Frequency-selective Multipath Channels Research Articles

A Learning-Based End-to-End Wireless Communication System Utilizing a Deep Neural Network Channel Module

The existing end-to-end (E2E) wireless communication systems require fewer communication modules and have a simple processing signal flow, compared to conventional wireless communication systems. However, in the absence of a differentiable channel model, it is impossible to train transmitters, used in such systems, which makes impossible to get optimal system performance. To solve this problem, an E2E wireless communication system, learned with conditional generative adversarial networks (CGANs) for channel modeling, has been proposed recently. Unfortunately, the CGAN training is prone to instability, slow convergence, and inaccurate channel modeling, which affects the system performance. To this end, a learning-based E2E wireless communication system, utilizing a deep neural network (DNN) channel module to model an unknown channel, is proposed in this paper. Simulation results show that the proposed DNN channel modeling has faster convergence, simpler network structure, and can reflect the behavior of real channels more accurately. In addition, the proposed E2E wireless communication system performs better, in terms of bit error rate (BER) and block error rate (BLER), than the E2E wireless communication system, using CGAN as unknown channel, and a traditional communication system, designed based on the prior knowledge of the channel. Compared to these two systems, at high signal-to-noise ratio (SNR) values, the proposed system can achieve a SNR gain of at least 2 dB, in communication scenarios involving frequency-selective multi-path channels.

Simple and Efficient LoRa Receiver Scheme for Multipath Channel

This paper presents a novel LoRa (Long Range) receiver operating in frequency selective Multi-Path Channel (MPC). The dechirped received LoRa wave-forms under MPC allows us to derive a simple and efficient LoRa receiver scheme by using a MF (Matched Filter) approach that aims to maximize the SNR (Signal-to-Noise Ratio) at the symbol index frequency of the DFT output. We show that the MF receiver can be seen as RAKE structure where interference peaks related to multipath, exhibited at DFT output, are recombined in a constructive way. Detection performance is driven by channel energy and the benefit of this novel MF/RAKE receiver over original coherent and non-coherent receiver appears only for MPC that exhibits significant paths energy. These two MF and RAKE receivers have however different implementation complexities that are studied in details. We provide in that sense recommendations on which receiver variant to use for real operations, depending on complexity constraints. Finally, the proposed MF/RAKE receiver outperforms previous results on TDEL (Time Delay Estimation LoRa) receiver over MPC, especially at low SNR and higher LoRa Spreading Factor (SF) parameter, at the cost of higher but reasonable complexity.

Iterative Equalization of STSK-Aided Single-Carrier Systems: Design and Analysis With Non-Ideal Power Amplifiers

A plethora of new applications will be enabled by next generation wireless networks. These demand sophisticated medium access control and physical layer protocols in order to fulfill the requirements in terms of spectral efficiency, bit error rate (BER), energy efficiency, reliability, and security, among others. This paper develops an advanced space-time multiple-input, multiple-output (MIMO) solution that builds on the concept of space-time shift keying (STSK) for single-carrier frequency domain equalization (SC-FDE). STSK-aided SC-FDE, or SSF, ensures space-time and frequency diversity in dispersive channels, but can only support suboptimal linear receiver schemes. We therefore introduce a turbo equalizer for SSF in frequency-selective multipath channels. It enables inter-symbol-interference cancellation by means of iterative space-time processing. We coin it the iterative space-time block equalizer (SSF-ISTBE). We provide the mathematical formulation for the proposed SSF-ISTBE framework in non-linear channel conditions. We demonstrate that the SSF-ISTBE achieves a substantial 4 dB gain in terms of BER over the linear minimum mean square error equalizer while significantly reducing the computational complexity of the optimal maximum likelihood SSF. When considering practical transceivers, in particular non-linear power amplifiers, the gain of the SSF-ISTBE becomes more prominent over state-of-the-art approaches, demonstrating its robustness against non-linear distortion.

