Multipath Channels Research Articles

Моделирование каналов связи с многолучевым распространением сигналов процедурами помехоустойчивого кодирования в рамках стандарта LTE

A scheme of orthogonal frequency division multiplexing technologies with a cyclic prefix was used, using the fast Fourier transform algorithm and amplifiers on the transmitter side and a normalizer on the receiver side. By adjusting the gains of the transmitting and receiving sides, the circuit practically makes it possible to reduce situations when inter-symbol interference (ISI) is affected to situations where it does not exist. The proposed model is modeled using Simulink based on MATLAB. The scheme was investigated for the bit error rate (BER) using the additive white Gaussian noise (AWGN) channel and the multipath Rice fading channel operating under the influence of ISI and different parameters for the channel were investigated, where cases of signal delay similar to the EPA standards (Extended Pedestrian A model) were considered. Data transmission in the system includes a Relay channel and AWGN with different values of signal-to-noise ratio (SNR, dB) and different values of Gain, dbGain amplifier. Result: A graph of data transmission performance in a multipath channel with fading with respect to BER and SNR (BER ≈ 0 with values of SNR –21dB) was obtained. The effect of intersymbol interference on the receiver side is also considered by analyzing eye diagrams. The research data can be used in the design of radio engineering devices for data transmission over a wireless network.

Локальное местоопределение приемника связи и проблема многолучевости в сложных условиях

In conditions when the signals of satellite navigation systems are unavailable or distorted, the receiver positioning task could be solved by local positioning system with an integrated data transmission channel. However, when such a system operates in various environments, a lot of multipath signals might appear, which strongly distort delay and phase measurements, on the basis of which the receiver coordinates are calculated. The accuracy of measurements can be significantly increased by introducing measurement redundancy by using the signal reflection properties and increasing the tracking channels on the receiver. In this article, a technique is proposed for creating and using the redundancy of phase measurements, as well as the phase derivatives differences of the local positioning system signals. This technique is based on the effects of signal reflection. An algorithm is proposed for estimating the intensity of the relative acceleration of a moving object, which makes it possible, using the threshold method, to switch between receiver channels at the moments when abnormal spikes appears because of the influence of a multipath signal propagation channel. An algorithm for smoothing transitions between antennas is also proposed using cubic spline interpolation. The obtained methods and algorithms, using two receiving antennas with a single phase center, make it possible to exclude about 80% of spikes caused by multipath effects from estimates of the relative velocity of a moving object, and also provide a basis for developing more advanced methods for using redundancy and further research in this area.

The Usage of ANN for Regression Analysis in Visible Light Positioning Systems.

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches. Three different ANN algorithms are considered, including Levenberg–Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, to minimize the positioning error () in the VLP system. The ANN design is optimized based on the number of neurons in the hidden layers, the number of training epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional received signal strength (RSS) technique using the non-linear least square estimation for all values of signal to noise ratio (SNR). Furthermore, in the inner region, which includes the area of the receiving plane within the transmitters, the positioning accuracy is improved by 43, 55, and 50% for the SNR of 10, 20, and 30 dB, respectively. In the outer region, which is the remaining area within the room, the positioning accuracy is improved by 57, 32, and 6% for the SNR of 10, 20, and 30 dB, respectively. Moreover, we also analyze the impact of different training dataset sizes in ANN, and we show that it is possible to achieve a minimum of 2 cm for 30 dB of SNR using a random selection scheme. Finally, it is observed that is low even for lower values of SNR, i.e., values are 2, 11, and 44 cm for the SNR of 30, 20, and 10 dB, respectively.

Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM.

Downlink precoding is considered for multi-path multi-input single-output channels where the base station uses orthogonal frequency-division multiplexing and low-resolution signaling. A quantized coordinate minimization (QCM) algorithm is proposed and its performance is compared to other precoding algorithms including squared infinity-norm relaxation (SQUID), multi-antenna greedy iterative quantization (MAGIQ), and maximum safety margin precoding. MAGIQ and QCM achieve the highest information rates and QCM has the lowest complexity measured in the number of multiplications. The information rates are computed for pilot-aided channel estimation and a blind detector that performs joint data and channel estimation. Bit error rates for a 5G low-density parity-check code confirm the information-theoretic calculations. Simulations with imperfect channel knowledge at the transmitter show that the performance of QCM and SQUID degrades in a similar fashion as zero-forcing precoding with high resolution quantizers.

