Time-varying Channel Environment Research Articles

Topology Perception and Relative Positioning of UAV Swarm Formation Based on Low-Rank Optimization

In a satellite-denied environment, a swarm of drones is capable of achieving relative positioning and navigation by leveraging the high-precision ranging capabilities of the inter-drone data link. However, because of factors such as high drone mobility, complex and time-varying channel environments, electromagnetic interference, and poor communication link quality, distance errors and even missing distance values between some nodes are inevitable. To address these issues, this paper proposes a low-rank optimization algorithm based on the eigenvalue scaling of the distance matrix. By gradually limiting the eigenvalues of the observed distance matrix, the algorithm reduces the rank of the matrix, bringing the observed distance matrix closer to the true value without errors or missing data. This process filters out distance errors, estimates and completes missing distance elements, and ensures high-precision calculations for subsequent topology perception and relative positioning. Simulation experiments demonstrate that the algorithm exhibits significant error filtering and missing element completion capabilities. Using the F-norm metric to measure the relative deviation from the true value, the algorithm can optimize the relative deviation of the observed distance matrix from 11.18% to 0.25%. Simultaneously, it reduces the relative positioning error from 518.05 m to 35.24 m, achieving robust topology perception and relative positioning for the drone swarm formation.

FEC-Aided Decision Feedback Blind Mismatch Calibration of TIADCs in Wireless Time-Varying Channel Environments

FEC-Aided Decision Feedback Blind Mismatch Calibration of TIADCs in Wireless Time-Varying Channel Environments

Cooperative Resource Allocation Based on Soft Actor–Critic With Data Augmentation in Cellular Network

This letter investigates the cooperative resource allocation of cellular networks with simultaneous wireless information and power transfer in the time-varying channel environment. The soft actor-critic (SAC) algorithm is exploited to tackle the optimization problem which aims to find a feasible resource allocation policy to maximize the data rate and system fairness while minimizing the channel switching penalty. Considering the costly agent-to-environment interactions and the restricted empirical dataset of the SAC algorithm, this letter explores the permutation equivalence of the optimization objective, and designs two data augmentation schemes for the experience replay buffer of SAC. The cumulative discount reward shows that data augmentation assisted algorithms outperform the baseline in the learning speed. The simulation results referring to the average data rate and system fairness show that the proposed schemes benefit to the training model and effectively improve the performance of algorithms.

A Collision Reduction Adaptive Data Rate Algorithm Based on the FSVM for a Low-Cost LoRa Gateway

LoRa (Long Range), a wireless communication technology for low power wide area networks (LPWANs), enables a wide range of IoT applications and inter-device communication, due to its openness and flexible network deployment. In the actual deployment and operation of LoRa networks, the static link transmission scheme does not make full use of the channel resources in the time-varying channel environment, resulting in a poor network performance. In this paper, we propose a more effective adaptive data rate (ADR) algorithm for low-cost gateways, we firstly analyze the impact of the different hardware parameters (RSSI, SNR) on the link quality and classify the link quality using the fuzzy support vector machine (FSVM). Secondly, we establish an end device (ED) throughput model and energy consumption model and design different adaptive rate algorithms, according to the different link quality considering both the link-level performance and the MAC layer performance. The proposed algorithm uses machine learning to classify the link quality, which can accurately classify the link quality using a small amount of data, compared to other adaptive rate algorithms, and the link parameter adaptation algorithm can maximize the throughput while ensuring the link stability, by considering the link-level performance and the MAC layer performance, compared to other algorithms. The results show that it outperforms the standard LoRaWAN ADR algorithm in both the single ED and the multi ED scenarios, in terms of the packets reception rate (PRR) and the network throughput. Compared to the LoRaWAN ADR in 32 multi-ED scenarios, the proposed algorithm improves the throughput by 34.12% and packets the reception rate by 26%, significantly improving the network throughput and the packets reception rate.

