Doppler Shift Estimation Of Mimo Ofdm Systems Based On Auto Correlation Function Of Channel Estimate

Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques have been considered as a strong candidate for the next-generation - wireless communication systems, due to their well-known advantages in high data-rate wireless transmission as well as high frequency spectrum efficiency. In the mean time, channel state information (CSI) is required for precise detection and recovery of signals. Therefore, channel estimation plays a significant role in MIMO-OFDM systems. On the other hand, due to the high mobility of wireless terminals, Doppler shift (DS) can be one of the major side-effects of utilizing MIMO-OFDM techniques, which may lead to severe performance loss. Many schemes on DS estimation have been developed for broadband single-input single-output (SISO) systems. A commonly used method is to exploit the auto-correlation property of the channel impulse response (CIR) estimated by well-developed channel estimation approaches, which not only has high accuracy but also moderate computational complexity. Hence, we first investigate an efficient channel estimation method in this thesis. We will then focus on Jakes' model based DS estimation schemes, and further extend to independently identically distributed (i.i.d.) MIMO-OFDM fading channels with both Rayleigh and Rician distributions. In the first part of the thesis, a training-sequence (TS) based least square (LS) channel estimation scheme is presented for MIMO-OFDM systems along with plenty of computer simulations and corresponding analyses. Experimental study shows that the CIR estimates obtained by the LS method are reliable under moderate channel conditions, and can efficiently be utilized for DS estimation. The second part of the thesis first studies the auto-correlation function (ACF) based DS estimation schemes for SISO-OFOM systems in Rayleigh fading channels, and then extends it to Rician fading channels by developing a new approach along with the analysis of its accuracy and complexity. Thereafter, we apply those approaches to MIMO-OFOM systems and present a few enhanced methods by using non-linear interpolation under certain circumstances. Detailed computer simulations and comparisons are performed, confirming that the proposed ACF based schemes give satisfactory estimation performance over i.i.d. Rayleigh or Rician fading channels with various channel conditions.

Designing spectral efficient, high-speed wireless links that offer high quality- of-service and range capability has been a critical research and engineering challenge. In this thesis, we mainly address the complexity and performance issues of channel estimation and data detection in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems over time-varying channels. We derive the probability density function (pdf) expressions of the condition number (i.e., the maximum-to-minimum-singular-value ratio, MMSVR) of the channel state information matrix of MIMO OFDM systems. It is shown that this ratio is directly related to the noise enhancement in open-loop systems and provides a significant insight on the system capacity. A decision-directed (DD) maximum a posteriori probability (MAP) channel estimation scheme of MIMO systems is derived. Error performance of a zero- forcing receiver with the DD MAP and perfect channel estimates is provided and compared. This scheme has a low complexity and can be applied to time-varying Rayleigh fading channels with an arbitrary spaced-time correlation function. We propose an iterative channel estimation and data detection scheme for MIMO OFDM systems in the presence of inter-carrier-interference (ICI) due to the nature of time-varying channels. An ICI-based minimum-mean-square error (MMSE) detection scheme is derived. An expectation-maximization (EM) based least square (LS) channel estimator is proposed to minimize the mean-square error (MSE) of the channel estimates and to reduce the complexity of the implementation. With the estimate of the channel and initially detected symbols, ICI is estimated and removed from the received signal. Thus more accurate estimation of the channel and data detection can be obtained in the next iteration. An EM-based MAP channel estimator is derived by exploiting the frequency/time correlation of the pilot and data sub-carriers. Performance comparison is made between the proposed schemes and the ideal case - time-invariant channels and perfect channel estimation. We optimize the data transmission by exploiting the long term correlation characteristics. The transmitted data is successively detected without an error floor in spatially correlated channels. The algorithms proposed in this thesis allow low-complexity implementation of channel estimation and data detection for MIMO OFDM systems over time-varying fading channels, while providing good error performance.

