Joint Iterative Channel and Data Estimation in High Mobility MIMO-OFDM Systems
Author: Stephan Sand
Publisher: Logos Verlag Berlin GmbH
Published: 2010
Total Pages: 272
ISBN-13: 3832523855
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Channel Estimation and Data Detection for Mobile MIMO OFDM Systems
Author: Jie Gao
Publisher:
Published: 2005
Total Pages: 210
ISBN-13:
DOWNLOAD EBOOKDesigning 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.
Channel Estimation and Performance Analysis of MIMO-OFDM Communications Using Space-time and Space-frequency Coding Schemes
Author: Fabien Delestre
Publisher:
Published: 2011
Total Pages:
ISBN-13:
DOWNLOAD EBOOKThis thesis is concerned with channel estimation and data detection of MIMO-OFDM communication systems using Space-Time Block Coding (STBC) and Space-Frequency Block Coding (SFBC) under frequency selective channels. A new iterative joint channel estimation and signal detection technique for both STBC-OFDM and SFBC-OFDM systems is proposed. The proposed algorithm is based on a processive sequence of events for space time and space frequency coding schemes where pilot subcarriers are used for channel estimation in the first time instant, and then in the second time instant, the estimated channel is used to decode the data symbols in the adjacent data subcarriers. Once data symbols are recovered, the system recursively performs a new channel estimation using the decoded data symbols as pilots. The iterative process is repeated until all MIMO-OFDM symbols are recovered. In addition, the proposed channel estimation technique is based on the maximum likelihood (ML) approach which offers linearity and simplicity of implementation. Due to the orthogonality of STBC and SFBC, high computation efficiency is achieved since the method does not require any matrix inversion for estimation and detection at the receiver. Another major novel contribution of the thesis is the proposal of a new group decoding method that reduces the processing time significantly via the use of sub-carrier grouping for transmitted data recovery. The OFDM symbols are divided into groups to which a set of pilot subcarriers are assigned and used to initiate the channel estimation process. Designated data symbols contained within each group of the OFDM symbols are decoded simultaneously in order to improve the decoding duration. Finally, a new mixed STBC and SFBC channel estimation and data detection technique with a joint iterative scheme and a group decoding method is proposed. In this technique, STBC and SFBC are used for pilot and data subcarriers alternatively, forming the different combinations of STBC/SFBC and SFBC/STBC. All channel estimation and data detection methods for different MIMO-OFDM systems proposed in the thesis have been simulated extensively in many different scenarios and their performances have been verified fully.
Localization and Posture Recognition via Magneto-Inductive and Relay-Aided Sensor Networks
Author: Henry Ruben Lucas Schulten
Publisher: Logos Verlag Berlin GmbH
Published: 2022-12-15
Total Pages: 198
ISBN-13: 3832555862
DOWNLOAD EBOOKBody-centric wireless sensor networks are expected to enable future technologies such as medical in-body micro robots or unobtrusive smart textiles. These technologies may advance personalized healthcare as they allow for tasks such as minimally invasive surgery, in-body diagnosis, and continuous activity recognition. However, the localization of individual sensor nodes within such networks or the determination of the entire network topology still pose challenges that need to be solved. This work provides both theoretic and simulative insights to enable the required sub-millimeter localization accuracy of such sensors using magneto-inductive networks. It identifies inherent localization issues such as the asymmetry of the position estimation in magneto-inductive networks and outlines how such issues may be addressed by using passive relays or cooperation. It further proposes a novel approach to recognize the entire structure of a magneto-inductive network using simple impedance measurements and clusters of passive tags. This approach is evaluated extensively by simulation and experiment to demonstrate the feasibility of low-cost human body posture recognition.
Joint Estimation of CFO and CIR in MIMO-OFDM Systems
Author: Thavalapill Smith
Publisher: LAP Lambert Academic Publishing
Published: 2015-06-24
Total Pages: 56
ISBN-13: 9783659748875
DOWNLOAD EBOOKRecently the integration of the Multiple-Input Multiple-Output (MIMO) architectures and Orthogonal Frequency Division Multiplexing (OFDM) technique has been widely considered as a potential strategy to enhance data rate, capacity and quality of broadband wireless OFDM systems.However, the inherent drawback of OFDM-based systems is their susceptibility to synchronization errors such as the Carrier Frequency Offset (CFO) and the primary challenge in MIMO based systems is the increasing complexity in channel estimation as the number of antennas increases.Various joint CFO and channel estimation for OFDM as well as MIMO-OFDM systems have been proposed till date. In this report, we consider an iterative Expectation-Maximization (EM) algorithm for the joint estimation of CFO and Channel Impulse Response(CIR) for MIMO-OFDM system in frequency selective fading channel.Simulation results show that EM algorithm gives marginally better performance over pilot-assisted Maximum Likelihood (ML)- based algorithm, proposed recently, in terms of MSE of both channel and frequency offset estimator
Intelligent Multi-Modal Data Processing
Author: Soham Sarkar
Publisher: John Wiley & Sons
Published: 2021-04-06
Total Pages: 288
ISBN-13: 1119571421
DOWNLOAD EBOOKA comprehensive review of the most recent applications of intelligent multi-modal data processing Intelligent Multi-Modal Data Processing contains a review of the most recent applications of data processing. The Editors and contributors – noted experts on the topic – offer a review of the new and challenging areas of multimedia data processing as well as state-of-the-art algorithms to solve the problems in an intelligent manner. The text provides a clear understanding of the real-life implementation of different statistical theories and explains how to implement various statistical theories. Intelligent Multi-Modal Data Processing is an authoritative guide for developing innovative research ideas for interdisciplinary research practices. Designed as a practical resource, the book contains tables to compare statistical analysis results of a novel technique to that of the state-of-the-art techniques and illustrations in the form of algorithms to establish a pre-processing and/or post-processing technique for model building. The book also contains images that show the efficiency of the algorithm on standard data set. This important book: Includes an in-depth analysis of the state-of-the-art applications of signal and data processing Contains contributions from noted experts in the field Offers information on hybrid differential evolution for optimal multilevel image thresholding Presents a fuzzy decision based multi-objective evolutionary method for video summarisation Written for students of technology and management, computer scientists and professionals in information technology, Intelligent Multi-Modal Data Processing brings together in one volume the range of multi-modal data processing.
