Antenna Selection for Time Reversal MIMO UWB Systems

A Multi-Input Multi-Output (MIMO) Ultra-Wide Band (UWB) communication system with Time Reversal (TR) is investigated in this paper. The system uses spatial multiplexing (SM) scheme to achieve high data rate. In order to cope with long delay spread of the UWB channel, time reversal technique is adopted at transmitter. Later a Multi Stream Interference (MSI) mitigation algorithm based on Zero Forcing (ZF) is proposed. The proposed ZF algorithm requires the knowledge of the channel state information (CSI), which is already available for time reversal at tranmitter. Simulation results show that the algorithm can considerably improve the BER performance of the system when the number of data streams is large (ges 3). This paper focuses on MIMO single user cases, however, the proposed MIMO-TR-UWB can be also extended to MIMO broadcasting system.

The performance of a Multi-Input Multi-Output (MIMO) and Ultra-Wide Band (UWB) communication system with Time Reversal (TR) has been studied in connection to the effect of spatial correlation. MIMO methods are thought to be an excellent approach to increasing network dependability and transmission rate. In this study, these features are investigated using a comprehensive UWB single-input multiple-output (SIMO) channel-sounding experiment. The issue with MIMO is that spatial correlation results in transmitters with greater BER. As a solution to the spatial correlation problem, the TR technique can solve the problem with its ability to time and space focusing. Our technique can considerably improve the BER performance of the system relative to the values of spatial correlation as shown in simulation results.

The time reversal (TR) technique combined with the ultra-wideband (UWB) system offers a new potential for decreasing the cost and complexity of the UWB receivers. In spite of TR–UWB's good performance in perfect channel state information (CSI), it is very sensitive to the channel estimation error. The effect of channel imperfection on the TR–UWB system is considered in this paper. At first, based on a minimum mean square error (MMSE) equalizer receiver, a prefilter is calculated in closed form to improve the performance of the TR–UWB system in an imperfect CSI scenario. Furthermore, for comparison purposes, a similar calculation for prefilter is carried out based on a simple matched filter (MF) receiver. Then, in order to improve the MF receiver performance, a two-stage iteration-based algorithm is developed. The initial value for this iteration-based improved algorithm is considered to be a prefilter which is calculated in the TR–UWB system with MMSE equalizer. This optimized algorithm causes the channel estimation error in the TR–UWB system to become zero in some steps. Finally, exhaustive simulations are done to demonstrate the performance advantage attained by the improved algorithm.

High rate data transmission in an underwater link necessitates the use of multiple antennas. Intersymbol interference (ISI), one of the major issues in single antenna underwater acoustic (UWA) systems, becomes even more prominent while establishing a multi-antenna communication link. Deploying an adaptive equalizer to mitigate this ISI incurs huge computational complexity as the equalizer needs large number of taps. Also, this might require a compromise in data rate and/or error performance of the system. A solution to this is the time reversal (TR) technique which has been proven to be a computationally simpler approach to combat ISI and to provide high signal to noise ratio gains in a single antenna system. In this paper, we explore the possibility of the TR technique in improving error rate, and minimizing computational burden of the equalizer in a multi-antenna UWA link. We present an experimental demonstration which shows that while reducing the computational complexity, the TR technique also provides better error performance at higher data rate.

In this contribution, we investigate the performance of dual-polarized multi input multi output (MIMO) multi-carrier interleave division multiple access system (MC-IDMA) over correlated frequency selective channels in the presence of channel state estimation error. In the code division multiple access (CDMA), orthogonal spreading sequence is used as user specific where as in IDMA, user specific interleaving pattern is used. In our considered work, Multi-carrier (MC) is realized by orthogonal frequency division multiplexing (OFDM). The channel is estimated at the mobile stations (MSs) by pilot assisted channel estimation (PACE) technique using minimum mean square error (MMSE) algorithm. Further, the dual-polarized MIMO system considered in our work which is realized with the aid of orthogonal polarizations, replaces two spatially separated uni-polarized antennas, thus resulting in polarization multiplexing. In particular, we evaluate the effects of three types of delay spread on MIMO MC-IDMA system in the context of downlink (DL) communications pertaining to the Standard University Interim (SUI) channel model. In a multi-user environment, users experience multi stream interference (MSI) in addition to the multiple access interference (MAI) and these interferences can degrade the system performance. Furthermore, we consider turbo code as channel encoder for MIMO MC-IDMA system to mitigate the effects of MAI and MSI. It is discerned from the simulation results that dual-polarized MIMO MC-IDMA system is capable of supporting many users and performs better in terms of achievable bit error rate (BER) in the context of DL communications with reduced number of antennas.