Outdated Access Point Selection for Mobile Edge Computing With Cochannel Interference

In this paper, we investigate a mobile edge computing (MEC) network, where the user has some computational tasks to be assisted by multiple computational access points (CAPs) through offloading. We consider practical communication scenarios with limited spectrum resources, and the cochannel interference arising from the aggressive reuse of frequency severely degrades the system offloading performance. To enhance the system performance, we provide three CAP selection criteria to choose one best CAP among multiple ones. Specifically, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion I</i> maximizes the computational capability at the CAP, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion II</i> minimizes the interfering power, while <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion III</i> maximizes the instantaneous channel gain of data link. In time-varying channel environments, the CAP selection may be outdated, which deteriorates the system performance. For the three criteria, we evaluate the system outage probability in the outdated channel state information (CSI) by taking into account the latency, energy consumption and data rate, and provide the analytical and asymptotic expressions of outage probability, from which we obtain some critical insights on the system design. Simulation results are finally demonstrated to verify the proposed studies. In particular, criterion III under the perfect CSI can achieve the system whole diversity order coming from multiple CAPs.

The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels.

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

A Novel Demodulation Method Based on Spectral Clustering for Phase-Modulated Signals Interrupted by the Plasma Sheath Channel

The phenomenon of radio blackout due to a plasma sheath during reentry has attracted much attention over the last several decades. However, radio blackout has long puzzled aerospace researchers and has not yet been completely resolved. Owing to the effects of the time-varying plasma sheath channel environment, the constellation of received signals exhibits multiple manifolds, making the traditional algorithms based on Euclidean distance unable to perform demodulation. In the current study, we proposed a novel demodulation method based on spectral clustering for phase-modulated signals interrupted by the plasma sheath channel. Experimental results revealed that as long as the receiving radio waves were above the floor of receiver’s dynamic range, the proposed algorithm effectively classified received signals after time-varying plasma. The parasitic modulation interference caused by time-varying plasma was restrained effectively through the novel algorithm. In contrast to the traditional communication method, the proposed method can be applied to telemetry, track and command, as well as communication between reentry vehicles and near-space hypersonic vehicles in future.

Uplink Null-Space Expansion for Multiuser Massive MIMO in Time-Varying Channels Under Unknown Interference

This article proposes a novel postcoding design scheme for suppressing inter-user interference (IUI) and inter-cell interference (ICI) in uplink multiuser massive multiple-input multiple-output (MIMO) system in time-varying channel environments. In the uplink system, the base station (BS) designs postcoding weight based on estimated channel state information (CSI) to suppress IUI. When user terminals move, the estimated CSI is outdated because actual channels vary with time. This causes IUI and leads to degrading the system capacity. Besides, ICI extensively arises in multiuser massive MIMO systems since many users are simultaneously supported in each cell. The accuracy of CSI estimates is degraded since ICI contaminates the uplink pilot sequences from desired users. Adopting a weight design based on minimum mean square error (MMSE) criteria, we can suppress ICI adequately, and exploiting plentiful degrees of freedom (DoFs) of massive array, we can also suppress IUI even in time-varying channels by steering many nulls for one user based on null-space expansion (NSE) scheme. The computer simulations clarify that the proposed scheme has superior SINR performance in Rayleigh fading channel at low speed, low SIR, and high SNR regions while it is effective at almost all conditions in Rician fading channel.

A New Filter-Bank Multicarrier System: The Linearly Processed FBMC System

In this paper, we propose a linearly processed filter-bank multicarrier (LP-FBMC) system which employs faster than Nyquist signaling to remove residual intrinsic interferences. We represent the FBMC transceiver in a matrix form and then apply singular value decomposition-based linear transformation in order to convert the overlapped FBMC data into parallel independent interference-free data. This interference-free characteristic of the proposed LP-FBMC system enables the use of conventional multiple antenna configurations. Performance evaluations show that out-of-band emission performance of the proposed LP-FBMC system is superior to those of conventional quadrature amplitude-based FBMC (FBMC-QAM) and orthogonal frequency division multiplexing systems. Furthermore, the proposed LP-FBMC system outperforms the conventional FBMC-QAM in terms of bit error rate performance when high order modulation is employed under time-varying channel and multiuser uplink environment.

