Small-scale Fading Effects Research Articles

Coverage Analysis for High-Speed Railway Communications with Narrow-Strip-Shaped Cells over Suzuki Fading Channels.

Unlike circular cell coverage in public land mobile communications, narrow-strip-shaped cell coverage should be considered in high-speed railway (HSR) communications. Moreover, for the coverage analysis in HSR communications, most works ignore the effect of small-scale fading, which results in an inaccurate coverage performance evaluation. In this paper, we focus on the coverage analysis for HSR communications with narrow-strip-shaped cells over the Suzuki fading channel, where the composite channel fading includes path loss, lognormal shadowing, and Rayleigh-distributed small-scale fading. Based on the channel model, we first analyze the statistical characteristic of the received signal-to-noise ratio. Then, we derive analytical expressions of the edge coverage probability (ECP) and the percentage of cell coverage area (CCA). To link the edge coverage performance and the average coverage performance of a cell, we express the percentage of CCA as a summation of the ECP and a positive increment. As special cases, we also obtain the coverage performance expressions for the systems without small-scale fading. Through Monte Carlo simulations, the accuracy of the derived expressions is verified. Numerical results also show that the small-scale fading has a strong effect on coverage performance and cannot be ignored. In addition, the effects of key parameters are also discussed.

Intelligent-reflecting-surfaces-assisted hybrid FSO/RF communication with diversity combining: a performance analysis

Free space optics (FSO) and radio frequency (RF) communication systems exhibit complementary characteristics, with FSO being susceptible to fog, turbulence, and pointing errors, whereas RF is susceptible to rain and small scale fading. These inherent complementary characteristics between FSO and RF communication systems enable the hybrid configuration to effectively alleviate the impact of environmental impediments. This paper presents the performance analysis of an intelligent reflecting surfaces (IRSs)-assisted hybrid FSO/RF system under atmospheric turbulence (AT), pointing errors (PE), small scale fading effects, and attenuation due to climatic conditions such as fog, rain, etc. To characterize the AT, gamma–gamma distribution is used, and the multipath fading in the RF link is modeled using Nakagami-m distribution. At the receiver, signals from both the FSO and RF links are combined using either the selection combining (SC) or maximal-ratio combining (MRC) technique. We derive the exact closed-form expressions for outage probability and average symbol error rate (ASER) for both diversity combining schemes. The proposed system is compared with the direct link (DL) FSO system, IRSs-assisted FSO system, and hybrid FSO/RF system with diversity combining schemes. Further, the performance comparison between the SC and MRC schemes is also reported. Finally, the accuracy of the analytical expressions is verified by utilizing Monte Carlo simulations.

A channel perceiving attack and the countermeasure on long-range IoT physical layer key generation

Physical layer key generation is a lightweight technique to generate secret keys from wireless channels for resource-constrained Internet of things (IoT) applications. The security of the key generation relies on spatial decorrelation, which assumes that eavesdroppers observe uncorrelated channel measurements when they are located over a half-wavelength away from legitimate users. Unfortunately, no experimental validation exists for communications environments with both large-scale and small-scale fading effects. Furthermore, while the current key generation work mainly focuses on short-range communications techniques such as WiFi and ZigBee, the exploration with long-range communications, e.g., LoRa, is somewhat limited. This paper presents a long-range key generation testbed and reveals a new attack scenario that perceives and utilizes large-scale fading effects in key generation channels, by using multiple eavesdroppers circularly around a legitimate user. We formalized such an attack and validated it through extensive experiments conducted in indoor and outdoor environments. It is corroborated that the attack reduces secret key capacity when large-scale fading is predominant. We further investigated potential defenses by proposing a conditional entropy and high-pass filter-based countermeasure to estimate and eliminate large-scale fading components. The experimental results demonstrated that the countermeasure significantly improved the key generation’s security when both large-scale and small-scale fading existed. The keys generated by legitimate users have a desirable low key disagreement rate (KDR) and are validated by the NIST randomness tests. In contrast, eavesdroppers’ average KDR is increased from 0.25 to 0.49.

Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model.

Two-wave with diffuse power (TWDP) is one of the most promising models for description of a small-scale fading effects in the emerging wireless networks. However, its conventional parameterization based on parameters K and is not in line with model’s underlying physical mechanisms. Accordingly, in this paper, we first identified anomalies related to usage of conventional TWDP parameterization in moment-based estimation, showing that the existing -based estimators are unable to provide meaningful estimates in some channel conditions. Then, we derived moment-based estimators of recently introduced physically justified TWDP parameters K and and analyzed their performance through asymptotic variance (AsV) and Cramer–Rao bound (CRB) metrics. Performed analysis has shown that -based estimators managed to overcome all anomalies observed for -based estimators, simultaneously improving the overall moment-based estimation accuracy.

