SYNCHRONIZATION AND RESOURCE ALLOCATION IN DOWNLINK OFDM SYSTEMS

The next generation (4G) wireless systems are expected to provide universal personal and multimedia communications with seamless connection and very high rate transmissions and without regard to the users’ mobility and location. OFDM technique is recognized as one of the leading candidates to provide the wireless signalling for 4G systems. The major challenges in downlink multiuser OFDM based 4G systems include the wireless channel, the synchronization and radio resource management. Thus algorithms are required to achieve accurate timing and frequency offset estimation and the efficient utilization of radio resources such as subcarrier, bit and power allocation. The objectives of the thesis are of two fields. Firstly, we presented the frequency offset estimation algorithms for OFDM systems. Building our work upon the classic single user OFDM architecture, we proposed two FFT-based frequency offset estimation algorithms with low computational complexity. The computer simulation results and comparisons show that the proposed algorithms provide smaller error variance than previous well-known algorithm. Secondly, we presented the resource allocation algorithms for OFDM systems. Building our work upon the downlink multiuser OFDM architecture, we aimed to minimize the total transmit power by exploiting the system diversity through the management of subcarrier allocation, adaptive modulation and power allocation. Particularly, we focused on the dynamic resource allocation algorithms for multiuser OFDM system and multiuser MIMO-OFDM system. For the multiuser OFDM system, we proposed a lowiv complexity channel gain difference based subcarrier allocation algorithm. For the multiuser MIMO-OFDM system, we proposed a unit-power based subcarrier allocation algorithm. These proposed algorithms are all combined with the optimal bit allocation algorithm to achieve the minimal total transmit power. The numerical results and comparisons with various conventional nonadaptive and adaptive algorithmic approaches are provided to show that the proposed resource allocation algorithms improve the system efficiencies and performance given that the Quality of Service (QoS) for each user is guaranteed. The simulation work of this project is based on hand written codes in the platform of the MATLAB R2007b

Comparative Analysis of CMA and MMSE in MIMO-OFDM System

Channel estimation is one of the techniques used to achieve high data rates and low bit error rates in wireless communications. In wireless communication system, where Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing (MIMO-OFDM) exists, the effect of channel causes the received signal to be distorted which necessitates the receiver to have an insight of the channel known as the channel estimation. However, most of the existing techniques such as Least Square Error (LSE), Minimum Mean Square Error (MMSE) and Best Linear Unbiased Estimation Algorithm (BLUE) employ pilot symbols. High errors are observed in addition to computational complexity and in the platform other than MIMO-OFDM. In this paper, performances of Constant Modulus Algorithm (CMA) and MMSE are evaluated, and compared with each other in the 3x3 MIMO-OFDM systems. The system model for 3x3 MIMO-OFDM system incorporating each of CMA and MMSE consists of a transmitter, frequency selective channel and the receiver. 1000 bits are generated randomly and served as input signal. Three antennas configurations at the input of the frequency selective channel radiate the signal. The three antennas at the output of the channel receive the radiated power, processed by appropriate signal processing techniques. Each of MMSE and CMA techniques is performed at SNR of 5, 10 and 15dB. The system model is simulated using MATLAB 7.2 application package and evaluated using Mean Square Error (MSE) and convergence value. The results obtained show that CMA gives lower error than the MMSE and converges faster. Therefore, the study has shown the significant reduction in computational complexity and can be used by wireless design. Keywords: Constant Modulus Algorithm, Orthogonality, Channel Estimation, Multiple Antenna, Cyclic Prefix

An improved channel estimation approach for MIMO-OFDM systems

University of Technology, Sydney. Faculty of Engineering and Information Technology.In wireless environments, signals bounce off many obstacles such as mountains, buildings, trees, etc. as they propagate between transmitters and receivers. The resultant signal at the receive antenna is, therefore, often the sum of the attenuated transmitted signal and one or more delayed versions of the transmitted signal. The received signal also suffers from intersymbol interference which degrades the quality of signal to a certain extent. However, MIMO-OFDM systems are designed to take advantage of the multi-path properties in wireless communications and are capable of improving transmission rate, range and reliability simultaneously. MIMO-OFDM attracts a good deal of research and commercial interest because of the perceived benefits, and has been adopted in many wireless standards such as IEEE 802.1 In, IEEE 802.16e. Such systems are also potential candidates for fourth-generation (4G) systems. However, practical problems still exist in implementing MIMO-OFDM, for example, in the estimation of channel state information (CS1). This thesis studies the issues of MIMO, OFDM and the relevant techniques of MIMO-OFDM, and focuses on proposing a practical, low complexity and accurate channel estimation method for such systems. In a MIMO-OFDM system, CSI is required at the receiver to perform space-time decoding or diversity combining. In many practical wireless applications, the propagation environment is both complex and time-variant, leading to CSI estimation errors and overall system performance degradation. A variety of channel estimation approaches have been proposed in the literature to address this problem. One of the most important parameters of CSI is the number of significant or dominant propagation paths, also referred to as the number of channel taps. However, in most existing estimation schemes for MIMO-OFDM, there is an assumption that the number of channel taps is known at the receiver. In reality, in order to perform space-time decoding, the receiver needs to estimate the number of channel taps from the received signal with this estimation process sometimes aided by the insertion of pilot tones into the transmitted signal. In this thesis, a pilot-assisted, conditional model-order estimation (CME) based channel estimation algorithm is presented. The approach can be utilised to detect both the number of channel resolvable paths and channel gains for MIMO-OFDM systems. The performance of the proposed algorithm is compared with the commonly used minimum description length (MDL) algorithm by mean of simulation in the context of a 2x2 MIMO-OFDM system. Results indicate that the new algorithm is superior to the MDL algorithm in channel order estimation over an unknown, noisy, multipah fading channel with limited pilot assistance. Furthermore, the proposed scheme is tested in both fixed and mobile broadband MIMO-OFDM systems based on WiMAX techniques in Matlab simulation, and its capacity is verified again for those near practical broadband MIMO- OFDM systems in the absence of prior knowledge of model parameters. Finally, with the purpose to “make the thing work in practice”, a 2x2 MIMO baseband platform is built in order to demonstrate the proposed scheme. The platform consists of two DSP based, real-time development boards called SignalWAVe, produced by Lyrtech. Given the existing hardware components, the whole platform is built based on a fixed MIMO-OFDM system according to WiMAX standard, and the results demonstrate that the proposed algorithm is a valid approach in practice

Efficient space-frequency block coded pilot-aided channel estimation method for multiple-input-multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An iterative pilot-aided channel estimation technique for space-frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.Peer reviewe

Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Low Complexity Blind Equalization for OFDM Systems with General Constellations

This paper proposes a low-complexity algorithm for blind equalization of data in OFDM-based wireless systems with general constellations. The proposed algorithm is able to recover data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information of the channel and thus does not suffer from latency normally associated with blind methods. We also demonstrate how to reduce the complexity of the algorithm, which becomes especially low at high SNR. Specifically, we show that in the high SNR regime, the number of operations is of the order O(LN), where L is the cyclic prefix length and N is the total number of subcarriers. Simulation results confirm the favorable performance of our algorithm