Secrecy Cooperative Networks With Outdated Relay Selection Over Correlated Fading Channels

In this paper, we study the impact of correlated fading on the secrecy performance of multiple decode-and-forward (DF) relaying with outdated relay selection. It is assumed that the information transmission, assisted by $N$ DF relays from the source to the destination, can be overheard by an eavesdropper. Particularly, we consider the realistic scenario where the eavesdropper's and the main channels are correlated. In order to enhance the network security, the best relay is selected among $N$ available DF relays to assist the secure transmission. Due to the time-varying channel environments, we note that the selected relay may be outdated. In order to study the impact of both channel correlation and outdated relay selection on the secrecy performance, we first derive an analytical expression for the secrecy outage probability (SOP). Also, we derive the asymptotic expression for the SOP in the high main-to-eavesdropper ratio regime. Numerical results are provided to demonstrate the correctness of our analytical expressions.

A Robust Distributed Power Control Algorithm for Minimum Interference to Primary Users in Underlay Cognitive Radio Networks

A robust distributed optimal power control (RDPC) scheme under worst case condition is proposed to make primary users (PUs) receive minimum interference generated from all secondary users (SUs) in underlay cognitive radio networks (CRNs). The strategy considers the transmit power of each SU below the maximum allowable power of the devices and interference plus noise ratio (SINR) of each SU under the minimum threshold. Simulation illustrate thatthe RDPC can lead SUs to reduce the interference to PUs, and simultaneously the better meet quality of service (QoS) requirement of SUs in comparison with the distributed power control algorithm (DPC) and the traditional iterative water filling algorithm (IWFA) in time-varying channel environment.

Interference Alignment Based on Antenna Selection With Imperfect Channel State Information in Cognitive Radio Networks

Interference alignment (IA) is a promising technique that can eliminate interference in wireless networks effectively and has been applied to spectrum sharing in cognitive radio (CR) networks. However, most existing IA schemes neglect the quality of the desired signal, which may lead to poor performance, particularly at poor channel status. In this paper, we analyze the problem of the decrease in the signal-to-interference-plus-noise ratio (SINR) of the desired signal and propose a novel IA scheme based on antenna selection (AS) to improve the received SINR of each user in IA-based CR networks. In the proposed scheme, multiple antennas are equipped at each secondary receiver, and some of them are chosen to achieve optimal performance. Furthermore, the condition of imperfect channel state information (CSI) is also considered, which can impact the performance of IA-AS. To face this problem, a scheme called CSI filtering is proposed to weaken the influence of the imperfect CSI. Moreover, considering the considerable computational complexity brought by the selection among mass of antenna combinations, an efficient IA-AS algorithm based on discrete stochastic optimization (DSO) is thus proposed, which can converge quickly to the optimum with low computational complexity. To further improve the tracking performance of the algorithm under a time-varying channel environment, we propose an adaptive DSO scheme with window CSI filtering for IA-AS to give the algorithm a good tracking capability. Simulation results are presented to show that the proposed schemes can significantly improve the performance of IA-based CR networks.

Underwater acoustic communication in time-varying channel environment based on passive time reversal

Channels estimated from probe signal or training symbols will mismatch with the true channels in passive time reversal (TR) underwater acoustic (UWA) communication when the ocean environment is time-varying, leading to poor channel equalization performance. In order to solve this problem, this paper studies Block-based TR processing structure. The received data are divided into small blocks and the channel estimated from previously decoded symbols is used to match filter the current block to suppress the channel mismatch. Decision feedback equalizer (DFE) is also combined with Block-based TR to remove the residual inter symbol interference (ISI) and Doppler effect (Block-based TR-DFE). Mobile UWA communication experiment was conducted near Xiao Changshan island, Dalian in July, 2015. Though the received data are preprocessed by resampling, residual Doppler effect still exists due to ununiform motion between the receiver and transmitter, making the channel time-varying fastly. Block-based TR realized effective tracking and compensation for time-varying channels. The output signal-to-noise ratio (SNR) after equalization is greatly improved and the bit error rate (BER) is significantly reduced.

다중사용자 상향링크 환경을 위한 적응형 다중안테나 채널추정 기법

In this letter, an adaptive multi-antenna channel estimation scheme is proposed for uplink multiuser environments such as LTE-A systems to accurately estimate time-varying channels within an affordable complexity. It is confirmed that the proposed channel estimator can achieve accurate channel tracking performance even when various time-varying channel environments and traffic patterns are provided. Ⅰ. 서 론

Random Linear Network Coding Based on Outdated Channel-State Information

Scheduling based on random linear network coding is an effective way of improving system performance in a wireless network. In a time-varying channel environment, it is important to take the effects of outdated channel-state information (CSI) into consideration when scheduling because the CSI used may be different from the real CSI for data transmissions due to mobility and feedback delays. Here, we analyze the outage probability for scheduling based on random linear network coding in an outdated CSI environment. Practical scenarios are assessed so that the outage probability performance can be evaluated reliably.

