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The Last decade saw significant growth in the digital terrestrial television (DTT) subscribers. The High peak-to-average power ratio (PAPR) of the transmitted signal is implied by the large fluctuations in its amplitude, which is a serious issue in the contemporary and next generation DTT broadcasting systems. These large fluctuations prevent feeding the high power amplifier (HPA) at an operating point near its non-linear (NL) saturation region, thereby lowering its power efficiency. For a better future, energy-efficient green communications is the need of hour. This paper focuses on digital predistortion (DPD), which is among the widely used techniques for HPA linearization in order to minimize the NL effects. DPD technique requires a feedback signal. This paper proposes a novel adding signal-based digital predistortion, where the output of the HPA is gradually linearized by adding a signal at the input in an iterative manner. By Taylor series approximation, the DPD problem can be posed as a convex one. We prove that a tighter upper bound exists for the convergence factor and instead of directly solving the convex problem, we pick a convergence factor value within its bounds that offers a good trade-off between convergence speed and residual error value. The simulation results show that the proposed technique can quickly linearize the HPA with good convergence. [ABSTRACT FROM AUTHOR]

With the ratification of the IEEE 802.11ad amendment to the 802.11 standard in December 2012, a major step has been taken to bring consumer wireless communication to the millimeter wave band. However, multi-gigabit-per-second throughput and small interference footprint come at the price of adverse signal propagation characteristics, and require a fundamental rethinking of Wi-Fi communication principles. This article describes the design assumptions taken into consideration for the IEEE 802.11ad standard and the novel techniques defined to overcome the challenges of mm-Wave communication. In particular, we study the transition from omnidirectional to highly directional communication and its impact on the design of IEEE 802.11ad. [ABSTRACT FROM PUBLISHER]

To detect moving weak targets in the dual function radar communication (DFRC) system of an orthogonal frequency division multiplexing (OFDM) waveform, a modified hybrid integration method is addressed in this paper. A high-speed aircraft can cause range walk (RW) and Doppler walk (DW), rendering traditional detection methods ineffective. To overcome RW and DW, this paper proposes an integration approach combining DFRC and OFDM. The proposed approach consists of two primary components: intra-frame coherent integration and hybrid multi-inter-frame integration. After the echo signal is re-fragmented into multiple subfragments, the first step involves integrating energy across fixed situations within intra-frames for each subcarrier. Subsequently, coherent integration is performed across the subfragments, followed by the application of a Radon transform (RT) to generate frames based on the properties derived from the coherent integration output. This paper provides detailed expressions and analyses for various performance metrics of our proposed method, including the communication bit error ratio (BER), responses of coherent and non-coherent outputs, and probability of detection. Simulation results demonstrate the effectiveness of our strategy. [ABSTRACT FROM AUTHOR]

This paper presents the algorithmic framework for a multimodal hearing aid (HA) prototype designed on a Field Programmable Gate Array (FPGA), specifically the RFSOC4*2 AMD FPGA, and evaluates the transmitter performance through simulation studies. The proposed architecture integrates audio and video inputs, processes them using advanced algorithms, and employs the 5G New Radio (NR) communication protocol for uploading the processed signal to the cloud. The core transmission utilizes Orthogonal Frequency Division Multiplexing (OFDM), an algorithm that effectively multiplexes the processed signals onto various orthogonal frequencies, enhancing bandwidth efficiency and reducing interference. The design is divided into different modules such as Sound reference signal (SRS), demodulation reference signal (DMRS), physical broadcast channel (PBCH), and physical uplink shared channel (PUSCH). The modulation algorithm has been optimized for FPGA parallel processing capabilities, making it better suited for the hearing aid requirements for low latency. The optimized algorithm achieves a transmission time of only 4.789 ms and uses fewer hardware resources, enhancing performance in a cost-effective and energy-efficient manner. [ABSTRACT FROM AUTHOR]

As the Internet of Things (IoT) continues to expand, wireless communication is increasingly widespread across diverse industries and remote devices. This includes domains such as Operational Technology in the Smart Grid. Notably, there is a surge in resource-constrained devices leveraging wireless communication, especially with the advances of 5G/6G technology. Nevertheless, the transmission of wireless communications demands substantial power and computational resources, presenting a significant challenge to these devices and their operations. In this work, we propose the use of deep learning to improve the Bit Error Rate (BER) performance of Orthogonal Frequency Division Multiplexing (OFDM) wireless receivers. By improving the BER performance of these receivers, devices can transmit with less power, thereby improving IoT devices' battery life. The architecture presented in this paper utilizes a depthwise Convolutional Neural Network (CNN) for channel estimation and demodulation, whereas a Graph Neural Network (GNN) is utilized for Low-Density Parity Check (LDPC) decoding, tested against a proposed (1998, 1512) LDPC code. Our results show higher performance than traditional receivers in both isolated tests for the CNN and GNN, and a combined end-to-end test with lower computational complexity than other proposed deep learning models. For BER improvement, our proposed approach showed a 1 dB improvement for eliminating BER in QPSK models. Additionally, it improved 16-QAM Rician BER by five decades, 16-QAM LOS model BER by four decades, 64-QAM Rician BER by 2.5 decades, and 64-QAM LOS model BER by three decades. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of side lobe interference in 5G networks by proposing a unique collaborative beamforming strategy based on Deep Q-Network (DQN) reinforcement learning. Our method, which operates in the sub-6 GHz band, maximizes beam steering and power management by using a two-antenna system with DQN-controlled phase shifters. We provide an OFDM cellular network environment where inter-cell interference is managed while many base stations serve randomly dispersed customers. In order to reduce interference strength and improve signal-to-interference-plus-noise ratio (SINR), the DQN agent learns to modify the interference angle. Our model integrates experience replay memory with a long short-term memory (LSTM) recurrent neural network for time series prediction to enhance learning stability. The outcomes of our simulations show that our suggested DQN approach works noticeably better than current DQN and Q-learning methods. In particular, our technique reaches a maximum of 29.18 dB and a minimum of 5.15 dB, whereas the other approaches only manage 0.77–27.04 dB. Additionally, we significantly decreased the average interference level to 5.42 dB compared to competing approaches of 38.84 dB and 34.12 dB. The average sum-rate capacity is also increased to 3.90 by the suggested strategy, outperforming previous approaches. These findings demonstrate how well our cooperative beamforming method reduces interference and improves overall network performance in 5G systems. [ABSTRACT FROM AUTHOR]