Efficient Channel Charting via Phase-Insensitive Distance Computation

Channel charting is an unsupervised learning task whose objective is to encode channels so that the obtained representation reflects the relative spatial locations of the corresponding users. It has many potential applications, ranging from user scheduling to proactive handover. In this letter, a channel charting method is proposed, based on a distance measure specifically designed to reduce the effect of small scale fading, which is an irrelevant phenomenon with respect to the channel charting task. A nonlinear dimensionality reduction technique aimed at preserving local distances (Isomap) is then applied to actually get the channel representation. The approach is empirically validated on realistic synthetic multipath MIMO channels, achieving better results than previously proposed approaches, at a lower cost.

An Alternative Statistical Characterization of TWDP Fading Model.

Two-wave with diffuse power (TWDP) is one of the most promising models for the description of small-scale fading effects in 5G networks, which employs mmWave band, and in wireless sensor networks deployed in different cavity environments. However, its current statistical characterization has several fundamental issues. Primarily, conventional TWDP parameterization is not in accordance with the model’s underlying physical mechanisms. In addition, available TWDP expressions for PDF, CDF, and MGF are given either in integral or approximate forms, or as mathematically untractable closed-form expressions. Consequently, the existing TWDP statistical characterization does not allow accurate evaluation of system performance in all fading conditions for most modulation and diversity techniques. In this regard, physically justified TWDP parameterization is proposed and used for further calculations. Additionally, exact infinite-series PDF and CDF are introduced. Based on these expressions, the exact MGF of the SNR is derived in a form suitable for mathematical manipulations. The applicability of the proposed MGF for derivation of the exact average symbol error probability (ASEP) is demonstrated with the example of M-ary PSK modulation. The derived M-ary PSK ASEP expression is further simplified for large SNR values in order to obtain a closed-form asymptotic ASEP, which is shown to be applicable for SNR > 20 dB. All proposed expressions are verified by Monte Carlo simulation in a variety of TWDP fading conditions.

Attenuation of Several Common Building Materials: Millimeter-Wave Frequency Bands 28, 73, and 91 GHz

Future cellular systems will make use of millimeter wave (mmWave) frequency bands. Many users in these bands are located indoors, i.e., inside buildings, homes, and offices. Typical building material attenuations in these high frequency ranges are of interest for link budget calculations. In this paper, we report on a collaborative measurement campaign to find the attenuation of several typical building materials in three potential mmWave bands (28, 73, 91 GHz). Using directional antennas, we took multiple measurements at multiple locations using narrow-band and wide-band signals, and averaged out residual small-scale fading effects. Materials include clear glass, drywall (plasterboard), plywood, acoustic ceiling tile, and cinder blocks. Specific attenuations range from approximately 0.5 dB/cm for ceiling tile at 28 GHz to approximately 19 dB/cm for clear glass at 91 GHz.

Adaptive Mini-Batch Gradient-Ascent-Based Localization for Indoor IoT Networks Under Rayleigh Fading Conditions

Location estimation in an indoor Internet-of-Things (IoT) environment is a challenging task due to multipath signals and obstacles that cause shadowing and fading effects, and change the received signal power considerably. Most of the existing path-loss-based localization methods assume only a lognormal shadowing model and ignore small scale fading effects. This article considers a generic combined lognormal shadowing and Rayleigh fading model for efficient localization of smart devices in an indoor IoT environment. In particular, the maximum likelihood estimate of the location and path-loss exponent (PLE), and Cramer-Rao lower bound (CRLB) are derived. The localization parameters are estimated using a novel adaptive mini-batch gradient ascent method that maximizes the log-likelihood function with an appropriate batch size based on the convergence factor. Hence, the proposed method addresses the challenge of an arbitrary selection of a fixed batch size for a gradient ascent method by utilizing this convergence factor. Performance evaluation by a simulation study and real experiments from an indoor IoT testbed provide a more accurate joint estimation of model parameters and smart device localization.

On NOMA-Based mmWave Communications

Non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) communication are two promising techniques to increase the system capacity in the fifth-generation (5G) mobile network. The former can achieve high spectral efficiency by modulating the information in power domain and the latter can provide extremely large spectrum resources. Fluctuating two-ray (FTR) channel model has already been proved to accurately agree with the small-scale fading effects in mmWave communications in experiments. In this paper, the performance of NOMA-based communications over FTR channels in mmWave communication systems is investigated in terms of outage probability (OP) and ergodic capacity (EC). Specifically, we consider the scenario that one base station (BS) transmits signals to two users simultaneously under NOMA scheme. The BS and users are all equipped with a single antenna. Two power allocation strategies are considered: the first one is a general (fixed) power allocation scheme under which we derive the OP and EC of NOMA users in closed form; the other one is an optimal power allocation scheme that can achieve the maximum sum rate for the whole system. Under the second scheme, not only the closed-form OP and EC but also the upper and lower bounds of EC are derived. Furthermore, we also derive the asymptotic expression for the OP in high average SNR region to investigate the diversity order under these two schemes. Finally, we show the correctness and accuracy of our derived expressions by Monte-Carlo simulation.

