On PAPR Reduction of OFDM using Partial Transmit Sequence with Intelligent Optimization Algorithms

In recent time, the demand for multimedia data services over wireless links has grown up rapidly. Orthogonal Frequency Division Multiplexing (OFDM) forms the basis for all 3G and beyond wireless communication standards due to its efficient frequency utilization permitting near ideal data rate and ubiquitous coverage with high mobility. OFDM signals are prone to high peak-to-average-power ratio (PAPR). Unfortunately, the high PAPR inherent to OFDM signal envelopes occasionally drives high power amplifiers (HPAs) to operate in the nonlinear region of their characteristic leading out-of-band radiation, reduction in efficiency of communication system etc. A plethora of research has been devoted to reducing the performance degradation due to the PAPR problem inherent to OFDM systems. Advanced techniques such as partial transmit sequences (PTS) and selected mapping (SLM) have been considered most promising for PAPR reduction. Such techniques are seen to be efficient for distortion-less signal processing but suffer from computational complexity and often requires transmission of extra information in terms of several side information (SI) bits leading to loss in effective data rate. This thesis investigates the PAPR problem using Partial Transmit Sequence (PTS) scheme, where optimization is achieved with evolutionary bio-inspired metaheuristic stochastic algorithms. The phase factor optimization in PTS is used for PAPR reduction. At first, swarm intelligence based Firefly PTS (FF-PTS) algorithm is proposed which delivers improved PAPR performance with reduced searching complexity. Following this, Cuckoo Search based PTS (CS-PTS) technique is presented, which offers good PAPR performance in terms of solution quality and convergence speed. Lastly, Improved Harmony search based PTS (IHS-PTS) is introduced, which provides improved PAPR. The algorithm has simple structure with a very few parameters for larger PTS sub-blocks. The PAPR performance of the proposed technique with different parameters is also verified through extensive computer simulations. Furthermore, complexity analysis of algorithms demonstrates that the proposed schemes offer significant complexity reduction when compared to standard PAPR reduction techniques. Findings have been validated through extensive simulation tests

Chicken Swarm Optimization for PTS based PAPR Reduction in OFDM Systems

Partial transmit sequence (PTS) is a well-known PAPR reduction scheme for the OFDM system. One of the major challenge of this scheme is to find an optimal phase vector using exhaustive search over all the allowed phase factor combinations. This leads to increased search complexity which grows exponentially as the number of sub-blocks is increased. In this paper, chicken swarm optimization (CSO) based PTS system is designed that aims to find an optimal solution in less number of average iterations and therefore results in reduced computational complexity of the system. We have proposed two categories of the algorithm: (i) CSO-PTS system without threshold limit on PAPR (ii) CSO-PTS system with threshold limit on PAPR. Both the schemes offer effective trade-offs between the computational complexity and the PAPR reduction capability of the system. Simulation results confirm that our proposed schemes perform well in terms of low computational complexity, lesser number of average iterations and improved PAPR reduction capability of the OFDM signal without any loss in BER performance of the system

PERFORMANCE EVALUATION OF A MULTICARRIER MIMO SYSTEM BASED ON DFT-PRECODING AND SUBCARRIER MAPPING

The ever-increasing end user demands are instigating the development of innovative methods targeting not only data rate enhancement but additionally better service quality in each subsequent wireless communication standard. This quest to achieve higher data rates has compelled the next generation communication technologies to use multicarrier systems e.g. orthogonal frequency division multiplexing (OFDM), while also relying on the multiple-input multiple-output (MIMO) technology. This paper is focused on implementing a MIMO-OFDM system and on using various techniques to optimize it in terms of the bit-error rate performance. The test case considered is a system implementation constituting the enabling technologies for 4G and beyond communication systems. The bit-error rate optimizations considered are based on preceding the OFDM modulation step by Discrete Fourier Transform (DFT) while also considering various subcarrier mapping schemes. MATLAB-based simulation of a 2 × 2 MIMO-OFDM system exhibits a maximum of 2 to 5 orders of magnitude reduction in bit-error rate due to DFT-precoding and subcarrier mapping respectively at high signal-to-noise ratio values in various environments. A 2-3dBs reduction in peak-to-average power ratio due to DFT-precoding in different environments is also exhibited in the various simulations

A Comparison Study of PAPR Reduction in OFDM Systems Based on Swarm Intelligence Algorithms