The research work in this dissertation addresses reduced complexity equalization technique for multipath channels with large delay spread. This has been one of the key challenges for high data rate impulse radio based Ultra-Wideband (UWB) communication systems using low cost receiver design. Our research focus is on developing efficient and effective tap selection techniques for non-uniformly spaced Minimum Mean Squared Error (MMSE) equalization and applying it to UWB systems to achieve high performance with reduced receiver complexity. In this dissertation, a new class of tap selection techniques based on Order Recursive Least Squares (ORLS) and Matching Pursuit (MP) algorithms is proposed for UWB multipath channel equalization in the presence of Inter Symbol Interference (ISI) and unknown co-channel interference. The proposed tap selection techniques are directly implemented based on training symbol sequence under Least Squares (LS) criterion without the need for explicit channel estimation. In addition, Diagonal Loading (DL) technique is incorporated into the tap selection and MMSE equalization processes to insure system robustness given limited number of training symbols in the case of practical implementation. The proposed tap selection based equalizer is shown to outperform the conventional uniformly spaced linear equalizer and is with reduced computational complexity. The LS based technique proposed for equalizer tap selection is then extended to receive antenna selection for high data rate UWB systems with multiple receive antenna elements to achieve improved performance in the presence of Narrow Band Interference (NBI). Based on the LS criterion, antenna selection techniques for Multiple Input Multiple Output (MIMO) systems are also explored in our research work. Novel transmit and receive antenna selection techniques are proposed for MIMO spatial multiplexing systems with linear receivers under LS criterion. Unlike conventional approaches, xii

Time reversal telecommunications in complex environments

Capacity maximizing in massive MIMO with linear precoding for SSF and LSF channel with perfect CSI

In this work, a new antenna selection algorithm is proposed for multiple-input multiple-output (MIMO) wireless communication systems. It is assumed that the channel state information (CSI) is exactly known at the receiver, and hence the antenna selection is considered only at the receiver. The goal of antenna selection is to find a tradeoff between the maximization of the channel capacity and the minimization of the pair-wise error probability (PEP). It turns out that the scheme of antenna selection plays an important part when dealing with high antenna correlation. It is shown that our proposed scheme for a system with two-transmit antennas and five-receive antennas offers better PEP performance than the algorithm based on the maximization capacity, but has little capacity loss. The simulation results indicate that our proposed scheme can jointly meet the capacity maximization and the PEP minimization.

A unified approach is developed for the study of multi-input, multi-output (MIMO) systems under fast fading with quantized covariance feedback. In such systems, the receiver computes, using perfect channel state information (CSI), the covariance matrices to be adopted by the transmitter corresponding to the current channel realization, and feeds back a quantized version of this information to the transmitter using finite, say Nf, bits per channel realization. Our analysis is based on a geometric framework we developed in a companion paper for manifolds of positive semi-definite (covariance) matrices with various trace and rank constraints. That analysis applies to MIMO systems in a unified manner to optimal as well as various suboptimal precoding methods for obtaining input covariances. These include, for example, the capacity achieving spatio-temporal water-filling strategy, the incorporation of just spatial water-filling and reduced-rank beamforming with power allocation in both cases, as well as MIMO systems with antenna selection. For a given system strategy, including the one that achieves capacity, the gap between the communication rates in the perfect and quantized covariance cases is shown to be O(2-Nf/N), where N is the dimension of the particular Pn manifold used for quantization. This dimension depends on the precoding strategy adopted and strongly determines how quickly the communication rate with quantized covariance feedback approaches that with perfect CSI at the transmitter (CSIT). Our results show how the choice of covariance quantization manifold can be tailored to the available feedback rate in MIMO system design.

1.1 Impulse Radio (IR) Ultra Wideband (UWB) Communications Ultra wideband (UWB) communication is a fast emerging technology that offers new opportunities such as high data rates, low equipment cost, low power, precise positioning capability and extremely low interference Ghawami (2005). A wide range of possible UWB communication system applications includes radars due to UWB ultra high precision ranging at the centimeter level, wireless personal area networks (WPAN), sensor networks, imaging systems, UWB positioning systems, etc. Yang (2004), Kshetrimayum (2009). From a commercial point of view, the high data rates are the most attractive feature of UWB systems for which speeds of over 100Mb/s have been demonstrated Ghawami (2005). There exist three main types of UWB technologies: impulse radio (IR UWB), direct sequence (DS UWB), and multi-band orthogonal frequency division multiplexing (MB OFDM) Ran (2009). IR UWB communication technique is essentially different from all other communication techniques because it is carrier free and uses for communication between transmitters and receivers very narrow radio frequency (RF) pulses generated from the UWB pulse generator, while traditional transmission systems transmit information by varying the power, frequency, and/or phase of a sinusoidal wave in a modulation process Kshetrimayum (2009), Yao (2007). Consequently, complicated frequency mixers and local oscillators for carrier frequency up and down conversion are not necessary Yao (2007). IR UWB modulation techniques are especially important because the UWB spectrum has been made available by the Federal Communication Commission (FCC) and it can be used with IRs developed to date Lin (2005). Waveforms for IR UWB are designed to obtain a flat frequency response over the bandwidth of the pulse and to avoid a DC component. The large spectrum of a UWB signal may interfere with existing users. In order to keep this interference to the minimum, FCC specifies spectral masks for different applications, i.e. the allowed power output for specific frequencies Ghawami (2005). A contiguous bandwidth of 7.5GHz is available in the frequency interval of (3.1− 10.6)GHz at a maximum power output of −41.3dBm/MHz which is considered as extremely low Ghawami (2005). The power spectral density (PSD) of UWB systems defined as a ratio of the transmitted power P in watts and a signal bandwidth B in hertz is extremely low as compared to other communication systems due to the very wide bandwidth B of short pulses that are typically of nanosecond or picosecond order Ghawami (2005). The selection of the impulse signal type for IR UWB communication system is essential since it determines

