Space-frequency trellis coding for MIMO OFDM systems

This work presents a theoretical framework for determining the optimal clipping level for a multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. We start by modeling of the clipping noise, and propose a maximum likelihood (ML) receiver for the resulting signal. The bit error rate (BER) for this ML receiver is then derived for MIMO spatial multiplexing, space time coding, and cyclic delay diversity schemes. A search through the tradeoff space between the BER performance penalty and power amplifier (PA) power consumption advantage reveals optimum clipping levels of the system. Using an IEEE 802.11n like system, we show that the optimum clipping as predicted by this approach can improve PA power efficiency as much as 70%.

In this paper a deterministic parallel factor (PARAFAC) receiver is proposed, for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. We show that the received signal forms a 4-way tensor whose dimensions are space, time, and frequency, and can be written as a sum of tensor products (over paths and users) of four tensors representing the channel (for two of them), the symbols, and the modulation. Parameters of this model are identified via an alternating least squares (ALS) algorithm, called DEBRE, whose identifiability conditions are pointed out

In this paper, a method for estimating the maximum Doppler shift frequency is presented for Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. This method uses the Autocorrelation Function (ACF) for estimating frequency shift that induces ICI between adjacent OFDM subcarriers. The simulation results investigate the BER performance of OFDM system that achieves transmit and receive diversity by using Alamouti/MRC, as well as the BER performance of MIMO linear detectors Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) under the effect of a Doppler spread channel.

In order to improve the performance of space-time coded (STC) multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) enhancements were implemented in a MatLab simulation by shaping the OFDM pulses transmitted through various terrestrial Rayleigh fading channel models. The goal is to achieve the lowest possible BER to overcome channel effects. The pulse shaping investigated achieved high data rates by being overlapped in the time domain, equalisation was then used to suppress the resulting intersymbol interference. Our finding after researching a number of pulses is that the harris-moerder pulse was the most successful. Unlike the other pulse shapes this shape performs better in a Rayleigh fading channel than in an approximated AWGN channel. This also indicates that simulations using an overly simplified channel model can give results that are likely to be contrary to performance in the real physical environment.

Free Space Optical (FSO) communication is an emerging technology to provide high bandwidth, secure and high quality communication. In this work we have determined the capacity of the Free Space Optical communication system with Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) technique under weak atmospheric turbulence conditions. To model the weak turbulence condition of the atmosphere lognormal channel model is used throughout the work. The capacity of MIMO-OFDM FSO is evaluated in the presence of Inter Symbol Interference (ISI) and is compared with MIMO FSO with ISI. The capacity of MIMO-OFDM FSO system increases in comparison to MIMO in the presence of ISI. It is found that the effect of ISI is mitigated by using OFDM and the capacity is enhanced. Since MIMO uses spatial divervity to mitigate the fading caused by turbulence hence the capacity of both MIMO-OFDM FSO and MIMO FSO also increases as the number of receiving antennas is increased.

I/Q imbalance, which is one of the radio frequency (RF) circuit impairments in direct conversion transmitter and receiver, introduces severe performance degradation in wireless communication systems. In this paper, we propose a novel blind compensation algorithm for both frequency-dependent and frequency-independent I/Q imbalance based on independent component analysis (ICA) in multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, where ICA, an efficient higher order statistics (HOS) based blind source separation technique, is applied to compensate for I/Q imbalance and equalize the received signals simultaneously. Moreover, precoding is employed to resolve the ambiguity in the ICA output signals. Simulation results show that the proposed approach can not only compensate for I/Q imbalance effectively, but also achieve frequency diversity gains and outperform the case with perfect channel state information (CSI) and no I/Q imbalance.