Long-range underwater acoustic communication of M-eyry spread spectrum with cyclic prefix

The Spread Spectrum is an effective transmission method for complex channels in underwater acoustic (UWA) communication because of the high correlation of pseudo-random noise (PN) sequence. In particular, the spread spectrum method is effective in an environment with a low signal-to-noise ratio. The bandwidth of UWA communication channel is limited due to the fact that sound wave attenuation in water is positively associated with frequency. The limited bandwidth directly leads to the low data rate of conventional direct-sequence spread spectrum UWA communication. M-ary spread spectrum (MSS) schemes using multiple orthogonal PN sequences were proposed as a solution to this problem. However, even in the MSS method, the performance may be limited by the delay spread characteristics in the multipath propagation channels. We propose a more robust communication method in the UWA channel by including Cyclic Prefix (CP) to achieve a more robust performance in the multipath channel. In the proposed method, a CP is inserted for every symbol. In the 160 km long-range UWA communication experiment conducted in the East Sea, the proposed method showed more reliable results than the conventional MSS method. [Work supported by the Agency for Defense Development, South Korea, Grant No. UD200010DD.]

Estimation and interpretation of multipath channel activity using braiding techniques

Robust underwater acoustic channel estimation is critical towards improving communications efforts and enhancing awareness of changing environments. To explore these channels in-depth, machine learning algorithms are developed through feature geometric representations, referred to as “braiding,” to interpret multipath ray bundles within shallow water acoustic channels in two ways. The first application of this work predicts the number of reflections an acoustic signal may undergo through the environment by applying known physical parameters and braid features. The second application explores the importance of a braid feature within the acoustic channel for estimation purposes by using braid path information. Three unique machine learning techniques are trained to predict the applications using a diverse set of shallow water acoustic channels generated through the BELLHOP model. Machine learning models developed for the applications demonstrate high testing accuracies with an accuracy of 86.70% in the first application and an accuracy of 99.94% in the second application. As a further demonstration, braid feature representations and model predictions are used for channel estimation and determining the number of reflections using SPACE08 field data.

Delay Estimation for Ranging and Localization Using Multiband Channel State Information

In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth of the training signals used for channel probing. Considering that typical training signals have limited bandwidth, delay estimation using these algorithms often leads to poor localization performance. To mitigate these constraints, we exploit the multiband and carrier frequency switching capabilities of wireless transceivers and propose to acquire channel state information (CSI) in multiple bands spread over a large frequency aperture. The data model of the acquired measurements has a multiple shift-invariance structure, and we use this property to develop a high-resolution delay estimation algorithm. We derive the Cramér-Rao Bound (CRB) for the data model and perform numerical simulations of the algorithm using system parameters of the emerging IEEE 802.11be standard. Simulations show that the algorithm is asymptotically efficient and converges to the CRB. To validate modeling assumptions, we test the algorithm using channel measurements acquired in real indoor scenarios. From these results, it is seen that delays (ranges) estimated from multiband CSI with a total bandwidth of 320 MHz show an average RMSE of less than 0.3 ns (10 cm) in 90% of the cases.

Joint equalizer and phase-locked loop for time variability in underwater acoustic communications

In this paper, we verify the performance of the equalizer and phase-locked loop (PLL) operating jointly for channel time variability in underwater acoustic communications. We apply the decision feedback equalizer in order to eliminate channel multipath and PLL to phase rotation due to Doppler effects. In the PLL, a decision-directed tan−1 type phase detector is adopted. As shown in previous papers, it is difficult to make PLL to be steady state because of time-varying ISI occurred by multipath. Also, the phase rotation incurs the equalizer tap rotation. Therefore, we can see that the two subsystems of equalizer and PLL complement each other perfectly. Another issue is the convergence speed; how quickly we can make the joint equalizer and PLL to be stable state within the preamble period (known data). In order to verify the performance, the sea experiments were conducted in the condition of moving transmitter. The transmitted signal is modulated by using PSK and consists of five burst frames that are composed of preamble of PN code and random data. As a result, if we use the initial multipath value and Doppler frequency offset, we can make the joint equalizer and PLL to be the steady state more quickly.

Machine Learning Empowered Accurate CSI Prediction for Large-Scale 5G Networks

Wi-Fi networks rely on channel estimation to ensure their performance. The computational complexity and dependability of fifth generation telecommunication networks have significantly improved using supervised learning. In this paper, we develop a channel estimation model that uses a machine learning approach and the study uses multipath channel simulations for the estimation of channel state information (CSI) over arbitrary transceiver antennas. The simulation is conducted to test the efficacy of the model against various machine learning channel estimation models. The results of simulation show that the proposed model obtains increased channel estimation quality than other methods. Further, the bit error rate is recorded low among other methods using the machine learning model. Thus, it is seen that the proposed method achieves a reduced mismatch rate of 1.26 × 10 − 1.5 than other methodson Doppler frequency during channel estimation, where the mismatch rate is higher in existing methods.