In the current context of global communications, HF (High Frequency) NVIS (Near Vertical Incidence Skywave) data networks can be of strategic importance, providing short- and medium-range communication capabilities independent of terrestrial configuration and existing conventional communications infrastructure. They are essential in critical conditions, such as natural disasters or conflicts, when terrestrial networks are unavailable. This paper investigates the development of such systems for HF NVIS data communications by introducing a customized Orthogonal Frequency Division Multiplexing (OFDM) protocol with parameters adapted to HF ionospheric propagation, implemented on Software-Defined Radio (SDR) systems, which provide extensive configurability and high adaptability to varying HF channel conditions. This work presents an innovative approach to the application of OFDM narrow-channel aggregation in the HF spectrum, a technique that significantly enhances system performance. The aggregation enables a more efficient utilization of the available spectrum and an increase in the data transmission rate, which represents a substantial advancement in NVIS communications. The implementation was realized using an SDR system, which allows flexible integration of the new OFDM protocol and dynamic adaptation of resources. The work also includes the development of a messaging application capable of using this enhanced HF communication system, taking advantage of the new features of channel aggregation and SDR flexibility. This application demonstrates the applicability of the protocol in real-world scenarios and provides a robust platform for data transmission under conditions of limited access to other means of communication. Thus, this study contributes to the technological advancement of NVIS communications and opens new research and deployment directions in HF communications. [ABSTRACT FROM AUTHOR]

Abstract - In this Paper We want to talk about the Current or Future Generations of Network and Successor of 4g networks - 5th Generation Network, 5g is a new era of technology comes with new technologies like OFDM(Orthogonal Frequency division Multiplexing), Radio Wave Technologies, BDMA(Beam Division Multiple Access) etc are some technologies of 5th Generation Networks, also about situation of 5g in India. In this paper We will discuss these points 1. What is 5g 2. Why we need 5g 3. What 5g delivers us 4. Technologies in 5g 5. Future of 5g in India and world 6. Satellite Technology 7. 5g open source architecture 8. 5g open core network and its functionality. [ABSTRACT FROM AUTHOR]

The peak-to-average power ratio (PAPR), commonly used to describe the amplitude variations of an OFDM (orthogonal frequency-division multiplex) signal, does not accurately reflect its impact on the system performance. This paper applies the mutual information as a metric to assess the effects of nonlinear PAPR reduction schemes on the performance of OFDM systems. Evaluation of the achieved mutual information shows that a significant capacity loss from clipping occurs only at high SNR (signal-to-noise ratio) and a simple compression/expansion technique is proposed to achieve close to optimal performance in this regime. The effectiveness of this method is validated through WER (word error rate) simulations with several modulation and coding schemes. [ABSTRACT FROM AUTHOR]

The increasing volume of air traffic has placed significant stress on the current Air Traffic Management (ATM) systems, especially concerning the use of Very High Frequency (VHF) communication bands. As air traffic continues to grow, the limitations of the existing spectrum and infrastructure necessitate significant upgrades to ensure safety, efficiency, and capacity. The modernization of air traffic management systems has led to the development and introduction of the L-band Digital Aeronautical Communication System (LDACS), a new communication protocol. LDACS is designed to operate alongside existing L-band systems, ensuring compatibility with legacy users. The coexistence of LDACS with legacy systems poses significant interference challenges, as any disruption in data retrieval can critically impact flight safety. This paper proposes four potential interference mitigation techniques that LDACS can employ to detect and reduce the primary source of interference: Distance Measuring Equipment (DME). The authors introduce a prototype LDACS receiver that uses Rank-Ordered Absolute Differences (ROAD) statistics for effective interference sensing and employs GAE-enhanced pulse peak processors to mitigate Distance Measuring Equipment (DME) interference. Unlike the current GAE-enhanced pulse peak processors, the proposed methods use ROAD value-based detection for identifying DME interference. The performance of the proposed methods - ROAD GAE enhanced Pulse Peak Attenuator (RGPPA), ROAD GAE enhanced Pulse Peak Limiter (RGPPL), ROAD joint GAE enhanced Pulse Peak Attenuator (RJGPPA), and ROAD joint GAE enhanced Pulse Peak Limiter (RJGPPL) is analyzed across different threshold ROAD values to determine their efficacy in various signal conditions. Moreover, the performance of the proposed methods is compared to existing methods such as conventional pulse blanking and GAE-enhanced nonlinear devices, which use the amplitude of the received signal for the detection of interference. Furthermore, the proposed method’s performance is compared to another method, ROAD PB, which uses ROAD statistics to detect DME interference and pulse blanking for DME mitigation. The comparative results show that the proposed methods outperformed conventional pulse blanking and ROADPB. Besides, these methods outperformed existing GAE-enhanced methods for their optimum threshold ROAD value. [ABSTRACT FROM AUTHOR]

This paper presents Z-OFDM, a high-performance solution for underwater acoustic communication. Traditional underwater orthogonal frequency division multiplexing (OFDM) systems suffer from spectrum leakage and distortion due to the narrowband nature of underwater acoustic signals and the picket fence effect of the fast Fourier transform (FFT). Z-OFDM addresses these issues by integrating zoom-fast Fourier transform (ZoomFFT) with OFDM and redesigning the modulator and demodulator to replace the conventional FFT. This integration enhances spectral resolution, resulting in higher channel capacity, improved Signal to Interference plus Noise Ratio (SINR), and reduced Bit Error Rate (BER). Computer simulations using underwater acoustic channels from Fuxian Lake and Wuyuan Bay demonstrate that the Z-OFDM system achieves a 6 dB gain compared to conventional OFDM systems at a BER of 10 − 3 . These results demonstrate the effectiveness of Z-OFDM in overcoming the limitations of traditional FFT-based OFDM systems in underwater environments. [ABSTRACT FROM AUTHOR]

