NOVEL OFDM SYSTEM BASED ON DUAL-TREE COMPLEX WAVELET TRANSFORM

The demand for higher and higher capacity in wireless networks, such as cellular, mobile and local area network etc, is driving the development of new signaling techniques with improved spectral and power efficiencies. At all stages of a transceiver, from the bandwidth efficiency of the modulation schemes through highly nonlinear power amplifier of the transmitters to the channel sharing between different users, the problems relating to power usage and spectrum are aplenty. In the coming future, orthogonal frequency division multiplexing (OFDM) technology promises to be a ready solution to achieving the high data capacity and better spectral efficiency in wireless communication systems by virtue of its well-known and desirable characteristics. Towards these ends, this dissertation investigates a novel OFDM system based on dual-tree complex wavelet transform (D

A Study on PAPR Reduction in OFDM System using Hybrid Continuous Modulus Algorithm

ABSTRACT PAPR is a generic problem in OFDM system. Loss of data at transmitter and receiver end is an inherit part of communication system. Different techniques have been proposed to solve this PAPR problem based on artificial intelligence. A PAPR reduction way for OFDM system is proposed, inspired by constant modulus property known as weight pattern hybrid continuous modulus algorithm. This coupled with the idea of weight pattern to change the scale of convergence with alter step size for optimal solution. Proposed method is tested on OFDM system for PAPR value and comparison is made with different techniques in literature. Test results shows the efficacy of projected method

Interference mitigation techniques for wireless OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is a promising multicarrier wireless system for transmission of high-rate data stream with spectral efficiency and fading immunity. Conventional OFDM system use efficient IFFT and FFT to multiplex the signals in parallel at the transmitter and receiver respectively. On the other hand, wavelet based OFDM system uses orthonormal wavelets which are derived from a multistage tree-structured wavelet family. The Fourier based and wavelet based OFDM systems are studied in this dissertation. Two types of QAM schemes, circular and square modulations are used to compare the performance in both OFDM systems. A new approach of determining exact BER for optimal circular QAM is proposed. In addition, the presence of narrowband interference (NBI) degrades the performance of OFDM systems. Thus, a mitigation technique is necessary to suppress NBI in an OFDM system. Recent mitigation techniques can be broadly categorized into frequency domain cancellation, receiver windowing and excision filtering. However, none of the techniques considers wavelet based OFDM. Therefore, an interference cancelation algorithm has been proposed to work for both OFDM platforms. The performance results of two OFDM schemes applicable to digital video broadcasting (DVB)-terrestrial system and under the effect of impulsive noise interference are also studied. BER performances are obtained in all results. It has been shown that wavelet based OFDM system has outperformed Fourier based OFDM system in many cases

Spectrum Optimisation in Wireless Communication Systems: Technology Evaluation, System Design and Practical Implementation

Two key technology enablers for next generation networks are examined in this thesis, namely Cognitive Radio (CR) and Spectrally Efficient Frequency Division Multiplexing (SEFDM). The first part proposes the use of traffic prediction in CR systems to improve the Quality of Service (QoS) for CR users. A framework is presented which allows CR users to capture a frequency slot in an idle licensed channel occupied by primary users. This is achieved by using CR to sense and select target spectrum bands combined with traffic prediction to determine the optimum channel-sensing order. The latter part of this thesis considers the design, practical implementation and performance evaluation of SEFDM. The key challenge that arises in SEFDM is the self-created interference which complicates the design of receiver architectures. Previous work has focused on the development of sophisticated detection algorithms, however, these suffer from an impractical computational complexity. Consequently, the aim of this work is two-fold; first, to reduce the complexity of existing algorithms to make them better-suited for application in the real world; second, to develop hardware prototypes to assess the feasibility of employing SEFDM in practical systems. The impact of oversampling and fixed-point effects on the performance of SEFDM is initially determined, followed by the design and implementation of linear detection techniques using Field Programmable Gate Arrays (FPGAs). The performance of these FPGA based linear receivers is evaluated in terms of throughput, resource utilisation and Bit Error Rate (BER). Finally, variants of the Sphere Decoding (SD) algorithm are investigated to ameliorate the error performance of SEFDM systems with targeted reduction in complexity. The Fixed SD (FSD) algorithm is implemented on a Digital Signal Processor (DSP) to measure its computational complexity. Modified sorting and decomposition strategies are then applied to this FSD algorithm offering trade-offs between execution speed and BER

On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA–OFDM Wireless Communication System

Space Division Multiple Access(SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of SDMA and OFDM has emerged as a most competitive technology for future wireless communication system. In the SDMA uplink, multiple users communicate simultaneously with a multiple antenna Base Station (BS) sharing the same frequency band by exploring their unique user specific-special spatial signature. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. On the other hand, due to exhaustive search mechanism, the optimal Maximum Likelihood (ML) detector is limited by high computational complexity, which increases exponentially with increasing number of simultaneous users. Hence, cost function minimization based Minimum Error Rate (MER) detectors are preferred, which basically minimize the probability of error by iteratively updating receiver’s weights using adaptive algorithms such as Steepest Descent (SD), Conjugate Gradient (CG) etc. The first part of research proposes Optimization Techniques (OTs) aided MER detectors to overcome the shortfalls of the CG based MER detectors. Popular metaheuristic search algorithms like Adaptive Genetic Algorithm (AGA), Adaptive Differential Evolution Algorithm (ADEA) and Invasive Weed Optimization (IWO), which rely on an intelligent search of a large but finite solution space using statistical methods, have been applied for finding the optimal weight vectors for MER MUD. Further, it is observed in an overload SDMA–OFDM system that the channel output phasor constellation often becomes linearly non-separable. With increasing the number of users, the receiver weight optimization task turns out to be more difficult due to the exponentially increased number of dimensions of the weight matrix. As a result, MUD becomes a challenging multidimensional optimization problem. Therefore, signal classification requires a nonlinear solution. Considering this, the second part of research work suggests Artificial Neural Network (ANN) based MUDs on thestandard Multilayer Perceptron (MLP) and Radial Basis Function (RBF) frameworks fo