One of the challenging issues for Orthogonal Frequency Division Multiplexing (OFDM) system is its high Peak-to-Average Power Ratio (PAPR). In this paper, we review and analysis different OFDM PAPR reduction techniques, based on computational complexity, bandwidth expansion, spectral spillage and performance. We also discuss some methods of PAPR reduction for multiuser OFDM broadband communication systems.

https://engold.ui.ac.ir/~sabahi/Advanced%20digital%20communication/An%20Overview%20Peak-to-Average%20Power%20Ratio%20Reduction%20Reduction%20Techniques%20for%20OFDM%20Signals.pdf

An Overview: Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

Quadrature amplitude modulation (QAM) is an attractive technique to achieve high rate transmission without increasing the bandwidth. A great deal of attention has been devoted to the study of bit error rate (BER) performance of QAM, and approximate expressions for the bit error probability of QAM have been developed in many places in the literature. However, the exact and general BER expression of QAM with an arbitrary constellation size has not been derived yet. We provide an exact and general closed-form expression of the BER for one-dimensional and two-dimensional amplitude modulations, i.e., PAM and QAM, under an additive white Gaussian noise (AWGN) channel when Gray code bit mapping is employed. The provided BER expressions offer a convenient way to evaluate the performance of PAM and QAM systems for various cases of practical interest. Moreover, simple approximations can be found from our expressions, which are the same as the well-known approximations, if only the dominant terms are considered.

On the general BER expression of one- and two-dimensional amplitude modulations

From the Publisher:
Orthogonal frequency-division multiplexing (OFDM) is a method of digital modulation in which a signal is split into several narrowband channels at different frequencies.
CDMA is a form of multiplexing, which allows numerous signals to occupy a single transmission channel, optimising the use of available bandwidth. Multiplexing is sending multiple signals or streams of information on a carrier at the same time in the form of a single, complex signal and then recovering the separate signals at the receiving end.
Multi-Carrier (MC) CDMA is a combined technique of Direct Sequence (DS) CDMA (Code Division Multiple Access) and OFDM techniques. It applies spreading sequences in the frequency domain.
Wireless communications has witnessed a tremendous growth during the past decade and further spectacular enabling technology advances are expected in an effort to render ubiquitous wireless connectivity a reality.
This technical in-depth book is unique in its detailed exposure of OFDM, MIMO-OFDM and MC-CDMA. A further attraction of the joint treatment of these topics is that it allows the reader to view their design trade-offs in a comparative context.
Divided into three main parts:
Part I provides a detailed exposure of OFDM designed for employment in various applications
Part II is another design alternative applicable in the context of OFDM systems where the channel quality fluctuations observed are averaged out with the aid of frequency-domain spreading codes, which leads to the concept of MC-CDMA
Part III discusses how to employ multiple antennas at the base station for the sake of supporting multiple users in the uplink
Portrays theentire body of knowledge currently available on OFDMProvides the first complete treatment of OFDM, MIMO(Multiple Input Multiple Output)-OFDM and MC-CDMAConsiders the benefits of channel coding and space time coding in the context of various application examples and features numerous complete system design examplesConverts the lessons of Shannon's information theory into design principles applicable to practical wireless systemsCombines the benefits of a textbook with a research monograph where the depth of discussions progressively increase throughout the book

This all-encompassing self-contained treatment will appeal to researchers, postgraduate students and academics, practising research and development engineers working for wireless communications and computer networking companies and senior undergraduate students and technical managers.

OFDM and MC-CDMA for Broadband Multi-User Communications, WLANs and Broadcasting

The objective of this survey is to provide the readers and practitioners in the industry with a broader understanding of the high peak-to-average power ratio (PAPR) problem in orthogonal frequency division multiplexing (OFDM) systems and generate a taxonomy of the available solutions to mitigate the problem. Beginning with a description of OFDM systems, the survey describes the most commonly encountered impediment of OFDM systems, the PAPR problem and consequent impact on power amplifiers leading to nonlinear distortion. The survey clearly defines the metrics based on which the performance of PAPR reduction schemes can be evaluated. A taxonomy of PAPR reduction schemes classifies them into signal distortion, multiple signaling and probabilistic, and coding techniques with further classification within each category. We also provide complexity analyses for a few PAPR reduction methods to demonstrate the differences in complexity requirements between different methods. Moreover, the paper provides insights into the transmitted power constraint by showing the possibility of satisfying the constraint without added complexity by the use of companding transforms with suitably chosen companding parameters. The rapid growth in multimedia-based applications has triggered an insatiable thirst for high data rates and hence increased demand on OFDM-based wireless systems that can support high data rates and high mobility. As the data rates and mobility supported by the OFDM system increase, the number of subcarriers also increases, which in turn leads to high PAPR. As future OFDM-based systems may push the number of subcarriers up to meet the higher data rates and mobility demands, there will be also a need to mitigate the high PAPR that arises, which will likely spur new research activities. The authors believe that this survey will serve as a valuable pedagogical resource for understanding the current research contributions in the area of PAPR reduction in OFDM systems, the different techniques that are available for designers and their trade-offs towards developing more efficient and practical solutions, especially for future research in PAPR reduction schemes for high data rate OFDM systems.