The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource, can meet the above requirements, and hence, it is a promising candidate technology for next generations of wireless systems. With massive antenna arrays at the BS, for most propagation environments, the channels become favorable, i.e., the channel vectors between the users and the BS are (nearly) pairwisely orthogonal, and hence, linear processing is nearly optimal. A huge throughput and energy efficiency can be achieved due to the multiplexing gain and the array gain. In particular, with a simple power control scheme, Massive MIMO can offer uniformly good service for all users. In this dissertation, we focus on the performance of Massive MIMO. The dissertation consists of two main parts: fundamentals and system designs of Massive MIMO. In the first part, we focus on fundamental limits of the system performance under practical constraints such as low complexity processing, limited length of each coherence interval, intercell interference, and finite-dimensional channels. We first study the potential for power savings of the Massive MIMO uplink with maximum-ratio combining (MRC), zero-forcing, and minimum mean-square error receivers, under perfect and imperfect channels. The energy and spectral efficiency tradeoff is investigated. Secondly, we consider a physical channel model where the angular domain is divided into a finite number of distinct directions. A lower bound on the capacity is derived, and the effect of pilot contamination in this finite-dimensional channel model is analyzed. Finally, some aspects of favorable propagation in Massive MIMO under Rayleigh fading and line-of-sight (LoS) channels are investigated. We show that both Rayleigh fading and LoS environments offer favorable propagation. In the second part, based on the fundamental analysis in the first part, we propose some system designs for Massive MIMO. The acquisition of channel state information (CSI) is very importantin Massive MIMO. Typically, the channels are estimated at the BS through uplink training. Owing to the limited length of the coherence interval, the system performance is limited by pilot contamination. To reduce the pilot contamination effect, we propose an eigenvalue-decomposition-based scheme to estimate the channel directly from the received data. The proposed scheme results in better performance compared with the conventional training schemes due to the reduced pilot contamination. Another important issue of CSI acquisition in Massive MIMO is how to acquire CSI at the users. To address this issue, we propose two channel estimation schemes at the users: i) a downlink "beamforming training" scheme, and ii) a method for blind estimation of the effective downlink channel gains. In both schemes, the channel estimation overhead is independent of the number of BS antennas. We also derive the optimal pilot and data powers as well as the training duration allocation to maximize the sum spectral efficiency of the Massive MIMO uplink with MRC receivers, for a given total energy budget spent in a coherence interval. Finally, applications of Massive MIMO in relay channels are proposed and analyzed. Specifically, we consider multipair relaying systems where many sources simultaneously communicate with many destinations in the same time-frequency resource with the help of a massive MIMO relay. A massive MIMO relay is equipped with many collocated or distributed antennas. We consider different duplexing modes (full-duplex and half-duplex) and different relaying protocols (amplify-and-forward, decode-and-forward, two-way relaying, and one-way relaying) at the relay. The potential benefits of massive MIMO technology in these relaying systems are explored in terms of spectral efficiency and power efficiency.

This work describes the OFDM-based MIMO Radar-Communication System, intended for operation in a multiple-user network, especially the automotive sector in the vehicle-to vehicle/infrastructure network. The OFDM signals however are weak towards frequency offsets causing subcarrier misalignment and corrupts the radar estimation and the demodulation of the communication signal. A simple yet effective interference cancellation algorithm is detailed here with real time measurement verification.

Orthogonal frequency-division multiplexing (OFDM) is a method of digital modulation in which a signal is split into several narrowband channels at different frequencies. CDMA is a form of multiplexing, which allows numerous signals to occupy a single transmission channel, optimising the use of available bandwidth. Multiplexing is sending multiple signals or streams of information on a carrier at the same time in the form of a single, complex signal and then recovering the separate signals at the receiving end. Multi-Carrier (MC) CDMA is a combined technique of Direct Sequence (DS) CDMA (Code Division Multiple Access) and OFDM techniques. It applies spreading sequences in the frequency domain. Wireless communications has witnessed a tremendous growth during the past decade and further spectacular enabling technology advances are expected in an effort to render ubiquitous wireless connectivity a reality. This technical in-depth book is unique in its detailed exposure of OFDM, MIMO-OFDM and MC-CDMA. A further attraction of the joint treatment of these topics is that it allows the reader to view their design trade-offs in a comparative context. Divided into three main parts: Part I provides a detailed exposure of OFDM designed for employment in various applications Part II is another design alternative applicable in the context of OFDM systems where the channel quality fluctuations observed are averaged out with the aid of frequency-domain spreading codes, which leads to the concept of MC-CDMA Part III discusses how to employ multiple antennas at the base station for the sake of supporting multiple users in the uplink Portrays the entire body of knowledge currently available on OFDM Provides the first complete treatment of OFDM, MIMO(Multiple Input Multiple Output)-OFDM and MC-CDMA Considers the benefits of channel coding and space time coding in the context of various application examples and features numerous complete system design examples Converts the lessons of Shannon’s information theory into design principles applicable to practical wireless systems Combines the benefits of a textbook with a research monograph where the depth of discussions progressively increase throughout the book This all-encompassing self-contained treatment will appeal to researchers, postgraduate students and academics, practising research and development engineers working for wireless communications and computer networking companies and senior undergraduate students and technical managers.