Subcarrier Filtering For Spectrally Efficient Multicarrier Modulation Schemes and Its Impact on PAPR: A Unified Approach

Multicarrier modulation (MCM) based schemes have been a major contributing factor in revolutionizing cellular networks due to their ability to overcome fading. One of the popular scheme orthogonal frequency division multiple access (OFDMA), having been part of 4G, is also adapted as part of 5G enhanced mobile broadband (eMBB).  Though it has several advantages, spectral efficiency (SE) and peak to average power ratio (PAPR) have been two major concerns which have attracted lot of attention resulting in proposals of several other MCM schemes.  But most of these studies have treated the two issues independently. This paper in particular studies the subcarrier filtering approach to improve the spectral efficiency of MCM scheme and its impact on the overall PAPR of such schemes. The analysis shows that the PAPR improvement is also achieved by such filters meant for spectral confinement and the simulation results validate the same provoking a unified research direction less explored till now

Digital signal processing techniques for peak-to-average power ratio mitigation in MIMO–OFDM systems

The focus of this thesis is to mitigate the very large peak-to-average transmit power ratios (PAPRs) inherent to conventional orthogonal frequency division multiplexing (OFDM) systems, particularly in the context of transmission over multi-input multi-output (MIMO) wireless broadband channels. This problem is important as a large PAPR generally needs an expensive radio frequency (RF) power amplifier at the transmitter due to the requirement for linear operation over a wide amplitude range and such a cost would be compounded when multiple transmit antennas are used. Advanced signal processing techniques which can reduce PAPR whilst retain the integrity of digital transmission therefore have considerable potential for application in emergent MIMO–OFDM wireless systems and form the technical contributions of this study. [Continues.

Improved Hybrid Blind PAPR Reduction Algorithm for OFDM Systems

The ever growing demand for high data rate communication services resulted into the development of long-term evolution (LTE) technology. LTE uses orthogonal frequency division multiplexing (OFDM) as a transmission technology in its PHY layer for down-link (DL) communications. OFDM is spectrally efficient multicarrier modulation technique ideal for high data transmissions over highly time and frequency varying channels. However, the transmitted signal in OFDM can have high peak values in the time domain due to inverse fast Fourier transform (IFFT) operation. This creates high peak-to-average power ratio (PAPR) when compared to single carrier systems. PAPR drives the power amplifiers to saturation degrading its efficiency by consuming more power. In this paper a hybrid blind PAPR reduction algorithm for OFDM systems is proposed, which is a combination of distortion technique (Clipping) and distortionless technique (DFT spreading). The DFT spreading is done prior to clipping reducing significantly the probability of having higher peaks in the composite signal prior to transmission. Simulation results show that the proposed algorithm outperforms unprocessed conventional OFDM transmission by 9 dB. Comparison with existing blind algorithms shows 7 dB improvement at error rate 10–3 and 3 dB improvement at error rate 10–1 when operating in flat fading and doubly dispersive channels, respectively.Keywords:    LTE Systems; OFDM; Peak to Average Power Ratio; DFT spreading; Signal to Noise Power Ratio

Adjustable dynamic range for paper reduction schemes in large-scale MIMO-OFDM systems

In a multi-input-multi-output (MIMO) communication system there is a necessity to limit the power that the output antenna amplifiers can deliver. Their signal is a combination of many independent channels, so the demanded amplitude can peak to many times the average value. The orthogonal frequency division multiplexing (OFDM) system causes high peak signals to occur because many subcarrier components are added by an inverse discrete Fourier transformation process at the base station. This causes out-of-band spectral regrowth. If simple clipping of the input signal is used, there will be in-band distortions in the transmitted signals and the bit error rate will increase substantially. This work presents a novel technique that reduces the peak-to-average power ratio (PAPR). It is a combination of two main stages, a variable clipping level and an Adaptive Optimizer that takes advantage of the channel state information sent from all users in the cell. Simulation results show that the proposed method achieves a better overall system performance than that of conventional peak reduction systems in terms of the symbol error rate. As a result, the linear output of the power amplifiers can be minimized with a great saving in cost

Waveform Design for Ground-Penetrating Radar

A ground-penetrating radar is being designed to find subterranean structures. This is difficult to do because of varying mediums. Having more bandwidth can help mitigate this problem. Because the frequency spectrum is so cluttered, one method to do this is to use non-contiguous orthogonal frequency division multiplexing (NC-OFDM) to occupy several free areas of the spectrum. An NC-OFDM waveform was designed and optimized with respect to peak-to-average-power ratio, orthogonality, spectral leakage and autocorrelation sidelobes. Techniques such as the use of a Zadoff-Chu sequence and a gap filling algorithm were implemented to do this. The waveform was tested in simulation to show that while computationally expensive, this may be a viable waveform for ground-penetrating radar

Optimizing multi-antenna M-MIMO DM communication systems with advanced linearization techniques for RF front-end nonlinearity compensation in a comprehensive design and performance evaluation study

The study presented in this research focuses on linearization strategies for compensating for nonlinearity in RF front ends in multi-antenna M-MIMO OFDM communication systems. The study includes the design and evaluation of techniques such as analogue pre-distortion (APD), crest factor reduction (CFR), multi-antenna clipping noise cancellation (M-CNC), and multi-clipping noise cancellation (MCNC). Nonlinearities in RF front ends can cause signal distortion, leading to reduced system performance. To address this issue, various linearization methods have been proposed. This research examines the impact of antenna correlation on power amplifier efficiency and bit error rate (BER) of transmissions using these methods. Simulation studies conducted under high signal-to-noise ratio (SNR) regimes reveal that M-CNC and MCNC approaches offer significant improvement in BER performance and PA efficiency compared to other techniques. Additionally, the study explores the influence of clipping level and antenna correlation on the effectiveness of these methods. The findings suggest that appropriate linearization strategies should be selected based on factors such as the number of antennas, SNR, and clipping level of the system