces the feedback load in orthogonal frequency division multiple access (OFDMA) systems employing adaptive modulation. This feedback reduction is achieved by grouping users into categories, and requesting feedback from users that belong to a certain category only. The feedback process comprises of two modes. The first mode is a polling only mode and the second mode consists of a contention stage followed by a polling stage. The contention stage is used to find the i-th category where the best user is likely to be found. All users belonging to that category are polled sequentially until an acceptable user with channel quality above a predefined threshold is found. Numerical results show that the proposed scheme reduces the feedback load and the guard-time without any loss in the spectral efficiency when compared to the optimal selective diversity with full feedback algorithm shown in [11]. We, further, derive closed-form expressions for the feedback load, average guard time and the spectral efficiency and show that the proposed scheme improves the system spectral efficiency, the feedback load and the average guard time when compared to the schemes proposed in [12].

Channel Regularization and Vector Perturbation for Dual-Hop Precoded AF Relaying in Downlink Transmission

In this paper, we investigate the channel regularization and vector perturbation techniques at the source and linear precoding at the relay to enhance the performance of a dual-hop amplify and-forward (AF) relay downlink system. At first, an optimal regularized channel inversion scheme via regularization parameter is proposed. The joint channel regularization and linear precoder design at the relay is then investigated using the mean-square-error (MSE) criterion. Since dealing directly with such a criterion is quite involved, we propose a simple iterative solution. Our simulation results show that the proposed solution significantly outperforms the conventional channel inversion method. To further improve the performance of the regularization scheme, we further incorporate vector perturbation into channel regularization using a sphere encoder at the source. Numerical results show that the bit-error-rate (BER) performance of the regularized perturbation technique outperforms other well-known precoder designs in dual-hop AF relay downlink systems.