MmWave Lens-Based MIMO System for Suppressing Small-Scale Fading and Shadowing

In this paper, we propose a generalized millimeter-Wave (mmWave) reconfigurable antenna multiple-input multiple-output (RA-MIMO) architecture that takes advantage of lens antennas. The considered antennas can generate multiple independent beams simultaneously using a single RF chain. This property, together with RA-MIMO, is used to combat small-scale fading and shadowing in mmWave bands. To this end, first, we derive a channel matrix for RA-MIMO. Then, we use rate-one space-time block codes (STBCs), together with phase-shifters at the receive reconfigurable antennas, to suppress the effect of small-scale fading. We consider two kinds of phase shifters: i) ideal which is error-free and ii) digital which adds quantization error. The goal of phase-shifters is to convert a complex-valued channel matrix into real-valued. Hence, it is possible to use rate-one STBCs for any dimension of RA-MIMO. We investigate diversity gain and derive an upper bound for symbol error rate in cases of ideal and digital phase-shifters. We show that RA-MIMO achieves the full-diversity gain with ideal phase-shifters and the full-diversity gain for digital phase-shifters when the number of quantization bits is higher than one. We investigate RA-MIMO in the presence of shadowing. Our analysis demonstrates that, by increasing the dimension of RA-MIMO, the outage probability decreases which means the effect of shadowing decreases. Numerical results verify our theoretical derivations.

Indoor Large-Scale MIMO-Based RSSI Localization with Low-Complexity RFID Infrastructure.

Indoor localization based on unsynchronized, low-complexity, passive radio frequency identification (RFID) using the received signal strength indicator (RSSI) has a wide potential for a variety of internet of things (IoTs) applications due to their energy-harvesting capabilities and low complexity. However, conventional RSSI-based algorithms present inaccurate ranging, especially in indoor environments, mainly because of the multipath randomness effect. In this work, we propose RSSI-based localization with low-complexity, passive RFID infrastructure utilizing the potential benefits of large-scale MIMO technology operated in the millimeter-wave band, which offers channel hardening, in order to alleviate the effect of small-scale fading. Particularly, by investigating an indoor environment equipped with extremely simple dielectric resonator (DR) tags, we propose an efficient localization algorithm that enables a smart object equipped with large-scale MIMO exploiting the RSSI measurements obtained from the reference DR tags in order to improve the localization accuracy. In this context, we also derive Cramer–Rao lower bound of the proposed technique. Numerical results evidence the effectiveness of the proposed algorithms considering various arbitrary network topologies, and results are compared with an existing algorithm, where the proposed algorithms not only produce higher localization accuracy but also achieve a greater robustness against inaccuracies in channel modeling.

Measurements and Analysis of Propagation Channels in Vehicle-to-Infrastructure Scenarios

In this paper, we present measurements and analysis of propagation channels in vehicle-to-infrastructure (V2I) scenarios, which are the basis of designing vehicular communication systems. Firstly, we propose a deterministic geometry-based method to classify V2I links into three types, i.e., line-of-sight beneath (LOS-B), non-LOS (NLOS), and line-of-sight above (LOS-A), based on the environmental features, where roadside row of trees constitute the main obstacles. Secondly, for each link, we investigate the large-scale fading effect on V2I channels, including the path loss exponent and shadowing components. Subsequently, we validate the empirical path loss model using extensive measurements and two classical channel models. The results show a good fit with a near-zero mean and tolerable standard deviation of the estimation error. Finally, we analyze the small-scale fading effects, including fading depth and distance-dependent Ricean K -Factor, which are very important for accurately predicting the required fading margin and link budget. Through the analysis and simulations, this work provides a reference of the V2I channel characteristics for the test, design, and performance analysis of V2I communication systems.

