The discrete cosine transform (DCT), introduced by Ahmed, Natarajan and Rao, has been used in many applications of digital signal processing, data compression and information hiding. There are four types of the discrete cosine transform. In simulating the discrete cosine transform, we propose a generalized discrete cosine transform with three parameters, and prove its orthogonality for some new cases. A new type of discrete cosine transform is proposed and its orthogonality is proved. Finally, we propose a generalized discrete W transform with three parameters, and prove its orthogonality for some new cases. Keywords: Discrete Fourier transform, discrete sine transform, discrete cosine transform, discrete W transform Nigerian Journal of Technological Research , vol7(1) 2012

On discrete cosine transform

We present rational rate k/n punctured convolutional codes (n up to 8, k=1, /spl middot//spl middot//spl middot/, n-1, and constraint length /spl nu/ up to 8) with good performance. Many of these codes improve the free distance and (or) weight spectra over previously reported codes with the same parameters. The tabulated codes are found by an exhaustive (or a random) search.

Rational Rate Punctured Convolutional Codes for Soft-Decision Viterbi Decoding

Orthogonal frequency division multiplexing (OFDM) is an efficient multi-carrier modulation technique that underlies most of the current and probably future high-speed wireless communication systems. However, the OFDM waveform is characterized by a high peak-to-average power ratio (PAPR), especially when a large number of subcarriers are used. A high PAPR is a major waveform defect since it leads to non-linear distortion when passing through the transmitter’s power amplifier. Most of the PAPR reduction techniques found in the literature reduce the PAPR mainly at the cost of either excessive computational complexity or degrading the transmission bit error rate (BER). We propose a low-complexity technique for PAPR reduction based on linear scaling of a portion of signal coefficients by an optimal factor. This paper is backed up by the extensive analysis of various performance metrics, which leads to optimal choices of key parameters and hence maximum achievable gains. The analytic and simulated results show that the proposed technique is capable of reducing the PAPR effectively with negligible effect on BER in return for a slight reduction in data rate. For example, for 1024 subcarriers, the PAPR can be reduced from 13 dB to below 7.4 or 6.9 dB, in return for only 1% or 2% reduction in data rate, respectively. In addition, the achievable PAPR varies very slightly in response to increasing the number of subcarriers. This offers a highly competitive and flexible tradeoff compared with those provided by current techniques found in the literature. Therefore, this technique has a very good potential for practical application in current and future OFDM-based systems, especially those which employ a very large number of subcarriers, such as LTE, DVB-T2, and 5G systems.

/pdf/an-optimal-low-complexity-papr-reduction-technique-for-next-50uejlzj05.pdf

An Optimal Low Complexity PAPR Reduction Technique for Next Generation OFDM Systems

Iterative clipping and filtering (ICF) is a straight-forward method for reducing the peak-to-average power ratio (PAPR) of signals in orthogonal frequency-division multiplexing (OFDM) system. Recently, convex optimization has been used to find the optimal filter coefficients that minimize the error vector magnitude (EVM) and meet the PAPR constraint. However, high-computation complexity may be incurred when solving the convex optimization problem. Therefore, we develop an efficient PAPR reduction method that uses the time-domain kernel matrix to generate the PAPR-reduction signal. Besides, we relax the assumption that the clipping noise is a series of uncorrelated parabolic pulses and apply the proposed method to more general cases. Based on the instantaneous observation of clipping noise, the proposed method constructs a simple time-domain kernel matrix and employs the curve fitting approach to optimize the corresponding scaling factors. The simulation results show that the proposed method can achieve very close performance to that using convex optimization in terms of both the PAPR reduction and EVM while the computational cost is reduced greatly. In addition, due to the decrease of iteration numbers and computational complexity, the proposed method is more efficient than some existing clipping and filtering methods.