A novel approach is here presented to superimpose a low-priority data stream on a high-priority data stream for OFDM systems. The main improvement with respect to conventional hierarchical modulation, which is included with the same purpose in various wireless technologies, is that the low-priority data stream can be decoded from the received subcarrier symbols without any previous equalization for multipath fading channels. As a consequence, the expected performance is nearly invariant of the channel estimation method used to equalize the channel. The low-priority stream is inserted adopting a gain-invariant dirty paper coding based on Rational Dither Modulation, which was proposed for data hiding applications. In this paper an analysis of the developed system is presented and several simulations have been carried out using DVB-T system parameters to verify the validity of the proposed approach. The experimental results show the better performance of the proposed method with respect to that of a conventional hierarchical modulation, particularly when the accuracy of the estimated channel response decreases. [ABSTRACT FROM PUBLISHER]

The universal filtered multicarrier (UFMC) modulation is among the most considered solutions for the realization of beyond orthogonal frequency division multiplexing (OFDM) air interfaces for future wireless networks. This paper focuses on the design and analysis of a UFMC transceiver equipped with multiple antennas and operating at millimeter-wave carrier frequencies. This paper provides the full mathematical model of an MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission and for the case of multiple-packet continuous transmission. In the latter situation, this paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, several considered detection structures and transmission schemes are compared in terms of bit-error rate, root-mean-square error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear minimum mean-square error (MMSE) data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10%–13%. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance. [ABSTRACT FROM AUTHOR]

This paper derives the maximum achievable sum-rate and presents the optimal encoding/decoding framework for rate-diverse wireless network coding (RD-WNC) over broadband channels consisting of multiple parallel subchannels. RD-WNC applies to a communication scenario in which a base station wants to deliver two different messages with different rates to two users. The base station combines the two separate messages into one network-coded message and broadcasts the network-coded message to both users. Each user then extracts its desired message from the network-coded message by subtracting from it the other message, which we assume to be side information available to the user. Deriving the maximum achievable sum-rate for RD-WNC is challenging when the channel consists of multiple parallel subchannels with different channel coefficients (e.g., the subcarrier channels of OFDM systems), since apart from the rate allocation between the two users, optimal power allocation among multiple subchannels needs to be identified. The first contribution of this paper is a new “mountain-leveling” power allocation algorithm to achieve the maximum sum-rate. With the resulting power allocation, we can then achieve the corresponding optimal sum-rate by having a separate encoding/decoding mechanism for each subchannels, but doing so is cumbersome and complex when the number of subchannels is large. The second contribution of this paper is a practical encoding/decoding framework using only one encoder-decoder mechanism for all subchannels without sacrificing sum-rate optimality. We provide numerical results to corroborate our theoretical findings and to demonstrate the benefits of our encoding/decoding framework. [ABSTRACT FROM AUTHOR]

Recently, multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems have gained significant attention in the field of wireless communications. The utilization of the Riemannian manifold has become prevalent in MIMO-OFDM systems. However, the existing data detection algorithms for MIMO-OFDM systems are mostly designed for block fading channels. Additionally, these algorithms often suffer from high computational complexity. In this paper, we propose a data detection algorithm on the basis of Riemannian manifold optimization for MIMO-OFDM systems under time-varying channels. The core concept of this algorithm is to optimize the transmitted signals by solving the manifold optimization problem in the case of time-varying channels. In order to reduce the computational complexity of the algorithm, we improve the proposed algorithm by dividing the transmitted signals into multiple subframes for solving the optimization problem separately and using the pilots to maintain the performance of the algorithm. In the simulation, the performance of multiple proposed algorithms and the forced-zero detection algorithm under different parameter settings are compared. The simulation results show that the proposed algorithm demonstrates good bit error rate and computational complexity performances. [ABSTRACT FROM AUTHOR]

In this paper, a 4 amplitude shift keying (4-ASK) fast orthogonal frequency division multiplexing (FOFDM) scheme was experimentally investigated over a turbulent air–water channel for optical wireless communications. The experiment results showed that the 4-ASK-FOFDM modulated signals were not sensitive to weak atmospheric turbulence, and the bit-error rate (BER) was lower than the 7% forward error correction (FEC) limit of 3.8 × 10−3. Under the condition of the same spectra efficiency, the 4-ASK-FOFDM scheme just had a tiny performance penalty compared to the 16-QAM-OFDM scheme. Consequently, the 4-ASK-FOFDM scheme is a promising alternative to the conventional 16-QAM-OFDM scheme in optical wireless communications. [ABSTRACT FROM AUTHOR]

The relentless evolution of communication systems, driven by the demands of 5G and the impending 6G networks, necessitates heightened data rates and spectral efficiency. orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation employed in multi-input multioutput (MIMO) systems, stands as a pivotal technology. Yet, OFDM grapples with challenges, notably the peak-to-average power ratio (PAPR) issue. Selective mapping (SLM) has been a favored technique for mitigating PAPR in OFDM, albeit challenged by computational complexities in its pursuit of discovering optimal phase factors. This paper pioneers a transformative approach by integrating metaheuristic algorithms genetic algorithm (GA), particle swarm optimization (PSO), and the innovative fireworks algorithm (FWA) into SLM for PAPR reduction while minimizing computational complexity. Simulation results not only affirm the efficacy of SLM-based techniques but also spotlight the potential of metaheuristic algorithms in addressing PAPR challenges in modern communication systems. The study transcends single-antenna systems, extending to MIMOOFDM systems based on WiMAX standards, validating the efficacy of these techniques in multi-antenna configurations. Crucially, the FWA, proposed for the first time in this paper, emerges as a robust candidate, striking an enviable balance between computational efficiency and performance, achieving a notable PAPR reduction with a favorable search number. [ABSTRACT FROM AUTHOR]

This paper presents the research and implementation of a China Digital Radio (CDR) experimental network in Hubei, China with two FM-CDR transmitting stations and four FM-band channels. To study the coverage discontinuity problem in a large service area, the experimental network employs an intelligent networking solution that incorporates multiple service channels carrying Broadcast and Data Services (BADS) and a Common-Regional-Information Channel (CRIC) carrying both service data and system information. The electronic service guide (ESG) carried by CRIC can inform the receivers about the available contents from current and adjacent stations, which can significantly improve the service quality in the overlapping areas, especially under mobile reception environment. Two RF tuners are used in the receiving terminals to access the CRIC, and the BADS channel, respectively. This paper first presents the frequency analysis and coverage tests of the experimental network, and then summarizes the coverage performances with different transmission parameter combinations. The goal is to gain experience in frequency planning, coverage prediction, as well as supportable services of CDR digital audio broadcasting. [ABSTRACT FROM AUTHOR]