An Adaptive Allocation Scheme in Multiuser OFDM Systems with Time-Varying Channels

Previously, a scheme in [1] is proposed for the subcarrier, bit, and power allocation problem to minimize the total transmit power for multiuser orthogonal frequency division multiplexing systems in downlink transmission. However, it is a batch mode which may not be so efficient in terms of computational complexity for slowly time-varying channel environments. The solution of the current frame can be obtained with slight modification from that of the previous frame in an adaptive fashion. By utilizing this property, we propose a scheme to obtain the solution in the adaptive fashion, which offers comparable performance with a reduced complexity compared to the previously proposed method and other existing suboptimal methods. Based on a derived expression composed of the channel gains, the numbers of assigned subcarriers, and the data rates along with the new proposed processing procedures, the proposed adaptive scheme is able to track the channel variation for the solution adjustment in a faster speed compared to the original batch mode method. Simulation results reveal that the proposed adaptive scheme has the competitive performance compared with those of the optimal and the existing schemes while the computational complexity and the number of iterations are both reduced.

Robustness of a time-reversal ultra-wideband system in non-stationary channel environments

Time reversal (TR) is regarded as a potential future transmission scheme for ultra-wideband (UWB) communication systems. However, the need for a perfect channel estimation is regarded as one of the main drawbacks of a TR system. It is assumed that in the case of a time-varying channel or imperfect channel estimation, the performance of the TR scheme degrades enormously. Based on this assumption, the time-reversal scheme is not considered suitable for such environments. Here, the robustness of a TR system in a time-varying channel environment is studied. The experiments are performed for a time-varying channel environment for fixed terminals and for a displaced terminal with a stationary channel environment. The results show that if the channel maintains some partial correlation with the previous channel, the TR system can perform robustly.

A RACH Preamble Detection Scheme Using Variable Coherent Correlation Intervals for WCDMA Systems

A new random access channel (RACH) preamble detection scheme using variable coherent correlation intervals (CCIs) is proposed. It is shown first that it is enough to employ two CCIs for supporting a user equipment (UE) velocity of 300 km/h, and then a CCI selection criterion is proposed. Computer simulation results indicate that the proposed scheme can provide a robust detection performance in time-varying fading channel environments.

MIMO-OFDM system based on fractional Fourier transform and selecting algorithm for optimal order

In the rapidly time-varying channel environment, the performance of traditional MIMO-OFDM system is deteriorated due to the intercarrier interference. In this paper, a novel MIMO-OFDM system is proposed, in which the modulation and demodulation of the symbols are implemented by the fractional Fourier transform instead of traditional Fourier transform. Through selecting the optimal order of the fractional Fourier transform, the modulated signals can match the time-varying channel characteristics, which results in a mitigation of the intercarrier interference. Furthermore, an algorithm is presented for selecting the optimal order of fractional Fourier transform, and the impact of system parameters on the optimal order is analyzed. Simulation results show that the proposed system can concentrate the power of desired signal effectively and improve the performance over rapidly time-varying channels with respect to the traditional MIMO-OFDM system.

Adaptive Two-Stage GSC-Based PIC Detection for Time-Varying MIMO Channels

Adaptive parallel interference cancellation (PIC) has been recently proposed for the signal detection in multiple- input multiple-output (MIMO) systems. However, it suffers from error propagation when operated in time-varying channels. In this letter, an adaptive two-stage PIC with the minimum variance (MV) criterion is proposed to solve the problem. Adaptation with the MV criterion is realized with a decision feedback generalized sidelobe canceller (DFGSC). In the first-stage cancellation, a special structure involving dual DFGSCs is developed. All adaptation operations are implemented with the least-mean-square (LMS) algorithm. Simulations show that the proposed adaptive PIC detection can significantly outperform the conventional adaptive PIC detection in time-varying MIMO channel environments.