Indoor Positioning of Low-Cost Narrowband IoT Nodes: Evaluation of a TDoA Approach in a Retail Environment.

The localization of internet of things (IoT) nodes in indoor scenarios with strong multipath channel components is challenging. All methods using radio signals, such as received signal strength (RSS) or angle of arrival (AoA), are inherently prone to multipath fading. Especially for time of flight (ToF) measurements, the low available transmit bandwidth of the used transceiver hardware is problematic. In our previous work on this topic we showed that wideband signal generation on narrowband low-power transceiver chips is feasible without any changes to existing hardware. Together with a fixed wideband receiving anchor infrastructure, this facilitates time difference of arrival (TDoA) and AoA measurements and allows for localization of the fully asynchronously transmitting nodes. In this paper, we present a measurement campaign using a receiver infrastructure based on software-defined radio (SDR) platforms. This proves the actual usability of the proposed method within the limitations of the bandwidth available in the ISM band at . We use the results to analyze the effects of possible anchor placement schemes and scenario geometries. We further demonstrate how this node-to-infrastructure-based localization scheme can be supported by additional node-to-node RSS measurements using a simple clustering approach. In the considered scenario, an overall positioning root-mean-square error (RMSE) of is achieved.

Study of the Alamouti-OFDM system using ZP technique and training symbols in multi path selective fading channel

In this paper, we propose a modified Alamouti code matrix and it associated with zero padding orthogonal frequency division multiplexing known as (Alamouti- ZP OFDM). Which zero padding (or zeros samples) are adopted over the OFDM symbols that construct also the encoded symbols of the Alamouti matx. Training symbols are applied for the channel estimation. Furthermore, the ML decoding algorithm is used to get output bits which the BER can be measured. Using the selective multi path fading as model for wireless channel to evaluate the performance provided by the system proposed. The performance of the approach proposed is based on BER parameter. For that, the system is simulated in two profiles of paths number (3 paths, and 6 paths) have used, which the spread delays of these paths are taken (in millisecond and in microsecond) respectively. Different data stream are simulated and compared. And the BER performance are compared also for ifft lengths 512 and 1024 and the BER results presented for all parameters of (paths number, and spread delays). The simulation results show that the system presented performed good even the spread delays of multi path channel are great (microseconds or milliseconds) and even increased the data simulated from increasing the parallel of the data streams transmitted in the system study . So, the system could keen their effectiveness against of fading channel and ISI phenomenon. And finaly, it is shown that increasing IFFT samples in the simulation process the improvements are more enhanced of the approach proposed.

Modeling and Analyzing Trellis-Coded Modulation on Power Line Communication Systems

Power Line channels present a very harsh environment for high speed data transfer which degrades the data transmission. Using proper channel coding can enhance the data transmission over PLC systems. The purpose of using channel coding is to encode the information transmitted over communication channel in such a way that in presence of other interferences and noise, the error can be detected and possibly corrected. This paper investigates the Bit Error Rate (BER) performance of PLC systems based on Orthogonal Frequency Division Multiplexing (OFDM), in presence of Middleton class A noise, and applying Trellis Coded Modulation (TCM) / Rectangular Quadrature Amplitude Modulation (QAM) TCM as a channel coding. Simulations are undertaken in Matlab 2013b. The obtained results illustrates that although trellis codes produce improvements in the SNR in presence of Additive white Gaussian noise (AWGN), they do not perform well with multipath power line channel and Middleton class A noise. Therefore the Rectangular QAM TCM has been used to enhance the results.

Precoded IM-OFDM-SS for Underwater Acoustic Communication

The nature of the multipath channel and the peak-to-average power ratio (PAPR) are regarded as the main challenges restricting the design of a multicarrier reliable underwater acoustic (UWA) communication. This paper proposes a new scheme, precoded index modulation orthogonal frequency division modulation spread spectrum (IM-OFDM-SS), for UWA communication. The precoded IM-OFDM-SS is proposed to increase the transmission efficiency and exploit the spreading and multipath diversities and, at the same time, reduce the PAPR to achieve a reliable communication system. Two different precoders, discrete Hartley transform (DHT) and discrete cosine transform (DCT), are utilized in the proposed scheme and compared with the conventional IM-OFDM-SS scheme. Simulation and real experimental results demonstrate the outperformance of the proposed precoded IM-OFDM-SS in comparison to the conventional benchmarks in terms of PAPR and bit error rate (BER) performance.