Peak-To-Average Power Ratio Reduction in OFDM Systems: A Survey And Taxonomy

By employing spatial multiplexing, multiple-input multiple-output (MIMO) wireless antenna systems provide increases in capacity without the need for additional spectrum or power. Zero-forcing (ZF) detection is a simple and effective technique for retrieving multiple transmitted data streams at the receiver. However the detection requires knowledge of the channel state information (CSI) and in practice accurate CSI may not be available. In this letter, we investigate the effect of channel estimation error on the performance of MIMO ZF receivers in uncorrelated Rayleigh flat fading channels. By modeling the estimation error as independent complex Gaussian random variables, tight approximations for both the post-processing SNR distribution and bit error rate (BER) for MIMO ZF receivers with M-QAM and M-PSK modulated signals are derived in closed-form. Numerical results demonstrate the tightness of our analysis

On the Performance of the MIMO Zero-Forcing Receiver in the Presence of Channel Estimation Error

In this paper, we introduce a simple geometric approach that is based on signal-space concepts to efficiently evaluate the performance of M-ary phase-shift keying (M-PSK) and M-ary quadrature amplitude modulation (M-QAM) schemes over an additive white Gaussian noise channel. In particular, new bit error rate approximations are derived and shown to be in excellent agreement with Monte Carlo simulation results.

M-PSK and M-QAM BER computation using signal-space concepts

A general companding transform method is proposed to effectively reduce peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. By compressing large signals while enhancing small signals along with taking into account their statistical characteristics, this method can achieve significant reduction in PAPR with low implementation complexity. Specifically, we present the design criteria of the transform, which enable effective tradeoff between reduction in PAPR and bit-error rate performance of the OFDM system. It is shown by simulations that the proposed method may significantly improve the performance of OFDM systems in radio channels by carefully choosing the companding form and parameters.

Companding transform for reduction in peak-to-average power ratio of OFDM signals

A companding transform-based scheme for reducing peak-to-average power ratio (PAPR) of transmitted OFDM signals is proposed. This scheme effectively compresses large signals while enhancing small ones, achieving a significant reduction of PAPR with a low computational complexity.

Reduction of peak-to-average power ratio of OFDM signals with companding transform

The thriving of artificial intelligence (AI) applications is driving the further evolution of wireless networks. It has been envisioned that 6G will be transformative and will revolutionize the evolution of wireless from “connected things” to “connected intelligence”. However, state-of-the-art deep learning and big data analytics based AI systems require tremendous computation and communication resources, causing significant latency, energy consumption, network congestion, and privacy leakage in both of the training and inference processes. By embedding model training and inference capabilities into the network edge, edge AI stands out as a disruptive technology for 6G to seamlessly integrate sensing, communication, computation, and intelligence, thereby improving the efficiency, effectiveness, privacy, and security of 6G networks. In this paper, we shall provide our vision for scalable and trustworthy edge AI systems with integrated design of wireless communication strategies and decentralized machine learning models. New design principles of wireless networks, service-driven resource allocation optimization methods, as well as a holistic end-to-end system architecture to support edge AI will be described. Standardization, software and hardware platforms, and application scenarios are also discussed to facilitate the industrialization and commercialization of edge AI systems.

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications

A modified belief-propagation algorithm is proposed for decoding of irregular low-density parity-check codes. This algorithm effectively reduces the decoding complexity while achieving a BER performance near to or even better than that of the standard belief-propagation algorithm.

Jianhua Lu

Papers

M-PSK and M-QAM BER computation using signal-space concepts

Companding transform for reduction in peak-to-average power ratio of OFDM signals

Reduction of peak-to-average power ratio of OFDM signals with companding transform

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications

Modified belief-propagation algorithm for decoding of irregular low-density parity-check codes