In this paper, we present a pre-transformed (PT) multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system, in short PT-MIMO-OFDM system. We propose two receiver structures that combine the iterative subcarrier reconstruction and iterative interference cancellation to fully exploit both the spatial and the frequency diversity of MIMO-OFDM systems. Significant performance gain can be achieved. Based on the performance and receiver complexity tradeoff, we also present a set of guidelines for choosing either one of the two receivers in practical systems

The electrical wireless network build 4G TD-LTE network in 1.8GHz band, orthogonal frequency division multiplexing (OFDM) and multiple input multiple output (MIMO) are the key technologies. The OFDM system is sensitive to carrier frequency offset (CFO) and hence accurate CFO estimates for the OFDM system are essential. In this paper, we study the problem of carrier frequency offset (CFO) in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, and then a multi-invariance PM algorithm is proposed to estimate CFO in MIMO-OFDM system. The proposed algorithm employs the property of multi-invariance. Simulations show that the proposed algorithm has a better CFO estimation performance than PM.

Physical layer security is a crucial issue in wireless networks to prevent legitimate communication from eavesdropping. This paper investigates the physical layer security of a wireless multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system in the presence of a multiple-antenna eavesdropper. We first propose a minimum mean square error (MMSE)-based-filter secure MIMO–OFDM system which can destroy the orthogonality of eavesdropper’s signals. The MMSE-based-filter is used at the receiver to suppress the inter-subcarrier interference and disturb the reception of eavesdropper while maintaining the quality of legitimate transmission. Next, we propose another artificial noise (AN)-assisted secure MIMO–OFDM system to further improve the security of the legitimate transmission. The time-domain AN signal is designed to be canceled out at the legitimate receiver. Therefore, AN will disturb the reception of eavesdropper while the legitimate transmission will not be affected. Finally, power allocation for AN signals and subcarriers will be discussed since AN is generated utilizing the residual power of the MIMO–OFDM system. Simulation results are presented to demonstrate the security performance of the proposed transmit filter design and AN-assisted scheme in the MIMO–OFDM system.

Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009

Timing synchronization using cross ambiguity function for MIMO OFDM systems with distributed antennas

Orthogonal frequency division multiplexing (OFDM) systems work well if the subcarriers are orthogonal to each other. However, the orthogonality among subcarriers may not exist and result in inter-carrier interference (ICI) at the receiver. This may cause by residual carrier frequency offset, time variations due to Doppler shift or phase noise. Further developing the parallel cancellation (PC) scheme to mitigate the ICI of OFDM systems, we expand this OFDM symbol-based PC scheme into a space-frequency (SF) coded system. This new simple space- frequency parallel cancellation (SFPC) scheme is a technique that combines the SF and PC schemes together. Computer simulations indicate that OFDM systems using the SFPC scheme outperform the regular PC and SF systems in slow and fast frequency selective fading channels, specifically at a high signal-noise-ratio (SNR). Furthermore, the error floor of the SFPC-OFDM system is significantly lower than that of the PC and SF systems without increasing computational load. Additionally, the SFPC scheme is a simple multiple input and multiple output (MIMO) system.

A set of long term associated neurological disorders which is characterized by seizures is epilepsy. Because of the abnormal electrical activities occurring in the brain, the occurrence of epileptic seizures become prominent. In epilepsy research, convulsions too are sometimes related to epileptic seizures. So to investigate and understand the brain’s electrical activity, recording the scalp is important and that can be done with the help of Electroencephalograph (EEG). The time consumption with the long term measurements is enormous and so reviewing it becomes quite a hectic task. So the need for an automatic detection of seizures is required. As the long term measurements produce a huge amount of data, it would be pretty difficult to process and so with the help of Independent Component Analysis (ICA), the dimensions of the data are reduced. Then it is transmitted via a Space Time Block Coded Multiple Input Single Output (2 x 1) Orthogonal Frequency Division Multiplexing (STBC MISO-OFDM) System. As the system has a high Peak to Average Power Ratio (PAPR), it is reduced with the help of Hadamard Based PAPR Reduction and then at the receiver the Bit Error Rate (BER) is computed. Also at the receiver side, the classifier employed is Linear Kernel Support Vector Machines (L-SVM). Finally the epilepsy risk level classification from EEG Signals is measured in terms in Specificity, Sensitivity, Accuracy, Time Delay and Quality Values.

In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits.

Multiuser channel estimation and prediction in two dimensions for MIMO–OFDM uplinks