Generalized Approximate Message Passing Equalization for Multi-Carrier Faster-Than-Nyquist Signaling

Multi-carrier faster-than-Nyquist (MFTN) signaling constitutes a promising spectrally efficient non-orthogonal physical layer waveform. In this correspondence, we propose a pair of low-complexity generalized approximate message passing (GAMP)-based frequency-domain equalization (FDE) algorithms for MFTN systems operating in multipath channels. To mitigate the ill-condition of the resultant equivalent channel matrix, we construct block circulant interference matrices by inserting a few cyclic postfixes, followed by truncating the duration of the inherent two-dimensional interferences. Based on the decomposition of the block circulant matrices, we develop a novel frequency-domain received signal model using the two-dimensional fast Fourier transform for mitigating the colored noise imposed by the non-orthogonal matched filter. Moreover, we derive a GAMP-based FDE algorithm and its refined version, where the latter relies on approximations for circumventing the emergence of the ill-conditioned matrices. Our simulation results demonstrate that, for a fixed spectral efficiency, MFTN signaling can significantly improve the bit error rate (BER) performance by jointly optimizing the time- and frequency-domain packing factors. Compared to its Nyquist-signaling counterpart, our proposed MFTN systems employing the refined GAMP equalizer can achieve about 39% higher transmission rates at a negligible BER performance degradation.

Design and Performance Analysis of a Robust Multi-Carrier M-Ary DCSK System: A Noise Suppression Perspective

A Noise Suppression aided Multi-Carrier <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary Differential Chaos Shift Keying (NS-MC-MDCSK) system is proposed here where each information subcarrier transmits an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary information-bearing signal and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary constellation symbols are constructed by orthogonal Walsh codes to improve the energy efficiency. Exploiting the redundant information available in the received signal, we propose a noise suppression algorithm to suppress channel noise in the reference and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary information-bearing signals. In the proposed algorithm, correlation coefficients detected between the received reference and information-bearing signals are fed back to suppress the noise corrupting the signal received. This method reduces the channel noise significantly and provides an outstanding Bit Error Rate (BER) performance. A performance analysis is performed for the NS-MC-MDCSK system over Additive White Gaussian Noise (AWGN) and multipath fading channels. Finally, the BER performance of the NS-MC-MDCSK system is compared to that of other chaotic communications systems. It is shown that the NS-MC-MDCSK system offers better BER performance than its competitors.

An Efficient ICI Cancellation Scheme to Mitigate the Effect of ICI on OFDM Systems.

Inter-carrier interference (ICI) emerges in orthogonal frequency division multiplexing (OFDM) systems used for mobile communication as a consequence of the Doppler Effect's loss of orthogonality among subcarriers. Inter-Carrier Interference (ICI), which affects every subcarrier, drastically lowers performance. The performance of OFDM systems may be enhanced using a variety of ICI mitigation strategies. Comparable subcarrier frequency offsets are guaranteed by the premise that the OFDM transmission bandwidth is suitably modest in the majority of ICI mitigation strategies, on the other hand. The frequency offsets between each subcarrier might change, hence a wideband OFDM system in a situation with high mobility is investigated. Furthermore, the suggested ICI cancellation approach, Total ICI Cancellation, does not reduce bandwidth efficiency or transmission rate. As an example, the Total ICI Cancellation approach uses the ICI matrix's orthogonality to provide perfect ICI cancellation and a significant boost in BER at a linearly increasing cost. The suggested technique, which matches the BER performance of a wideband OFDM system without ICI, offers the best BER performance possible in the presence of frequency offset and time shifts in the channel, according to simulation findings in the AWGN and multipath fading channels.

Stochastic Fading Channel Models With Multiple Dominant Specular Components

We introduce a comprehensive statistical characterization of the multipath wireless channel built as a superposition of scattered waves with random phases. We consider an arbitrary number <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> of specular (dominant) components plus an undetermined number of other weak diffusely propagating waves. Our approach covers the cases in which the specular components have constant amplitudes, as well as when these components experience random fluctuations. We show that this class of fading models can be expressed in terms of a continuous mixture of an underlying Rician (or Rician shadowed) fading model, averaged over the phase distributions of the specular waves. The proposed model parameters can be adjusted to tailor the statistical distribution of the received radio signal power to a wide variety of wireless scenarios, some of which are not covered by other state-of-the-art stochastic wireless channel models. In this regard, we verify that the proposed models accurately fit experimental measurements for which their multi-modality cannot be properly captured by other current stochastic models. It is shown that the fluctuations of the specular components have a detrimental impact on performance, and it is formally demonstrated that the lower error rate is obtained when the signal power is concentrated on a single specular component, regardless of whether it fluctuates or not.