Blind Adaptive Equalization for Aerospace Communication Channels

In some communication systems, it is desirable for the receiver to synchronize to the received signal and to adjust the equalizer without having knowledge of a training sequence. Blind equalization uses the initial adjustment of the coefficients without making use of a training sequence. Different adaptive blind equalization algorithms have been developed over the past four decades. In this paper, we investigate the effect of blind equalization on space communication channels. The space channel under investigation is considered to be a multipath frequency selective channel having four paths. The channel is subjected to the phenomenon of InterSymbol Interference (ISI) which severely degrades the performance of the space communication system. Two blind algorithms are used in equalizer adjustment. The impulse responses of the space channel, the blind equalizer and the combination of channel and equalizer for QPSK and 16-QAM transmission are shown. The scatter diagrams for the transmitted sequence, received sequence, and the output of the equalizer using two of the blind algorithms are shown.

Refined Nonlinear Rectenna Modeling and Optimal Waveform Design for Multi-User Multi-Antenna Wireless Power Transfer

In this paper, we study the optimal waveform design for wireless power transfer (WPT) from a multi-antenna energy transmitter (ET) to multiple single-antenna energy receivers (ERs) simultaneously in multi-path frequency-selective channels. First, we propose a refined nonlinear current-voltage model of the diode in the ER rectifier, and accordingly derive new expressions for the output direct current (DC) voltage and corresponding harvested power at the ER. Leveraging this new rectenna model, we first consider the single-ER case and study the multisine-based power waveform design based on the wireless channel to maximize the harvested power at the ER. We propose two efficient algorithms for finding high-quality suboptimal solutions to this non-convex optimization problem. Next, we extend our formulated waveform design problem to the general multi-ER case for maximizing the weighted sum of the harvested powers by all ERs, and propose an efficient difference-of-convex-functions programming (DCP)-based algorithm for solving this problem. Finally, we demonstrate the superior performance of our proposed waveform designs based on the new rectenna model over existing schemes/models via simulations.

On the Ungerboeck and Forney Observation Models for Spatial Combining And Their Application to 5G Millimeter-Wave Bands

Equivalent discrete-time models for a variety of spatial combining techniques operating in a frequency-selective multipath fading channel are derived. The equivalent discrete-time models are used to perform computer simulations of the post-equalizer bit error rate over a frequency-selective multipath channel whose derivation preserved polarization state information. Two sets of computer simulations were performed. In the first set, the performance of co-located cross-polarized antenna elements was investigated. The results showed that maximum likelihood combining maximizes polarization diversity, but that maximum ratio combining and selection combining were very competitive in the case where the cross-polarized antennas produce one strong channel and a relatively weak channel. Elliptical combining, using a 90° hybrid coupler, produced the worst results. The second set of simulations used a combination of spatial and cross-polarized antenna elements, for a total of eight antenna elements. The simulation results showed that maximum likelihood combining was best, followed by maximum ratio combining, equal gain combining, and selection combining. Again, elliptical combining was the worst, leading to the conclusion that other combining techniques are preferred in frequency-selective fading environments.

A Distributed Pulse-Based Synchronization Protocol for Half-Duplex D2D Communications

In distributed device-to-device (D2D) communications, no common reference time is available and the devices must employ distributed synchronization techniques. In this context, pulse-based synchronization, which can be implemented by distributed phase-locked loops is preferred due to its scalability. Several factors degrade the performance of pulse-based synchronization, such as duplexing scheme, clock skew and propagation delays. Furthermore, in distributed networks, devices should be aware of the synchronization status of others in order to initiate data communications. To address these prevailing issues, we first introduce a half-duplex timing-advance synchronization algorithm wherein each device alternates between being a transmitter and receiver in their exchange of synchronization pulses at each clock period. Based on this algorithm, we propose a novel fully-distributed pulse-based synchronization protocol for half-duplex D2D communications in 5G wireless networks. The protocol allows participating devices to become aware of the global synchronization status, so that they can complete the synchronization process ideally at the same time and proceed to data communication. In simulation experiments over multi-path frequency selective channels, the proposed synchronization protocol is shown to outperform a benchmark approach from the recent literature over a wide range of conditions, e.g., clock skew, number of devices, and network topology.