In wireless communication systems, reliability, low latency and power are essential in large scale multi-hop environment. Multi-hop based cooperative communication is an efficient way to achieve goals of wireless networks. This paper proposes a relay selection scheme for reliable transmission by selecting an optimal relay. The proposed scheme uses a signal-to-noise ratio (SNR) based Q-learning relay selection scheme to select an optimal relay in multi-hop transmission. Q-learning consists of an agent, environment, state, action and reward. When the learning is converged, the agent learns the optimal policy which is a rule of the actions that maximize the reward. In other words, the base station (BS) knows the optimal relay to select and transmit the signal. At this time, the cooperative communication scheme used in this paper is a decode-and-forward (DF) scheme in orthogonal frequency division multiplexing (OFDM) system. The Q-learning in the proposed scheme defines an environment to maximize a reward which is defined as SNR. After the learning process, the proposed scheme finds an optimal policy. Furthermore, this paper defines a reward which is based on the SNR. The simulation results show that the proposed scheme has the same bit error rate (BER) performance as the conventional relay selection scheme. However, this paper proposes an advantage of selecting fewer relays than conventional scheme when the target BER is satisfied. This can reduce the latency and the waste of resources. Therefore, the performance of the multi-hop transmission in wireless networks is enhanced. [ABSTRACT FROM AUTHOR]

In this paper, the scheme that combines LDM (Layered Division Multiplexing) with the FDM (Frequency Division Multiplexing) scheme based on BST-OFDM (Band Segmented Transmission - Orthogonal Frequency Division Multiplexing) is proposed for the next-generation DTTB (Digital Terrestrial Television Broadcasting). The proposed LDM-BST-OFDM scheme provides a more effective frequency utilization of the stream for fixed reception. The performance of the proposed scheme is evaluated by computer simulations where the effectiveness of proposed scheme for fixed reception is shown. Although LDM-BST-OFDM improves the performance, dedicated receivers that can demodulate symbols multiplexed by LDM are required. In this paper, LDM-BST-OFDM using punctured LDPC code is proposed, which can decode the stream for fixed reception even if symbols multiplexed by LDM are not demodulated. The reception characteristics of the proposed scheme are evaluated by computer simulations. [ABSTRACT FROM AUTHOR]

In this generation of high-speed internet many research organizations are still busy finding the best candidate for the upcoming next generation of cellular mobile communication. These days mobile communication is divided into two parts, one is calling service and second is internet connectivity. Though many waveforms have been suggested for the fifth generation of mobile communication but out of which getting a compared output results on the basis of channel estimation is required. Through this research paper, FBMC Aux, FBMC, and OFDM are compared in terms of BER and PAPR to find our best candidate for future 5th generation mobile and data communication. A comparison of the time index is also done to verify the merits and demerits of the FBMC and FBMC Aux in this paper. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) chirp waveforms are an attractive candidate to be a dual-function signal scheme for the joint radar and communication systems. OFDM chirp signals can not only be employed to transmit communication data through classic phase modulation, but also can perform radar detection by applying linear frequency modulation for subcarriers. However, the performance of the OFDM chirp communication system under the phase noise environment still remains uninvestigated. This paper tries to discuss the influence of phase noise on OFDM chirp communication systems and proposes effective phase noise estimation and compensation methods. We find that the phase noise effect on OFDM chirp communication systems consists of a common phase error (CPE) and an inter-carrier interference (ICI). If not compensated, the performance of the dual-function systems can be seriously degraded. In particular, an exact expression for the signal-plus-interference to noise ratio (SINR) for the OFDM chirp communication system is derived and some critical parameters are analyzed to exhibit the phase noise effects on system performance. Moreover, two low-complexity estimation approaches, maximum likelihood (ML) and linear minimum mean square error (LMMSE), as well as two compensation approaches, the de-correlation and cancellation algorithms, are respectively utilized to eliminate the phase noise impairment. Finally, the phase noise effects and the effectiveness of the compensation approach are verified by extensive numerical results. [ABSTRACT FROM AUTHOR]

A physical model of a wireless transmission channel in the time domain usually consists of the main propagation path and only a few reflections. The reasonable assumptions made about the channel model can improve its parameters' estimation by a greedy OFDM (Orthogonal Frequency Division Multiplexing) equalizer. The equalizer works flawlessly if delays between propagation paths are in the sampling grid. Otherwise, the channel impulse response loses its compressible characteristic and the number of coefficients to find increases. It is possible to get back to the simple channel model by data oversampling. The paper describes how the above idea helps the OMP (Orthogonal Matching Pursuit) algorithm estimate channel coefficients. The authors analyze the oversampling algorithm on the one hand to assess the influence of filtering function and signal resolution on the quality of the channel impulse response reconstruction. On the other hand, the abilities of the OMP algorithm are analyzed to distinguish components of the oversampled signal. Based on these analyses, we proposed modifications to the compressible channel's impulse response reconstruction algorithm to minimize the number of transmission errors. A distinction was made between the filters used in the OMP search and channel reconstruction stages before calculating equalizer coefficients. Additionally, the results of the search stage were considered as elements within the groups. [ABSTRACT FROM AUTHOR]

In UnderWater-Acoustic-Orthogonal-Frequency-Division-Multiplexing-(UWA-OFDM) communication, the traditional interpolated channel estimation method produces error codes, due to the small number of user pilots, uneven distribution, and complex channel characteristics. In this paper, we propose a novel UWA-channel-estimation method based on Deep Learning (DL). First, based on a small number of channel samples, we used the CWGAN-GP model to generate enhanced classified underwater-acoustic channel samples to have semantic similarity to the real samples and also to present the diversity of the samples. After obtaining the channel sample, the pilot estimation matrix was processed in a similar image way. Here, we extracted the channel features by constructing a convolutional network structure similar to U-Net, weakening the impact of feature information loss. A Channel-Attention-Denoising-(CAD) module was also designed, to further optimize the reconstructed channel information. The simulation results verified the superiority of the proposed algorithm, in terms of Mean Square Error (MSE) and Bit-Error Rate (BER) compared to the existing Least-Squares-(LS), Deep-Neural-Network-(DNN), and ChannelNet algorithms. [ABSTRACT FROM AUTHOR]

