Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

Frequency domain equalization space-time block-coded CDMA transmission system

Abstract In this work we propose a space-time block-coded (STBF) CDMA transmission system suitable for use with frequency domain equalization (FDE) algorithms. We illustrate the FDE by implementing the maximal ratio combining, the zero forcing and the minimum mean squared error single user detection algorithms. A diversity gain analysis is developed and some interesting results are pointed out. It is shown through computer simulations that the proposed transmission system exhibits good performance in terms of bit error rate when compared to previously proposed STBC CDMA transmission systems.</p

OPTIMIZATION OF BER PERFORMANCE IN THE MIMO-OFDMA SYSTEM FOR MOBILE WIMAX SYSTEM USING DIFFERENT EQUALIZATION ALGORITHM

ABSTRACT Combination of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) is implemented to offer a simple and high performance system as to increase channel capacity and serve high data rate. Even though the OFDMA concept is simple in its basic principle, but it suffers one of the most challenging issues, which is synchronization error that introduces the inter-symbol interference (ISI), thus degrades the signal performance. The goal of this paper is to provide a method to mitigate this ISI by employing the equalizers at the receiver end and using Space Time Block Codes (STFBC) to improve the Bit error rate (BER) performance and to achieve a maximum diversity order in MIMO-OFDMA by using simulation based on the platforms of MATLAB software As a result, the BER performance is improved when implementing equalizers at the receiver with STFBC outperforms the conventional system without equalizer with a maximum diversity order and an efficient bandwidth in the Mobile WiMAX system

Physical layer network coding based communication systems in frequency selective channels

PhD ThesisThe demand for wireless communications is growing every day which requiresmore speed and bandwidth. In two way relay networks (TWRN), physical layer network coding (PLNC) was proposed to double the bandwidth. A TWRN is a system where two end users exchange data through a middle node called the relay. The two signals are allowed to be physically added before being broadcasted back to the end users. This system can work smoothly in flat fading channels, but can not be applied straightforward in frequency selective channels. In a multipath multi-tap FIR channel, the inter-symbol interference (ISI) spreads through several symbols. In this case, the symbols at the relay are not just an addition of the sent symbols but also some of the previous symbols from both sides. This not only causes a traditional PLNC to fail but also a simple one equalizer system will not solve the problem. Three main methods have been proposed by other researchers. The OFDM based PLNC is the simplest in terms of implementation and complexity but suffers from the disadvantages of the OFDMlike cyclic prefix overhead and frequency offset. The main disadvantage, however is the relatively low BER performance because it is restricted to linear equalizers in the PLNC system. Another approach is pre-filtering or pre-equalization. This method also has some disadvantages like complexity, sensitivity to channel variation and the need of a feedback channel for both end nodes. Finally, the maximum likelihood sequence detector was also proposed but is restricted to BPSK modulation and exponentially rising complexity are major drawbacks. The philosophy in this work is to avoid these disadvantages by using a time domain based system. The DFE is the equalizer of choice here because it provides a non-trivial BER performance improvement with very little increase in complexity. In this thesis, the problem of frequency selective channels in PLNC systems can be solved by properly adjusting the design of the system including the DFE. The other option is to redesign the equalizer to meet that goal. An AF DFE system is proposed in this work that provides very low complexity especially at the relay with little sensitivity to channel changes. A multi-antenna DNF DFE system is also proposed here with an improved performance. Finally, a new equalizer is designed for very low complexity and cost DNF approach with little sacrifice of BER performance. Matlab was used for the simulations with Monte Carlo method to verify the findings of this work through finding the BER performance of each system. This thesis opens the door for future improvement on the PLNC system. More research needs to be done like testing the proposed systems in real practical implementation and also the effect of adding channel coding to these systems.Iraqi Government, Ministry of Higher Educatio

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Design of optimal equalizers and precoders for MIMO channels