Recently it has been shown that it is possible to improve the performance of multiple-input multiple-output (MIMO) systems by employing a larger number of antennas than actually used and selecting the optimal subset based on the channel state information. Existing antenna selection algorithms assume perfect channel knowledge and optimize criteria such as Shannon capacity or various bounds on error rate. This paper examines MIMO antenna selection algorithms where the set of possible solutions is large and only a noisy estimate of the channel is available. In the same spirit as traditional adaptive filtering algorithms, we propose simulation based discrete stochastic optimization algorithms to adaptively select a better antenna subset using criteria such as maximum mutual information, bounds on error rate, etc. These discrete stochastic approximation algorithms are ideally suited to minimize the error rate since computing a closed form expression for the error rate is intractable. We also consider scenarios of time-varying channels for which the antenna selection algorithms can track the time-varying optimal antenna configuration. We present several numerical examples to show the fast convergence of these algorithms under various performance criteria, and also demonstrate their tracking capabilities.

This paper investigates the massive multi-input multi-output (MIMO) system in practical deployment scenarios, in which, to balance the economic and energy efficiency with the system performance, the number of radio frequency (RF) chains is smaller than the number of antennas. The base station employs antenna selection (AS) to fully harness the spatial multiplexing gain. Conventional AS techniques require full channel state information (CSI), which is time-consuming as the antennas cannot be simultaneously connected to the RF chains during the channel estimation process. To tackle this issue, we propose a novel joint channel prediction and AS (JCPAS) framework to reduce the CSI acquisition time and improve the system performance under temporally correlated channels. Our proposed JCPAS framework is a fully probabilistic model driven by deep unsupervised learning. The proposed framework is able to predict the current full CSI, while requiring only a historical window of partial observations. Extensive simulation results show that the proposed JCPAS can significantly improve the system performance under temporally correlated channels, especially for very large-scale systems with highly correlated channels. multi-output (MIMO) system in practical deployment scenarios, in which, to balance the economic and energy efficiency with the system performance, the number of radio frequency (RF) chains is smaller than the number of antennas. The base station employs antenna selection (AS) to fully harness the spatial multiplexing gain. Conventional AS techniques require full channel state information (CSI), which is time-consuming as the antennas cannot be simultaneously connected to the RF chains during the channel estimation process. To tackle this issue, we propose a novel joint channel prediction and AS (JCPAS) framework to reduce the CSI acquisition time and improve the system performance under temporally correlated channels. Our proposed JCPAS framework is a fully probabilistic model driven by deep unsupervised learning. The proposed framework is able to predict the current full CSI, while requiring only a historical window of partial observations. Extensive simulation results show that the proposed JCPAS can significantly improve the system performance under temporally correlated channels, especially for very large-scale systems with highly correlated channels.

Ever since the adoption of the single carrier frequency division multiple access (SC-FDMA) scheme for the uplink in the Long Term Evolution (LTE) standard, there has been much interest in improved receiver algorithms for the same. Successive interference cancelation (SIC) based turbo receivers (Turbo SIC) have been proposed to tackle the multi-stream interference (MSI) for transmission modes such as spatial multiplexing (SM) and multiuser (MU) multiple input multiple output (MIMO). In addition, decision feedback equalizers (DFE) have been discussed as an alternative to the simple linear minimum mean square error (LMMSE) based receivers to suppress intersymbol interference (ISI) caused by the frequency selective multi-path channel. This paper proposes a DFE receiver variant based on parallel interference cancelation (PIC) with maximum likelihood detection (MLD) and ordered SIC (OSIC) principles to suppress ISI and MSI. Simulations show that the proposed receiver performs better than the existing SIC and DFE based receivers and achieves the matched filter bound (MFB) for both coded and uncoded systems.

The inter-vehicles communication is becoming increasingly mandatory to improve the road safety and to allow a better transport management. The concept behind an intelligent vehicle consists in equipping this vehicle with an optimum number of sensors, in order to perceive the environment surrounding it and to ensure an automatic guidance control and the communication with the infrastructure and other vehicles. Among the most often used tools for this objective, we can cite the embedded radar. Moreover, the Ultra Wide Band (UWB) communication systems are under fast development and undergo progressive implementation. The principle of UWB technology is to transmit rather low power, carrier-less, signals occupying a very broad spectrum [1]. The spectral concentration of radiated power is thus extremely low, so that the other systems perceive UWB ones like background noise. In this article, a road radar based on UWB technology is studied. The proposed device allows, in a road environment, good resolution and increased precision for detection and localization of obstacles.