Zero correlation zone (ZCZ) sequence sets and Golay complementary sets (GCSs) have different correlation properties and hence have different engineering applications. A number of constructions of ZCZ sequence sets and GCSs have been proposed, respectively, in the literature. In addition, some ZCZ sequence sets can be constructed from mutually orthogonal GCSs. In this paper, the relationship between GCSs and ZCZ sets is discovered further. We propose a new type of sequence sets which are ZCZ sequence sets and also GCSs. They are called the Golay-ZCZ sequence sets in this paper. Therefore, they have low peak-to-average power ratios when employed in OFDM systems due to the good autocorrelation properties of GCSs. Besides, the Golay-ZCZ sets possess zero autocorrelations and cross-correlations within their ZCZ and hence have the potential application to synchronization. Furthermore, a construction of Golay-ZCZ sequence family with flexible set sizes, various sequence lengths, and large ZCZ widths is proposed in this paper. [ABSTRACT FROM AUTHOR]

In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits. [ABSTRACT FROM AUTHOR]

It has been recently shown that zero padding (ZP)-orthogonal frequency-division multiplexing (OFDM) is a promising candidate for 6G wireless systems requiring joint communication and sensing. In this paper, we consider a multiuser uplink scenario where users are separated in power domain, i.e., non-orthogonal multiple access (NOMA), and use ZP-OFDM signals. The uplink transmission is grant-free and users are allowed to transmit asynchronously. In this setup, we address the problem of time synchronization by estimating the timing offset (TO) of all the users. We propose two non-data-aided (NDA) estimators, i.e., the joint method of moment (JMoM) and the successive moment cancellation (SMC), that employ the periodicity of the second order moment (SoM) of the received samples for TO estimation. Moreover, the coding assisted (CA) version of the proposed estimators, i.e., CA-JMoM and CA-SMC, are developed for the case of short observation samples. We also extend the proposed estimators to multiuser multiple-input multiple-output (MIMO) systems. The effectiveness of the proposed estimators is evaluated in terms of lock-in probability under various practical scenarios. Simulation results show that the JMoM estimator can reach the lock-in probability of one for the moderate range of E b / N 0 values. While existing NDA TO estimators in the literature either offer low lock-in probability, high computational complexity that prevents them from being employed in MIMO systems, or are designed for single-user scenarios, the proposed estimators in this paper address all of these issues. [ABSTRACT FROM AUTHOR]

The most widely used Wi-Fi wireless communication system, which is based on OFDM, is currently developing quickly. The receiver must, however, accurately estimate the carrier frequency offset between the transmitter and the receiver due to the characteristics of the OFDM system that make it sensitive to carrier frequency offset. The autocorrelation of training symbols is typically used by the conventional algorithm to estimate the carrier frequency offset. Although this method is simple to use and low in complexity, it has poor estimation performance at low signal-to-noise ratios, which has a significant negative impact on the performance of the wireless communication system. Meanwhile, the design of the communication physical layer using deep-learning-based (DL-based) methods is receiving more and more attention but is rarely used in carrier frequency offset estimation. In this paper, we propose a DL-based carrier frequency offset (CFO) model architecture for 802.11n standard OFDM systems. With regard to multipath channel models with varied degrees of multipath fadding, the estimation error of the proposed model is 70.54% lower on average than that of the conventional method under 802.11n standard channel models, and the DL-based method can outperform the estimation range of conventional methods. Besides, the model trained in one channel environment and tested in another was cross-evaluated to determine which models could be used for deployment in the real world. The cross-evaluation demonstrates that the DL-based model can perform well over a large class of channels without extra training when trained under the worst-case (most severe) multipath channel model. [ABSTRACT FROM AUTHOR]

Previous correlation-based wideband multiple-input–multiple-output (MIMO) channel models have been limited to non-line-of-sight (NLoS) scenarios where simple antenna correlation measurements are sufficient to describe the correlated Gaussian process representing the fading statistics. However, in the presence of line-of-sight (LoS) or specular reflections, simple antenna correlation measurements unfortunately do not lead to accurate fading characterizations. In this paper, we propose a trend-stationary correlation-based analytical model for wideband LoS and NLoS MIMO channels and design and validate a wideband multitone MIMO channel sounder and estimator to, respectively, measure channel impulse responses (CIRs) and estimate channel parameters for this model. Joint maximum-likelihood (ML) estimation of the LoS component and the NLoS complex correlation matrix is presented. In addition to enabling the estimation of the path correlation matrix of a wireless channel in the presence of LoS components, the modeling approach also provides tools to evaluate the validity of the assumption of uncorrelated scattering (US), even in LoS environments, which is commonly used in channel modeling. A more general model that does not assume US is also presented, which can likewise be estimated using the proposed estimator. To validate the channel sounding/model estimator techniques, we employ channel sounding waveforms and collect snapshots from the outputs of a state-of-the-art hardware MIMO channel emulator capable of emulating multipath channels under the US assumption. Receiver signal processing and channel parameter estimation are performed on the collected data, and the results are compared with the emulated channel parameters. The work is unique in that it provides a correlation-based multipath MIMO channel modeling approach that addresses LoS environments, it describes corresponding estimation techniques to extract the full complex correlation matrix, and the model estimators are backed using channel sounding with emulation-based validation. [ABSTRACT FROM PUBLISHER]