Efficient Machine Learning-Enhanced Channel Estimation for OFDM Systems

Recently much research work has focused on employing deep learning (DL) algorithms to perform channel estimation in the upcoming 6G communication systems. However, these DL algorithms are usually computationally demanding and require a large number of training samples. Hence, this work investigates the feasibility of designing efficient machine learning (ML) algorithms that can effectively estimate and track time-varying, frequency-selective channels. The proposed algorithm is integrated with orthogonal frequency-division multiplexing (OFDM) to eliminate intersymbol interference (ISI) induced by the frequency-selective multipath channel and compared with the well-known least square (LS) and linear minimum mean square error (LMMSE) channel estimation algorithms. The obtained results have demonstrated that even when a small number of pilot samples, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{P}$ </tex-math></inline-formula> , is inserted before the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> subcarriers OFDM symbol, the introduced ML-based channel estimation is superior to the LS and LMMSE algorithms. This dominance is reflected in the bit-error-rate (BER) performance of the proposed algorithm, which attains a gain of 2.5 dB and 5.5 dB over the LMMSE and LS algorithms, respectively, when <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{P}=\frac {N}{8}$ </tex-math></inline-formula> . Furthermore, the BER performance of the proposed algorithm is shown to degrade by only 0.2 dB when the maximum Doppler frequency is randomly varied. Finally, the number of iterations required by the proposed algorithm to converge to the smallest achievable mean-squared error (MSE) are thoroughly examined for various signal-to-noise ratio (SNR) levels.

Evaluaciónde OPS para la Reducción de la PAPR en un SistemaOFDM conCanal Multitrayecto

OFDM (Orthogonal Frequency Division Multiplexing) es una tecnología de comunicacióninalámbrica que tiene ventajas como alta eficiencia espectral, alta tasa de transmisión y es robusta a la propagación por mulitrayecto. Sin embargo, su principal desventaja es que tienealta PAPR (Peak-to-Average Power Ratio).Este artículo presenta la evaluaciónde la técnica OPS (Orthogonal Pilot Sequence) para la reducción de la PAPR en un sistema OFDM con canal multitrayecto. Para la evaluación se consideran dos tipos de canalesmultitrayecto selectivos en frecuencia, con y sin línea de vista. Se evalúa la técnica OPS obteniendola gráfica del BER (Bit Error Rate)vs Eb/No (energy per bit to noise power spectral density ratio) y la gráfica de la CCDF (Cumulative Complementary Distribution Function) para distintos parámetros. Losresultados muestran una reducción de la PAPR cuando se utiliza la técnica OPS y una mejora en el BER.

Performance Evaluation of OFDM System using Pseudo-Pilots with Particle Swarm &amp; Moth Flame (Hybrid) Optimization

This paper is focused on the advanced signal processing techniques for the multi-carrier modulation especially on the orthogonal frequency division multiplexing (OFDM). OFDM has high data rate and robust against the frequency selective multi-path channels. Channel estimation is crucial for the receiver design in coherent detection. In this paper we are investigating and examining the pilot aided system for channel estimation and its special effects on the performance of the OFDM based system. In this paper new technique is proposed which make use of conventional Least Square (LS) and Recursive Least Square (RLS) hybridization techniques for the channel estimation afterwards we apply Particle Swarm Optimization (PSO) and Hybrid PSO (PSO+ Moth Flame Optimization(MFO)) optimization for obtaining more optimize techniques. In the proposed system, to estimate channel impulse response we are using pseudo-pilots instead to pilots as it is useful to overcome the pilot overhead and decrease the complexity by using pseudo random symbol (PRS). The performance of the proposed techniques and the weighted scheme are compared and verified using computerized simulation carried out using Matrix Laboratory (MATLAB) software. It is demonstrated on the basis of graph between BER and signal to Noise Ratio (Eb/NO), that the proposed technique reduces the execution time and increase the transmission rate with low or zero overhead.