Signal Processing, Channel Estimation and Link Adaptation in MIMO-OFDM Systems
Author: Jianjun Ran
Publisher: Cuvillier Verlag
Published: 2008
Total Pages: 161
ISBN-13: 3867276498
DOWNLOAD EBOOKMIMO-OFDM for LTE, WiFi and WiMAX
Author: Lajos Hanzo
Publisher: John Wiley & Sons
Published: 2012-01-03
Total Pages: 693
ISBN-13: 111997299X
DOWNLOAD EBOOKMIMO-OFDM for LTE, WIFI and WIMAX: Coherent versus Non-Coherent and Cooperative Turbo-Transceivers provides an up-to-date portrayal of wireless transmission based on OFDM techniques augmented with Space-Time Block Codes (STBCs) and Spatial-Division Multiple Access (SDMA). The volume also offers an in-depth treatment of cutting-edge Cooperative Communications. This monograph collates the latest techniques in a number of specific design areas of turbo-detected MIMO-OFDM wireless systems. As a result a wide range of topical subjects are examined, including channel coding and multiuser detection (MUD), with a special emphasis on optimum maximum-likelihood (ML) MUDs, reduced-complexity genetic algorithm aided near-ML MUDs and sphere detection. The benefits of spreading codes as well as joint iterative channel and data estimation are only a few of the radical new features of the book. Also considered are the benefits of turbo and LDPC channel coding, the entire suite of known joint coding and modulation schemes, space-time coding as well as SDM/SDMA MIMOs within the context of various application examples. The book systematically converts the lessons of Shannon's information theory into design principles applicable to practical wireless systems; the depth of discussions increases towards the end of the book. Discusses many state-of-the-art topics important to today's wireless communications engineers. Includes numerous complete system design examples for the industrial practitioner. Offers a detailed portrayal of sphere detection. Based on over twenty years of research into OFDM in the context of various applications, subsequently presenting comprehensive bibliographies.
Iterative Channel Estimation Techniques For Multiple İnput Multiple Output Orthogonal Frequency Division Multiplexing Systems
Author: İlhan Baştürk
Publisher:
Published: 2007
Total Pages: 156
ISBN-13:
DOWNLOAD EBOOKOrthogonal frequency division multiplexing (OFDM) is well-known for its efficient high speed transmission and robustness to frequency-selective fading channels. On the other hand, multiple-input multiple-output (MIMO) antenna systems have the ability to increase capacity and reliability of a wireless communication system compared to single-input single-output (SISO) systems. Hence, the integration of the two technologies has the potential to meet the ever growing demands of future communication systems. In these systems, channel estimation is very crucial to demodulate the data coherently. For a good channel estimation, spectral efficiency and lower computational complexity are two important points to be considered. In this thesis, we explore different channel estimation techniques in order to improve estimation performance by increasing the bandwidth efficiency and reducing the computational complexity for both SISO-OFDM and MIMO-OFDM systems. We first investigate pilot and Expectation-Maximization (EM)-based channel estimation techniques and compare their performances. Next, we explore different pilot arrangements by reducing the number of pilot symbols in one OFDM frame to improve bandwidth efficiency. We obtain the bit error rate and the channel estimation performance for these pilot arrangements. Then, in order to decrase the computational complexity, we propose an iterative channel estimation technique, which establishes a link between the decision block and channel estimation block using virtual subcarriers. We compare this proposed technique with EM-based channel estimation in terms of performance and complexity. These channel estimation techniques are also applied to STBC-OFDM and V-BLAST structured MIMO-OFDM systems. Finally, we investigate a joint EM-based channel estimation and signal detection technique for V-BLAST OFDM system.
Recent Advances in Satellite Aeronautical Communications Modeling
Author: Grekhov, Andrii Mikhailovich
Publisher: IGI Global
Published: 2019-03-15
Total Pages: 313
ISBN-13: 1522582150
DOWNLOAD EBOOKModern systems and means of aeronautical radio communication are continuously being improved, but without the development of new technical means, the aviation industry suffers. The development of more innovative plans of aviation technology are needed in order to respond to the ever-increasing standard of aviation technology. Recent Advances in Satellite Aeronautical Communications Modeling is devoted to the modeling of satellite communication channels for aircraft and RPAS/UAV using the Matlab Simulink and NetCracker software. Featuring research on topics such as channel coding, microwave emitters, and array modeling, this book is ideally designed for scientists, engineers, air traffic controllers, managers, researchers, and academicians.