In underwater acoustic (UWA) adaptive communication system, due to time-varying channel, the transmitter often has outdated channel state information (CSI), which results in low efficiency. UWA channels are much more difficult to estimate and predict than terrestrial wireless channels, given the more severe multipath environments with varying propagation speeds in different locations, non-linear propagation paths, several-order higher propagation latency, mobile transceiver and obstacles in the sea, etc. To handle the complexity, this paper proposes an efficient online CSI prediction model for UWA CSI prediction considering the complicated correlationship of UWA channels in both the time and frequency domains. This paper designs a learning model called CsiPreNet, which is an integration of a one-dimensional convolutional neural network (CNN) and a long short term memory (LSTM) network. The performance is compared with the widely used recursive least squares (RLS) predictor, the approximate linear dependency recursive kernel least-squares (ALD-KRLS), and two common conventional deep neural networks (DNN) predictors, i.e., back propagation neural network (BPNN) and LSTM network using the measured data recorded in the South China Sea. To validate the efficacy of prediction, we investigate the prediction of CSI in simulated downlink UWA orthogonal frequency division multiple access (OFDMA) systems. Specifically, the measured UWA channel is used in the OFDMA system. A joint subcarrier-bit-power adaptive allocation scheme is used for resource allocation. To further improve the performance, we develop an offline-online prediction scheme, enabling the prediction results to be more stable. Simulation and experimental results show that the CsiPreNet has superior performance than the existing solutions, thanks to its capability in capturing both the temporal and frequency correlation of the UWA CSIs. [ABSTRACT FROM AUTHOR]

This paper presents a phase correction method to improve direction-of-arrival (DOA) estimation in spectrally interleaved orthogonal frequency-division multiplexing (OFDM) multiple-input-multiple-output (MIMO) radar systems. It is new in the way that a phase correction step is introduced between the range-Doppler processing and the DOA estimation. The phase correction results in an improved dynamic range. Both processing steps, range–velocity and DOA, are performed using discrete Fourier transforms (DFTs). This paper starts by introducing the waveform and reviewing range–velocity processing in OFDM radars. After that, the new phase correction method is introduced. Then, the concept is implemented in a quantitative simulation. The last part includes the system description and measurement in an outdoor scenario. Finally, the simulation and measurement results are discussed. [ABSTRACT FROM AUTHOR]

Resource allocation in mmWave small cell is a key issue of the fifth generation (5G) systems. To solve this problem, we first present a hybrid beamforming structure for base station of small cell, which consists of orthogonal frequency division multiplexing (OFDM), identity matrix and switched-beam. Next, we formulate the joint allocation of the beam and transmitted power on the sub-carriers into a mixed integer non-linear programming problem (MINLP). Due to the non-convexity of this problem, we decompose it into two subproblems which are the beam selection and the power allocation. For the beam selection, we propose an algorithm based on cooperative games. For the power allocation, we present an optimal and sub-optimal solution based on Lagrange duality and non-cooperative games respectively. Simulation results show that the beam allocation algorithm proposed in this paper can effectively improve the sum rate of the system, and the optimal power allocation solution is far superior to the sub-optimal one in sum rate. [ABSTRACT FROM AUTHOR]

Orthogonal frequency division multiplexing (OFDM) is a candidate modulation technique to achieve high-speed data transmission in visible light communication systems that provide both illumination and downlink data transmission. This paper proposes a method called polarity-header optical OFDM (PHO-OFDM) specially designed to account for the nonlinear response of the LED transmitters. To make the transmitted signal positive, as required for intensity modulation and direct detection systems, a signal header containing the sign information of the bipolar OFDM signal is transmitted followed by the amplitude of the signal. The binary sign information can be encoded and transmitted via a few samples using $M$ -ary pulse-amplitude modulation. The amplitude of the OFDM signal that is larger than the maximum LED power is sent in a subsequent frame to reduce the nonlinear distortion due to peak-power clipping. Furthermore, illumination requirements are taken into account, and their effects on the system performance are discussed. This paper also considers the overhead cost of adding a cyclic prefix to minimize intersymbol interference in dispersive channels. Compared with state-of-the-art optical OFDM techniques, the proposed PHO-OFDM achieves a better BER performance and higher data throughput, and provides a larger illumination flexibility. [ABSTRACT FROM AUTHOR]

Uplink transmission is an issue for visible light communications due to the unpleasant irradiance from the source light when placed close to the users. To overcome this problem, this paper proposes the use of relays to lower the required source optical power. A popular multi-carrier modulation scheme, termed direct-current biased optical orthogonal frequency division multiplexing, is employed to achieve high spectral efficiency. In addition, both amplitude-and-forward (AF) and decode-and-forward (DF) protocols are used. The theoretical models of AF and DF protocols are also obtained and verified by simulations. To minimize the source optical power while satisfying reliable communications, this paper formulates the associated optimization problems for AF and DF protocols. Exhaustive search is first used to obtain the optimal configuration for the system. As exhaustive search requires high computation efforts and can be time-consuming, two low-complexity suboptimal designs for AF and DF protocols are then proposed, and the proposed suboptimal designs can approximate the performance of exhaustive search in high signal-to-noise ratio regions. Numerical and experimental results indicate that when compared with the counterpart without a relay, the proposed relay-assisted system requires much lower source optical power under the constraints of reliable transmissions. [ABSTRACT FROM AUTHOR]

G-Cast is a wireless visual communication scheme that conveys visual information via image gradient. It is inspired by the characteristics of human vision systems and can provide improved perceptual quality. G-Cast is power efficient but bandwidth demanding, because gradient data have double the size of the original image. This paper presents a scheme named CG-Cast for scalable image transmission in bandwidth-limited wireless scenarios. It employs a compressive-gradient-based image representation to describe perceptually sensitive image details and reduce the bandwidth requirement at the same time, combining gradient-based visual representation with compressive sensing techniques. The compressive gradient data are transmitted in a pseudo-analog way so that it achieves elegant quality transition in a wide channel signal-to-noise ratio (CSNR) range. CG-Cast also sends a small set of low-frequency data in digital a way to provide the global and local luminance of the image. We developed an effective optimization algorithm for the decoder to reconstruct the original image from the received noisy compressive gradient and the low-frequency part of the image. Experimental results demonstrate that the proposed scheme improves the quality of received images remarkably under different CSNR and channel bandwidth conditions. [ABSTRACT FROM AUTHOR]

This paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization reduces greatly the complexity and power consumption but makes accurate channel estimation and data detection difficult. This is particularly true for multicarrier waveforms that have high peak-to-average power ratio in the time domain and fragile subcarrier orthogonality in the frequency domain. The severe distortion for one-bit quantization typically results in an error floor even at moderately low signal-to-noise-ratio (SNR) such as 5 dB. For channel estimation (using pilots), we design a novel generative supervised deep neural network that can be trained with a reasonable number of pilots. After channel estimation, a neural network-based receiver—specifically, an autoencoder—jointly learns a precoder and decoder for data symbol detection. Since quantization prevents end-to-end training, we propose a two-step sequential training policy for this model. With synthetic data, our deep learning-based channel estimation can outperform least squares channel estimation for unquantized (full-resolution) OFDM at average SNRs up to 14 dB. For data detection, our proposed design achieves lower bit error rate (BER) in fading than unquantized OFDM at average SNRs up to 10 dB. [ABSTRACT FROM AUTHOR]

This paper studies multi-user multi-cell visible light communications networks in which each cell is composed of multiple light emitting diode (LED) arrays. The use of multiple LED transmitters enables each cell to support multiple users by means of precoding techniques. In such multi-user multi-cell networks, the signal for each user can be severely interfered not only by the signals that are intended to other users in the same cell, i.e., intra-cell interference, but also by the signals for users of the other cells, i.e., inter-cell interference. While intra-cell interference can be handled by the underlying precoding scheme, it is hard to deal with the inter-cell one. This paper focuses on cell coordination/cooperation strategies and their corresponding coordinated/cooperative precoder designs as the approaches to alleviate, or possibly, to cancel out the inter-cell interference. We first derive lower and upper bounds on the capacity of Gaussian interference channels with amplitude constraints on the input and the interference. Capitalizing on derived bounds and the zero-forcing scheme as the underlying precoding technique, optimal coordinated/cooperative precoding designs to maximize users’ sum-rate are investigated under the non-negativity and amplitude-limited constraints on the channel inputs. The comprehensive numerical results are presented to compare the performance of the considered coordination/cooperation strategies. [ABSTRACT FROM AUTHOR]

In recent years, ambient backscatter communications have gained a lot of interests as a promising enabling technology for the Internet-of-Things and green communications. In ambient backscatter communication systems, ultra-low power devices are able to transmit information by backscattering ambient radio-frequency signals generated by legacy communication systems such as Wi-Fi and cellular networks. This paper is concerned with ambient backscatter communications over legacy orthogonal frequency division multiplexing (OFDM) signals. We propose a backscatter modulation scheme that allows backscattering devices to take advantage of the spectrum structure of ambient OFDM symbols to transmit information. The proposed modulation scheme allows both binary and higher-order modulation using noncoherent energy detection. We investigate the detector design and analyze the error performance of the proposed scheme. We provide an exact expression for the error probability for the binary case, whereas accurate approximate expressions for the error probability are derived for the $M$ -ary case. We corroborate our analysis using Monte–Carlo simulation and investigate the effects of varying the OFDM symbol size, maximum channel delay spread, and the number of receive antennas on the error performance. Our numerical results show that the proposed technique outperforms other techniques available in this paper for backscatter communication over ambient OFDM signals in different scenarios. [ABSTRACT FROM AUTHOR]

Various techniques have been proposed to address the problem of resource allocation in multi-carrier communications. These techniques, for the most part, arise from information-theoretic measures or otherwise associated with the channel behavior, which does not necessarily model the coding being employed. In this paper, an optimization technique is tailored for low density parity-check (LDPC) coded orthogonal frequency-division multiplexing (OFDM) systems, by employing the so-called general stability condition introduced by Richardson et al. The latter formulates a necessary condition for the belief-propagation decoder to perfectly decode a received vector with no errors. The general condition is re-formulated so as to model practical multi-carrier systems, such as OFDM. Consequently, a general resource-allocation framework is laid down for optimizing the transmitted power based on the characteristics of the LDPC code in use. The proposed optimization technique is utilized for power allocation in orthogonal frequency-division multiple access systems; and the transmitted power is minimized while guaranteeing reliable decoding. To validate the proposed approach, it is compared to information-theoretic-based methods that aim at optimizing the mutual information between the transmitter and the receiver. Both approaches are shown to provide almost identical performance for the scenarios addressed in this paper. [ABSTRACT FROM AUTHOR]

Downlink transmission into frequency-selective links experiencing different coherence bandwidths and coherence times has obvious practical relevance, but is often addressed via assuming for all users the coherence conditions corresponding to the fastest, most dispersive user. This paper demonstrates an alternative approach that directly exploits the differences between coherence bandwidth and coherence time of users under frequency-selective conditions, showing that it can lead to significant new efficiencies and gains. More specifically, we study a two-user downlink frequency-selective channel under three broad conditions of disparity between the link qualities: when the disparity is in coherence time, in coherence bandwidth, and in both coherence time and coherence bandwidth. Each of the coherence scenarios calls for a distinct treatment; for each, we provide an analysis demonstrating the gains in achievable rates due to exploiting coherence disparity. Numerical simulations demonstrate the advantages of the proposed schemes. [ABSTRACT FROM AUTHOR]

The availability of accurate channel state information (CSI) is essential in multiuser massive multiple-input multiple-output (MIMO) systems. However, most published works focus on frequency-flat channel estimation which requires that the estimation must be repeated for every frequency slot, e.g., subcarrier, in a broadband system. Since the channels in the frequency-domain are the Fourier transform of a small set of time-domain channel coefficients, the time-domain channel estimation requires that fewer parameters be estimated. In this paper, we propose a semi-blind, time-domain, channel estimation technique for frequency-selective massive MIMO systems. Our solution depends on the subspace spanned by the signal eigenvectors of the received signal covariance matrix. Importantly, since the receiver samples at the symbol rate, time-domain-based estimation inherently has available enough samples for an accurate matrix estimate. To avoid asymptotic assumptions, we express each channel vector as a linear combination of the signal eigenvectors. We estimate the linear combination using a set of training symbols. Given the many samples of the received signal in the time-domain, we obtain a better channel estimate compared to conventional subcarrier-wise frequency-domain channel estimation. Unlike the previous published results, in this paper, we do not assume orthogonality of users’ channels or knowledge of large-scale fading coefficients. In addition, our estimation procedure does not require orthogonality between the training symbols of the users in all cells. [ABSTRACT FROM AUTHOR]

In orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) systems, power optimization algorithms have been evaluated to maximize the achievable data rates of the secondary user (SU). However, unrealistic assumptions are made in the existing work, i.e., a Gaussian input distribution and traditional interference model that assumes a frequency-division multiplexing modulated primary user (PU) with perfect synchronization between the PU and the SU. In this paper, we first derive a practical interference model by assuming OFDM modulated PU with imperfect synchronization. Based on the new interference model, the power optimization problem is proposed for the finite symbol alphabet (FSA) input distribution [i.e., $M$-ary quadrature amplitude modulation (M-QAM)] , as used in practical systems. The proposed scheme is shown to save transmit power and to achieve higher data rates compared with the Gaussian optimized power allocation and the uniform power loading schemes. Furthermore, a theoretical framework is established in this paper to estimate the power saving by evaluating optimal power allocation for the Gaussian and the FSA input. Our theoretical analysis is verified by simulations and is proven to be accurate. It provides guidance for the system design and gives deeper insights into the choice of parameters affecting power saving and rate improvement. [ABSTRACT FROM PUBLISHER]

Orthogonal frequency-division multiplexing (OFDM), special form of multicarrier modulation, is the cornerstone of broad range of current standards. In addition, fifth-generation (5G) terrestrial wireless networks, advancing at accelerated speed, continue to use OFDM air interface. The first part of this paper endeavors to apply OFDM-like signaling for broadband satellite transmission in the forward direction, from gateway to terminals. Two layers of multicarrier operation are invoked. One allows multiple signals to share single on-board high-power amplifier. The other layer permits transmitted symbols from individual signals to modulate multiple narrowband OFDM subcarriers, followed by interpolating filters to suppress interference into adjacent signals and limit out-of-band emission to be compatible with satellite uplink. The second part of this paper proposes novel nonlinear compensation techniques, applied at the transmitter or receiver, and combination of both. Two performance assessments are provided: one exploiting information-theoretic framework using ideal channel coding; another based on total degradation using practical forward-error correction codes. We show that performance loss from nonlinear distortion can be significantly reduced when adopting the proposed correction methods. Furthermore, it is possible to use OFDM-like signaling over satellite, while being competitive, and in some cases surpassing, traditional systems with single-carrier modulation employing state-of-the-art enhanced receiver architecture. [ABSTRACT FROM AUTHOR]

This paper considers the problem of analytically assessing the maximum achievable rates (capacity) of orthogonal frequency division multiplexing (OFDM) transmissions when the receiver, for complexity reasons, only accounts for the common phase error (CPE) effect due to phase noise impairments with inter-carrier interference (ICI) treated as noise. By recognizing that the functional form of the CPE with respect to the phase noise realization is actually a free design parameter, determination of the capacity is posed as a functional optimization problem with respect to the, so-called, CPE function. A simple lower bound of the capacity is obtained, revealing the performance degradation due to the unknown CPE at the receiver, as well as the suboptimal performance achieved in severe phase noise conditions by the conventional CPE function that is routinely employed in previous works. The existence of an optimal number of subcarriers that balances the effects of the (unknown) CPE and ICI is highlighted and critical system design/operation issues, such as selection of the CPE function and effect of unknown channel on the achievable rate, are discussed. The analysis in this paper can be employed for determining the suitability of OFDM in phase noise channels and provides a tractable utility function for resource allocation purposes. [ABSTRACT FROM PUBLISHER]

In this paper, a delay diversity orthogonal frequency-division multiplexing (DD OFDM) transmission scheme in amplify-and-forward (AF) full-duplex relay systems is investigated. One direct source-to-destination link, one relay forwarding link, and residual self-interference are considered in the system. The necessary cyclic prefix length is investigated and a suitable AF relay protocol in the full-duplex relay OFDM system is proposed. This paper demonstrates that the AF relay link and the direct source-to-destination link can be combined to provide spatial diversity. The key is that the DD OFDM scheme is used to transform the spatial diversity into increased channel frequency diversity that is further exploited by using the bit-interleaved coding. The bit error rate performance of the proposed system is verified by simulation results. [ABSTRACT FROM PUBLISHER]

This paper analyzes the fundamental trade-offs that occur in the co-design of pilot resource allocations in orthogonal frequency-division multiplexing signals for both ranging (via time-of-arrival estimation) and communications. These trade-offs are quantified through the Shannon capacity bound, probability of outage, and the Ziv–Zakai bound on range estimation variance. Bounds are derived for signals experiencing frequency-selective Rayleigh block fading, accounting for the impact of limited channel knowledge and multi-antenna reception. Uncompensated carrier frequency offset and phase errors are also factored into the capacity bounds. Analysis based on the derived bounds demonstrates how Pareto-optimal design choices can be made to optimize the communication throughput, probability of outage, and ranging variance. Different pilot resource allocation strategies are then analyzed, showing how Pareto-optimal design choices change depending on the channel. [ABSTRACT FROM AUTHOR]

In this paper, we propose a parametric OFDM transceiver for wireless communication encryption. One of the major contributions of this work is the intrinsic encryption nature of the proposed system, since it is a completely new idea and philosophically different from the concept of existing secured OFDM systems requiring separate encryption blocks. The main idea behind the proposed system is the appropriate use of the parametric discrete Fourier transform (DFT-alpha) and its inverse IDFT-alpha, where alpha is randomly obtained from [-2pi, 0], to implement the OFDM system and at the same time inherently encrypt the communications. Thus, the resulting (IDFT-alpha/DFT-alpha)-based OFDM transceiver, which has a performance similar to that of the conventional IDFT/DFT-based OFDM transceiver, is applied and implemented in the IEEE 802.11a WIFI system framework OFDM for communication encrypting. Moreover, using BER and SNR, we experimentally determine the appropriate intervals of the possible values of alpha for perfect encryption in a flat fading channel assumed for optimal testing environment. We also examine and assess the effects of DFTalpha on the transformation of the constellation pattern of the transmitted signal to prove the validity of the obtained intervals for different modulation schemes such as BPSK, QPSK, 16QAM, and 64QAM. [ABSTRACT FROM AUTHOR]