Joint Frame Synchronization and Channel Estimation: Sparse Recovery Approach and USRP Implementation

Correlation-based techniques used for frame synchronization can suffer significant performance degradation over multi-path frequency-selective channels. In this paper, we propose a joint frame synchronization and channel estimation (JFSCE) framework as a remedy to this problem. This framework, however, increases the size of the resulting combined channel vector which should capture both the channel impulse response vector and the frame boundary offset and, therefore, its estimation becomes more challenging. On the other hand, because the combined channel vector is sparse, sparse channel estimation methods can be applied. We propose several JFSCE methods using popular sparse signal recovery algorithms which exploit the sparsity of the combined channel vector. Subsequently, the sparse channel vector estimate is used to design a sparse equalizer. Our simulation results and experimental measurements using software defined radios show that in some scenarios our proposed method improves the overall system performance significantly, in terms of the mean square error between the transmitted and the equalized symbols compared to the conventional method.

Practical Evaluations of SEFDM: Timing Offset and Multipath Impairments

The non-orthogonal signal waveform spectrally efficient frequency division multiplexing (SEFDM) improves spectral efficiency at the cost of self-created inter carrier interference (ICI). As the orthogonal property, similar to orthogonal frequency division multiplexing (OFDM), no longer exists, the robustness of SEFDM in realistic wireless environments might be weakened. This work aims to evaluate the sensitivity of SEFDM to practical channel distortions using a professional experiment testbed. First, timing offset is studied in a bypass channel to locate the imperfection of the testbed and its impact on SEFDM signals. Then, the joint effect of a multipath frequency selective channel and additive white Gaussian noise (AWGN) is investigated in the testbed. Through practical experiments, we demonstrate the performance of SEFDM in realistic radio frequency (RF) environments and verify two compensation methods for SEFDM. Our results show first frequency-domain compensation works well in frequency non-selective channel conditions while time-domain compensation method is suitable for frequency selective channel conditions. This work paves the way for the application of SEFDM in different channel scenarios.

Structure-Based Low Complexity MMSE Channel Estimator for OFDM Wireless Systems

Wireless communication systems utilizing orthogonal frequency division multiplexing (OFDM) transmissions are capable of delivering high data rates over multipath frequency selective channels. This paper deals with joint estimation/interpolation of wireless channel using pilot symbols transmitted concurrently with the data. We propose a low complexity, spectrally efficient minimum mean square error channel estimator which exploits the correlation structure of channel frequency response for reducing the complexity. Specifically, it is shown that if pilots are inserted appropriately across OFDM subcarriers, the proposed algorithm requires no matrix inversion, thereby significantly relieving the computational burden without deteriorating the performance. Moreover, the knowledge of channel correlation is also not required for the proposed estimator. Simulation results validate that the proposed technique outperforms existing low-complexity variants in terms of mean square error and computational complexity.

Sparse Frequency Domain Spectrum Sensing and Sharing based on Cyclic Prefix Autocorrelation

Cognitive radio (CR) is considered an important solution to the current spectral scarcity, which is expected to be a significant issue in the next generation of wireless communication systems, namely, 5G. Wideband spectrum sharing and sensing constitute highly desirable features of CR systems as they aim to increase the probability of identifying available spectral bands, which ensures a more efficient resource utilization. This paper proposes an efficient frequency-domain cyclic prefix autocorrelation-based wideband spectrum sensing and sharing method that can provide accurate detection of orthogonal frequency-division multiplexing (OFDM)-based primaries in wideband CR systems. Novel analytic expressions are derived for the corresponding threshold, probability of false alarm, and probability of detection in the presence of noise uncertainty (NU) and frequency selectivity. The derived models are validated by extensive comparisons with respective results from computer simulations. It is demonstrated that the introduced autocorrelation-based sensing method is able to counteract NU and the frequency-selective multipath channel effects in realistic wideband communication scenarios. Furthermore, the method facilitates partial band sensing, allowing the sensing of weak OFDM-type primary user (PU) signals in channels, which are partly overlapped by other strong PU or CR transmissions. This is considered a crucial element in practical spectrum sharing scenarios. Since the proposed sensing method makes use of sparsity in the spectral domain, it can be technically considered as compressed sensing method. The flexibility of this approach supports robust wideband multi-mode, multi-channel sensing with low complexity. Finally, it is shown that the offered results are particularly useful in the context of spectrum sharing as their high performance and reduced complexity can enable the co-existence of non-exhaustive yet highly efficient algorithms.