/pdf/an-enhanced-iterative-clipping-and-filtering-method-using-2r5sas8247.pdf

An Enhanced Iterative Clipping and Filtering Method Using Time-Domain Kernel Matrix for PAPR Reduction in OFDM Systems

One of the challenges in rollout of 5G is utilizing the radio communication which is not accessible by today’s radio system. To achieve a high data rate, it is necessary to make 5G networks compatible with advanced waveform. In this correspondence, we discussed advanced waveform technique non-orthogonal multiple access (NOMA) and filter bank multicarrier (FBMC) for 5G network. The design of advanced form technique compatible with advanced wireless communication is very important to fulfill the vision the 5G. Peak average to power ratio (PAPR) is viewed as a significant issue in actualizing NOMA and FBMC framework. PAPR reduction design for FBMC has been presented in the writing survey, yet PAPR decrease methods in NOMA are not investigated up until this point. In that regard are different downsides of minimization techniques introduced in the review. In the present investigation, we have inspected and analyzed the presence of the reduction systems and proposed a hybrid strategy (DSLM-CT) based on discrete selective mapping (DSLM) and circular transformation technique. Further, several parameters are discussed and analyzed. At long last, it is reasoned that the exhibition of the proposed hybrid technique is better than the existed minimization methods. Additionally, it is also observed that the implementation of proposed technique reduces the power consumption of solid state power amplifier.

A comprehensive study of PAPR reduction techniques: design of DSLM-CT joint reduction technique for advanced waveform

Compressed Sensing (CS) has been proposed as a low-complexity ECG data compression scheme for wearable wireless bio-sensor devices. However, CS decoding is characterized by high computational complexity. As a result, it represents a burden to the computational and energy resources of the network gateway node, where decoding is performed. In this article, we propose a Fast Compressive Electrocardiography (FCE) technique to address this problem. CS decoding in FCE is based on Weighted Regularized Least-Squares (WRLS), rather than the standard approach based on $\ell _{1}$ norm minimization. The WRLS formulation takes into account prior knowledge of ECG signal properties to estimate an optimally compact and accurate representation of ECG signals. Numerical results show that decoding by FCE is on average 33 times faster than the fastest tested CS-based ECG decoding technique. In addition, high-quality ECG signal reconstruction by FCE is achieved at 32% higher compression ratio. Therefore, FCE can contribute to improving the overall energy and computational resource efficiency of CS-based remote ECG monitoring systems.

/pdf/a-fast-compressed-sensing-decoding-technique-for-remote-ecg-1zkmusu7ws.pdf

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

Most of the literature on compressed sensing has not paid enough attention to scenarios in which the number of acquired measurements is insufficient to satisfy minimal exact reconstruction requirements. In practice, encountering such scenarios is highly likely, either intentionally or unintentionally, that is, due to high sensing cost or to the lack of knowledge of signal properties. We analyze signal reconstruction performance in this setting. The main result is an expression of the reconstruction error as a function of the number of acquired measurements.

https://onlinelibrary.wiley.com/doi/pdf/10.4218/etrij.13.0112.0312

Performance Analysis of Compressed Sensing Given Insufficient Random Measurements

Ultra-wideband (UWB) systems have witnessed a debate over whether they may cause interference to other existing and future narrowband systems sharing their band of operation. The detect and avoid (DAA) mechanism was developed as a solution to reduce interference to narrowband systems in order to ease regulatory concerns. It works by adaptively reducing the transmitted power at the overlapping bands upon detecting an active narrowband link. However, employing DAA degrades the performance of UWB transmissions. In this paper, we present the Korean UWB regulations as an example of regulations that require DAA in certain bands. We investigate DAA’s impact on performance and propose a method to mitigate it, which provides UWB with the more efficient support of the DAA mechanism and enables it to avoid a larger number of narrowband users while sustaining the data rate. Results show significant improvement in performance with the application of our technique compared to conventional performance.

Improvement of ultra-wideband link performance over bands requiring interference mitigation in korea

Compressed sensing is an emerging technique in the field of digital signal acquisition. It promises almost exact recovery of high-dimensional signals from a very small set of measurements. However, this technique is challenged by the task of recovering signals immersed in noise. In this paper, we derive upper and lower bounds on mean squared recovery error of noisy signals. These bounds are valid for any number of acquired measurements and at any signal-to-noise ratio. This work is highly useful for the design of any compressed sensing-based real world application by quantifying recovery error entailed with realistic digital signal acquisition scenarios. Copyright © 2013 John Wiley & Sons, Ltd.

Ahmad M. Rateb

Papers

An Optimal Low Complexity PAPR Reduction Technique for Next Generation OFDM Systems

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

Performance Analysis of Compressed Sensing Given Insufficient Random Measurements

Improvement of ultra-wideband link performance over bands requiring interference mitigation in korea

Recovery error bounds on compressed sensing of noisy signals