Optimization algorithms have been one of the most important research topics in Computational Intelligence Community. They are widely utilized mathematical functions that solve optimization problems in a variety of purposes via the maximization or minimization of a function. The swarm intelligence (SI) optimization algorithms are an active branch of Evolutionary Computation, they are increasingly becoming one of the hottest and most important paradigms, several algorithms were proposed for tackling optimization problems. The most respected and popular SI algorithms are Ant colony optimization (ACO) and particle swarm optimization (PSO). Fireworks Algorithm (FWA) is a novel swarm intelligence algorithm, which seems effective at finding a good enough solution of a complex optimization problem. In this chapter we proposed a comparison study to reduce the high PAPR (Peak-to-Average Power Ratio) in OFDM systems based on the swarm intelligence algorithms like simulated annealing (SA), particle swarm optimization (PSO), fireworks algorithm (FWA), and genetic algorithm (GA). It turns out from the results that some algorithms find a good enough solutions and clearly outperform the others candidates in both convergence speed and global solution accuracy

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Massive MIMO transmission techniques

Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. These requirements should be met while assuring energy efficiency for mobile devices and base stations. Several technologies are being proposed for 5G, but a consensus begins to emerge. Most likely, the future core 5G technologies will include massive MIMO (Multiple Input Multiple Output) and beamforming schemes operating in the millimeter wave spectrum. As soon as the millimeter wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped. The present work proposes a new transmission system with bi-dimensional antenna arrays working at millimeter wave frequencies, where the multiple antenna configurations can be used to obtain very high gain and directive transmission in point to point communications. A combination of beamforming with a constellation shaping scheme is proposed, that enables good user isolation and protection against eavesdropping, while simultaneously assuring power efficient amplification of multi-level constellations

Optical Wireless Data Center Networks

Bandwidth and computation-intensive Big Data applications in disciplines like social media, bio- and nano-informatics, Internet-of-Things (IoT), and real-time analytics, are pushing existing access and core (backbone) networks as well as Data Center Networks (DCNs) to their limits. Next generation DCNs must support continuously increasing network traffic while satisfying minimum performance requirements of latency, reliability, flexibility and scalability. Therefore, a larger number of cables (i.e., copper-cables and fiber optics) may be required in conventional wired DCNs. In addition to limiting the possible topologies, large number of cables may result into design and development problems related to wire ducting and maintenance, heat dissipation, and power consumption. To address the cabling complexity in wired DCNs, we propose OWCells, a class of optical wireless cellular data center network architectures in which fixed line of sight (LOS) optical wireless communication (OWC) links are used to connect the racks arranged in regular polygonal topologies. We present the OWCell DCN architecture, develop its theoretical underpinnings, and investigate routing protocols and OWC transceiver design. To realize a fully wireless DCN, servers in racks must also be connected using OWC links. There is, however, a difficulty of connecting multiple adjacent network components, such as servers in a rack, using point-to-point LOS links. To overcome this problem, we propose and validate the feasibility of an FSO-Bus to connect multiple adjacent network components using NLOS point-to-point OWC links. Finally, to complete the design of the OWC transceiver, we develop a new class of strictly and rearrangeably non-blocking multicast optical switches in which multicast is performed efficiently at the physical optical (lower) layer rather than upper layers (e.g., application layer). Advisors: Jitender S. Deogun and Dennis R. Alexande

AI/ML assisted Li-Fi communication systems for the future 6G communication systems

Information and communication technologies are developing rapidly, and tremendous growth along with advancements was observed over the last few decades. Requirements for bandwidth and capacity of current networks are overgrowing due to the increase in the use of high-speed Internet, video conferencing, streaming, Internet of things, etc. An ever-growing demand for increasing data volumes and multimedia services has led to an overload in the traditional radio frequency (RF) spectrum is used, and there is a need for transition from RF carrier to optical media. In this work, a novel Deep Neural Network (DNN) was proposed to mitigate nonlinearities caused by Perovskite material-based components of Li-Fi communication system, and measurement of Perovskite Photodiodes (PePD) the Optical Communications Laboratory in the National and Kapodistrian University of Athens. Due to the analysis of the PePDs bandwidth measurement, the highest cut-off frequency was measured 36,25kHz at 635nm wavelength. The proposed DNN showed promising results in comparison with Support Vector Machines (SVM) model, both models were trained on the dataset generated by OFDM based - Li-Fi systems. This technique successfully mitigates the nonlinearity of the PePD and the interference generated by the multipath channel. The simulation results reveal that the proposed scheme outperforms conventional techniques in terms of BER performance demonstrating the potential and validity of DL in the Li-Fi system