An Iterative DFE Receiver for MIMO SC-FDMA Uplink

Ever since the adoption of the single carrier frequency division multiple access (SC-FDMA) scheme for the uplink in the Long Term Evolution (LTE) standard, there has been much interest in improved receiver algorithms for the same. Successive interference cancelation (SIC) based turbo receivers (Turbo SIC) have been proposed to tackle the multi-stream interference (MSI) for transmission modes such as spatial multiplexing (SM) and multiuser (MU) multiple input multiple output (MIMO). In addition, decision feedback equalizers (DFE) have been discussed as an alternative to the simple linear minimum mean square error (LMMSE) based receivers to suppress intersymbol interference (ISI) caused by the frequency selective multi-path channel. This paper proposes a DFE receiver variant based on parallel interference cancelation (PIC) with maximum likelihood detection (MLD) and ordered SIC (OSIC) principles to suppress ISI and MSI. Simulations show that the proposed receiver performs better than the existing SIC and DFE based receivers and achieves the matched filter bound (MFB) for both coded and uncoded systems.

Performance analysis of precoding-based asymmetrically clipped optical orthogonal frequency division multiplexing wireless system in additive white Gaussian noise and indoor multipath channel

We have compared the bit error rate (BER) performance of precoding-based asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT) optical wireless (OW) systems in additive white Gaussian noise (AWGN) and indoor multipath frequency selective channel. Simulation and analytical results show that precoding schemes such as discrete Fourier transform, discrete cosine transform, and Zadoff-Chu sequences do not affect the performance of the OW systems in the AWGN channel while they do reduce the peak-to-average power ratio (PAPR) of the OFDM output signal. However, in a multipath indoor channel, using zero forcing frequency domain equalization precoding-based systems give better BER performance than their conventional counterparts. With additional clipping to further reduce the PAPR, precoding-based systems also show better BER performance compared to nonprecoded systems when clipped relative to the peak of nonprecoded systems. Therefore, precoding-based ACO-OFDM and PAM-DMT systems offer better BER performance, zero signaling overhead, and low PAPR compared to conventional systems.

Compressed Receiver for Multipath DSSS Signals

A compressed sensing (CS) assisted receiver for direct sequence spread spectrum (DSSS) signals transmitted over multipath frequency-selective channels is studied in this paper. We present a bit-error-rate analysis for the CS-domain maximum ratio combining receiver with perfect channel state information (CSI), and hence, the CS-induced signal-to-noise ratio (SNR) penalty is quantized. Moreover, to alleviate such penalty, we build a deterministic low pass sinusoid (LPS) matrix, which proves more suitable for the pulse-shaped DSSS signals than the commonly-used random sensing matrices. Furthermore, a joint channel estimation and symbol detection (JCESD) scheme based on structured least-squares search (SLSS) is proposed, whose performance is very close to the analytical lower bound and is far better than that of the orthogonal matching pursuit (OMP) based approach. Our numerical results show that, in contrast to a conventional receiver sampling at a Nyquist rate and relying on perfect CSI, the proposed CS-assisted SLSS-JCESD receiver may reduce the sampling rate requirement by 50% at SNR loss of about 1.2 dB.