Deep Learning-Aided Signal Detection for Two-Stage Index Modulated Universal Filtered Multi-Carrier Systems

The growing interests in Internet of Underwater Things (IoUT) put forward more demands for underwater acoustic (UWA) communication technologies. However, the conventional orthogonal frequency division multiplexing (OFDM) technology underperforms in terms of the resistance to carrier frequency offset (CFO), symbol time offset (STO), and applicability to multiple application scenarios. To remedy the deficiencies, this paper introduces the emerging universal filtered multi-carrier (UFMC) technology into UWA communications and devises a two-stage index modulated UFMC (TSIM-UFMC) system for performance improvement. In addition, a deep learning-aided signal detector termed as TSIMNet is proposed for the TSIM-UFMC system over multipath UWA channels. Specifically, at the transmitter, the TSIM-UFMC system adopts two-stage index modulation to characterize the different position information of data, pilot, and inactive subcarriers in each subblock for ameliorating the bit error rate (BER) performance under channel interferences. At the receiver, the TSIMNet detector exploits configurable deep neural networks to encapsulate the index demodulation, channel estimation, and constellation demodulation for optimizing the system structure. Furthermore, TSIMNet can be deployed to detect the received signal online for the TSIM-UFMC system after trained by offline data. Numerical results reveal that the proposed TSIM-UFMC system exhibits achievable advantages in combating CFO and STO, and the TSIMNet detector actualizes a near-optimal performance on BER with preferable computational complexity.

Time‐varying non‐line‐of‐sight (NLOS) satellite navigation channel modelling and simulation using multiple point‐scatterers

Recently, there has been an increasing interest in modelling and simulation of time-varying (TV) non-line-of-sight (NLOS) channels for global navigation satellite systems (GNSS) as an assisted means of resolving the GNSS urban canyon problem. In the above context, modelling and simulation of TV NLOS channels for GNSS have been investigated and studied due to their rapidly TV characteristics. However, conventional simulation approaches for TV multipath channels suffer from inconsistency and lack physical soundness, resulting in a non-smooth transition of the Doppler shift and low simulation output accuracy. The authors propose an improved satellite navigation channel modelling and simulation method for TV NLOS reception scenarios. The multiple-point-scatterer model framework is applied to the TV NLOS satellite navigation channel model. The major novelty of the proposed method is integrating the multiple-point-scatterer model with online planning of a kinematics trajectory to map changes in the continuous velocity to the Doppler shift, which can keep consistency and accuracy. As a side benefit of the authors' work, numerical integration based on the efficient composite trapezoidal rule is proposed to calculate the precise changes in signal path length, phase, and Doppler shift. The numerical simulation results show that the proposed modelling and simulation method can not only accurately simulate the TV characteristics of the channel multipath with the continuous phase and the Doppler shift, but also reproduce the Rayleigh fading statistics of the TV channel, thus effectively approximating the physical propagation model and generating the TV NLOS satellite navigation channel.

Performance evaluation of wireless local area network with congested fading channels

The IEEE 802.11ay wireless communication standard consents gadgets to link in the spectrum of millimeter wave (mm-Wave) 60 Giga Hertz band through 100 Gbps bandwidth. The development of promising high bandwidth in communication networks is a must as QoS, throughput and error rates of bandwidth-intensive applications like merged reality (MR), artificial intelligence (AI) related apps or wireless communication boggling exceed the extent of the chronic 802.11 standard established in 2012. Thus, the IEEE 802.11ay task group committee has newly amended recent physical (PHY) and medium access control (MAC) blueprints to guarantee a technical achievement especially in link delay on multipath fading channels (MPFC). However, due to the congestion of super bandwidth intensive apps such as IoT and big data, we propose to diversify a propagation delay to practical extension. This article then focuses on a real-world situation and how the IEEE 802.11ay design is affected by the performance of mm-Wave propagation. In specific, we randomize the unstable MPFC link capacity by taking the divergence of congested network parameters into account. The efficiency of congested MPFC-based wireless network is simulated and confirmed by advancements described in the standard.