Author: Andrew Paul MillarPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Channel Estimation and Non-linear Transceiver Designs for MIMO OFDM Relay Systems
Author: Andrew Paul MillarSignal Processing, Channel Estimation and Link Adaptation in MIMO-OFDM Systems
Author: Jianjun RanPublisher: Cuvillier Verlag
ISBN: 3867276498
Category :
Languages : en
Pages : 161
Book Description
Digital Compensation for Analog Front-Ends
Author: François HorlinPublisher: John Wiley & Sons
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 286
Book Description
The book concludes with two chapters providing an in-depth coverage of the estimation and compensation algorithms."--BOOK JACKET.
Analysis and Transceiver Design for the MIMO Broadcast Channel
Author: Raphael HungerPublisher: Springer Science & Business Media
ISBN: 3642316921
Category : Technology & Engineering
Languages : en
Pages : 323
Book Description
This book deals with the optimization-based joint design of the transmit and receive filters in MIMO broadcast channel in which the user terminals may be equipped with several antenna elements. Furthermore, the maximum performance of the system in the high power regime as well as the set of all feasible quality-of-service requirements is analyzed. First, a fundamental duality is derived that holds between the MIMO broadcast channel and virtual MIMO multiple access channel. This duality construct allows for the efficient solution of problems originally posed in the broadcast channel in the dual domain where a possibly hidden convexity can often be revealed. On the basis of the established duality result, the gradient-projection algorithm is introduced as a tool to solve constrained optimization problems to global optimality under certain conditions. The gradient-projection tool is then applied to solving the weighted sum rate maximization problem which is a central optimization that arises in any network utility maximization. In the high power regime, a simple characterization of the obtained performance becomes possible due to the fact that the weighted sum rate utility converges to an affine asymptote in the logarithmic power domain. We find closed form expressions for these asymptotes which allows for a quantification of the asymptotic rate loss that linear transceivers have to face with respect to dirty paper coding. In the last part, we answer the fundamental question of feasibility in quality-of-service based optimizations with inelastic traffic that features strict delay constraints. Under the assumption of linear transceivers, not every set of quality-of-service requirements might be feasible making the power minimization problem with given lower bound constraints on the rate for example infeasible in these cases. We derive a complete description of the quality-of-service feasibility region for arbitrary channel matrices.
Channel Estimation and Data Detection for Mobile MIMO OFDM Systems
Author: Jie GaoPublisher:
ISBN:
Category : MIMO systems
Languages : en
Pages : 210
Book Description
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.
Channel Estimation and Performance Analysis of MIMO-OFDM Communications Using Space-time and Space-frequency Coding Schemes
Author: Fabien DelestrePublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
This 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.
Doppler Shift Estimation of MIMO-OFDM Systems Based on Auto-correlation Function of Channel Estimate
Author: Qin ZhuPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
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.
Linear Transceiver Design in MIMO System with Imperfect Channel State Information
Author: Wei HuangPublisher:
ISBN:
Category : MIMO systems
Languages : en
Pages : 158
Book Description
MSE-Based Linear Transceiver Designs for Multiuser MIMO Wireless Communications
Author: Adam TenenbaumPublisher:
ISBN: 9780494780336
Category :
Languages : en
Pages : 362
Book Description
This dissertation designs linear transceivers for the multiuser downlink in multiple-input multiple-output (MIMO) systems. The designs rely on an uplink/downlink duality for the mean squared error (MSE) of each individual data stream.Our second set of designs maximize the sum throughput for all users. We establish a series of relationships linking MSE to the signal-to-interference-plus-noise ratios of individual data streams and the information theoretic channel capacity under linear minimum MSE decoding. We show that minimizing the product of MSE matrix determinants is equivalent to sum-rate maximization, but we demonstrate that this problem does not admit a computationally efficient solution. We simplify the problem by minimizing the product of mean squared errors (PMSE) and propose an iterative algorithm based on alternating optimization with near-optimal performance.The remainder of the thesis considers the more practical case of imperfections in CSI. First, we consider the impact of delay and limited-rate feedback. We propose a system which employs Kalman prediction to mitigate delay; feedback rate is limited by employing adaptive delta modulation. Next, we consider the robust design of the sum-MSE and PMSE minimizing precoders with delay-free but imperfect estimates of the CSI. We extend the MSE duality to the case of imperfect CSI, and consider a new optimization problem which jointly optimizes the energy allocations for training and data stages along with the sum-MSE/PMSE minimizing transceivers. We prove the separability of these two problems when all users have equal estimation error variances, and propose several techniques to address the more challenging case of unequal estimation errors.We first consider the design of transceivers assuming channel state information (CSI) at the transmitter. We consider minimization of the sum-MSE over all users subject to a sum power constraint on each transmission. Using MSE duality, we solve a computationally simpler convex problem in a virtual uplink. The transformation back to the downlink is simplified by our demonstrating the equality of the optimal power allocations in the uplink and downlink.
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