Multi-Carrier Asynchronous Bi-Directional Relay Networks: Joint Subcarrier Power Allocation and Network Beamforming

We consider an asynchronous bi-directional relay network, consisting of two single-antenna transceivers and multiple single-antenna relays, where the transceiver-relay paths are subject to different relaying and/or propagation delays. Such a network can be viewed as a multipath channel which can cause inter-symbol-interference (ISI) in the signals received by the two transceivers. Hence, we model such a communication scheme as a frequency selective multipath channel which produces ISI at the two transceivers, when the data rates are high. To tackle ISI, the transceivers can employ an orthogonal frequency division multiplexing (OFDM) scheme to diagonalize the end-to-end channel. The relays use simple amplify-and-forward relaying, thereby materializing a distributed beamformer. For such a scheme, we propose two different algorithms, based on the max-min fair design approach, to calculate the subcarrier power loading at the transceivers as well as the relay beamforming weights. We develop computationally efficient solutions to these two approaches. Simulation results are presented to show that our proposed schemes outperform equal or maximum power allocation schemes.

Performance of Convolution Coding Underwater Acoustic Communication System on Frequency Selectivity Index

천해 수중 음향 채널의 배경잡음과 다중경로에 의한 비트 오류율(BER)을 경감하기 위해 Quadrature Phase Shift Keying(QPSK)에 전방 오류 정정 코드(FEC)로 부호화 비율 1/2의 길쌈 코딩(CC)을 적용하였다. 전송신호의 대역폭에 대한 채널의 일관성 대역폭의 비를 주파수 선택 지표로 정의하였고 주파수 선택지표에 따른 전송 신호의 BER과 비트 에너지 대 잡음비의 이득을 평가하였다. 실내 수조 실험 결과, 주파수 선택지표가 약 1.0 이하인 경우 BER은 이론적인 결과와 일치하고 비트 에너지 대 잡음비의 이득은 약 5 dB로 이론적인 결과와 일치한다. 주파수 선택 지표가 1.0 이상인 주파수 선택적인 다중경로 채널에서도 BER은 효율적으로 감소하지만 비트 에너지 대 잡음비가 일정크기 이상인 조건에서만 CC의 비트 오류 감소에 효과가 있다. 이러한 결과는 본 연구에서 정의한 주파수 선택 지표가 다중 경로 채널에서 CC의 성능 평가의 지표로 적용될 수 있다. 아울러 등화기를 적용하지 않고 저속 수중 음향 통신시스템에 효과적으로 BER을 줄일 수 있다. The convolution code(CC) of code rate 1/2 as a forward error correction (FEC) in Quadrature Phase Shift Keying (QPSK) is applied to decrease bit error rate (BER) by background noise and multipath in shallow water acoustic channel. Ratio of transmitting signal bandwidth to channel coherence bandwidth is defined as frequency selectivity index. BER and bit energy-to-noise ratio gain of transmitted signal according to frequency selectivity index are evaluated. In the results of indoor water tank experiment, BER is well matched theoretical results at frequency selectivity index less than about 1.0. And bit energy-to-noise ratio gain is also matched theoretical value of 5 dB. BER is effectively decreased at frequency selective multipath channel with frequency selectivity index higher than 1.0. But bit energy-to-noise ratio greater than a certain size in terms of CC weaving is effective in reducing bit errors. In the results, the defined frequency selectivity index in this study could be applied to evaluate a performance of CC in multipath channel. Also it could effectively reduced BER in a low speed underwater acoustic communication system without an equalizer.

Performance of COFDM in Underwater Acoustic Channel with Frequency Selective Fading

In this paper, performance of COFDM (Coded Orthogonal Frequency Division Multiplexing) which is OFDM with a forward error correction code, is studied in frequency selective fading underwater acoustic communication channel. The OFDM is a multiplexing technique resistant to frequency selective multipath channel. In OFDM, a broadband information signal is transformed into several narrow band signals and transmits narrow band signals whose bandwidths are less than the channel coherence bandwidth. However, its performance is degraded in a specific narrow band signal due to its deep fading by multipath. To mitigate this degradation, COFDM which is OFDM with convolution code as a forward error correction code, is evaluated. The performance of COFDM is found to be better than that of OFDM in multipath channel.