Channel equalization has been extensively studied as a method of combating ISI and ICI for high speed MIMO data communication systems. This dissertation focuses on optimal channel equalization in the presence of non-white observation noises with unknown PSD but bounded power-norm. A worst-case approach to optimal design of channel equalizers leads to an equivalent optimal H-infinity filtering problem for the MIMO communication systems. An explicit design algorithm is derived which not only achieves the zero-forcing (ZF) condition, but also minimizes the RMS error between the transmitted symbols and the received symbols. The second part of this dissertation investigates the design of optimal precoders which minimize the bit error rate (BER) subject to a fixed transmit-power constraint for the multiple antennas downlink communication channels under the perfect reconstruction (PR) condition. The closed form solutions are derived and an efficient design algorithm is proposed. The performance evaluations indicate that the optimal precoder design for multiple antennas communication systems proposed herein is an attractive/reasonable alternative to the existing precoder design techniques

Soft-decision equalization techniques for frequency selective MIMO channels

Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI

Semi Blind Time Domain Equalization for MIMO-OFDM Systems

In this thesis, a semi-blind time-domain equalization technique is proposed for general MIMO OFDM systems. The received OFDM symbols are shifted by more than or equal to the cyclic prefix (CP) length, and a blind equalizer is designed to completely suppress both inter-carrier interference (ICI) and inter-symbol interference (ISI) using second-order statistics of the shifted received OFDM symbols. Only a one-tap equalizer is needed to detect the time domain signals from the blind equalizer output, and one pilot OFDM symbol is utilized to estimate the required channel state information for the design of the one-tap equalizer. Simulation results show that this technique is robust against the number of shifts in excess of the CP length

High Dimensional Modulation and MIMO Techniques for Access Networks

Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless amplitudephase (CAP) and multiple-input multiple-output (MIMO) radio-over-fiber (RoF) systems. High dimensionality CAP modulation has been investigated in optical fiber systems. In this project we conducted the first experimental demonstration of 3 and 4 dimensional CAP with bit rates up to 10 Gb/s. These results indicate the potentiality of supporting multiple users with converged services. At the same time, orthogonal division multiple access (ODMA) systems for multiple possible dimensions of CAP modulation has been demonstrated for user and service allocation in wavelength division multiplexing (WDM) optical access network. 2 x 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially to be utilized for multiple service allocation to different users. MIMO multiplexing techniques with OFDM provides the scalability in increasing spectral effciency and bit rates for RoF systems. High dimensional CAP and MIMO multiplexing techniques are two promising solutions for supporting wired and hybrid wired-wireless access networks

Polynomial matrix decomposition techniques for frequency selective MIMO channels

For a narrowband, instantaneous mixing multi-input, multi-output (MIMO) communications system, the channel is represented as a scalar matrix. In this scenario, singular value decomposition (SVD) provides a number of independent spatial subchannels which can be used to enhance data rates or to increase diversity. Alternatively, a QR decomposition can be used to reduce the MIMO channel equalization problem to a set of single channel equalization problems. In the case of a frequency selective MIMO system, the multipath channel is represented as a polynomial matrix. Thus conventional matrix decomposition techniques can no longer be applied. The traditional solution to this broadband problem is to reduce it to narrowband form by using a discrete Fourier transform (DFT) to split the broadband channel into N narrow uniformly spaced frequency bands and applying scalar decomposition techniques within each band. This describes an orthogonal frequency division multiplexing (OFDM) based system. However, a novel algorithm has been developed for calculating the eigenvalue decomposition of a para-Hermitian polynomial matrix, known as the sequential best rotation (SBR2) algorithm. SBR2 and its QR based derivatives allow a true polynomial singular value and QR decomposition to be formulated. The application of these algorithms within frequency selective MIMO systems results in a fundamentally new approach to exploiting spatial diversity. Polynomial matrix decomposition and OFDM based solutions are compared for a wide variety of broadband MIMO communication systems. SVD is used to create a robust, high gain communications channel for ultra low signal-to-noise ratio (SNR) environments. Due to the frequency selective nature of the channels produced by polynomial matrix decomposition, additional processing is required at the receiver resulting in two distinct equalization techniques based around turbo and Viterbi equalization. The proposed approach is found to provide identical performance to that of an existing OFDM scheme while supporting a wider range of access schemes. This work is then extended to QR decomposition based communications systems, where the proposed polynomial approach is found to not only provide superior bit-error-rate (BER) performance but significantly reduce the complexity of transmitter design. Finally both techniques are combined to create a nulti-user MIMO system that provides superior BER performance over an OFDM based scheme. Throughout the work the robustness of the proposed scheme to channel state information (CSI) error is considered, resulting in a rigorous demonstration of the capabilities of the polynomial approach