Joint Resource Allocation and Computation Offloading With Time-Varying Fading Channel in Vehicular Edge Computing

Vehicular edge computing (VEC) is considered as a novel paradigm to enhance the safety of automated vehicles and intelligent transportation systems (ITS). The computation offloading strategies are the key point of VEC, and the effect of time-varying channels cannot be ignored during the task transmission period. This paper investigates the utility maximization problem with task delay requirement constraints, in which the influence of time-varying channel on the task offloading strategies during the task offloading period is considered. The time-varying fading channel leads to the time-varying spectrum efficiency (SE), so the previous offloading strategies are questionable when the additional uncertain allocated bandwidth is taken into account. To deal with it, we first propose a linearization based Branch and Bound (LBB) algorithm to solve the fixed SE problem without considering the time-varying channel characteristics. Considering the complexity of the LBB algorithm, a closest rounding integer (CRI) algorithm is proposed to solve the fixed SE problem. Then, based on the resource allocation strategies of the fixed SE problem, we propose the LBB based computation offloading (LBBCO) algorithm and the CRI based computation offloading (CRICO) algorithm to solve the original problem for both the static tasks and dynamic tasks. The proposed LBBCO/CRICO algorithms are also applicable to multi-vehicle and multi-task scenarios. Furthermore, we analyze the effect of small-scale fading on the proposed offloading strategies. The simulation results show that the average utilities of LBBCO and CRICO algorithms have a small gap by 3.93% and 6.13% only to the upper bound, respectively. Meanwhile, the proposed LBBCO and CRICO algorithms can outperform the previous state-of-the-art solution by 4.52% and 2.38%, respectively.

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

In the fifth-generation 5G mobile networks, it is expected that users experience high throughputs with an ultra-low-latency network, while a massive number of devices are connected to the network. However, in remote rural areas, there is still a large number of people that do not have access to broadband Internet. To overcome this issue, a possible strategy is to exploit the excellent propagation conditions of very high frequency (VHF) and ultra-high frequency (UHF) bands by allowing secondary spectrum reuse in the TV white space (TVWS) channels. But for that, a reliable channel model is required to perform valid coverage and data rate prediction studies. In this paper, a channel model is proposed that takes into account large and small scale fading effects, as well as the particularities of such remote rural areas. The proposed model makes use of measurements along with the clustered delay line CDL profiles from 3rd Generation Partnership Project (3GPP). It is a simple model to implement and can be used to provide fast link and system-level simulations. Numerical and analytical results are provided to validate the proposed model and a data rate evaluation is carried out for single-input single-output (SISO) and multipleinput multiple-output (MIMO) configurations, as well as for single-polarized (SP) and dual-polarized (DP) antennas.

Deep-Learning-Based Joint Resource Scheduling Algorithms for Hybrid MEC Networks

In this article, we consider a hybrid mobile edge computing (H-MEC) platform, which includes ground stations (GSs), ground vehicles (GVs), and unmanned aerial vehicles (UAVs), all with the mobile edge cloud installed to enable user equipments (UEs) or Internet of Things (IoT) devices with intensive computing tasks to offload. Our objective is to obtain an online offloading algorithm to minimize the energy consumption of all the UEs, by jointly optimizing the positions of GVs and UAVs, user association and resource allocation in real time, while considering the dynamic environment. To this end, we propose a hybrid deep-learning-based online offloading (H2O) framework where a large-scale path-loss fuzzy c-means (LS-FCM) algorithm is first proposed and used to predict the optimal positions of GVs and UAVs. Second, a fuzzy membership matrix U-based particle swarm optimization (U-PSO) algorithm is applied to solve the mixed-integer nonlinear programming (MINLP) problems and generate the sample data sets for the deep neural network (DNN) where the fuzzy membership matrix can capture the small-scale fading effects and the information of mutual interference. Third, a DNN with the scheduling layer is introduced to provide the user association and computing resource allocation under the practical latency requirement of the tasks and limited available computing resource of H-MEC. In addition, different from the traditional DNN predictor, we only input one UE’s information to the DNN at one time, which will be suitable for the scenarios where the number of UE is varying and avoid the curse of dimensionality in DNN.

Secrecy Analysis of Random MIMO Wireless Networks Over <inline-formula> <tex-math notation="LaTeX">$\alpha$</tex-math> </inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula> Fading Channels

In this paper, we investigate the secrecy performance of stochastic multiple-input multiple-output wireless networks over small-scale α-μ fading channels, where both the legitimate receivers and eavesdroppers are distributed with two independent homogeneous Poisson point processes. Specifically, accounting for the presence of non-colluding eavesdroppers, secrecy performance metrics, including the connection outage probability (COP), the probability of non-zero secrecy capacity (PNZ), and ergodic secrecy capacity, are derived regarding the k-th nearest/best user cases. The index for the k-th nearest user is extracted from the ordering, in terms of the distances between transmitters and receivers, whereas that for the k-th best user is based on the combined effects of path-loss and small-scale fading. In particular, the probability density functions and cumulative distribution functions of the composite channel gain for the k-th nearest and best user are characterized, respectively. Benefiting from these results, closed-form representations of the COP, PNZ, and ergodic secrecy capacity are subsequently obtained. Furthermore, a limit on the maximal number of the best-ordered users is also computed, for a given secrecy outage constraint. Finally, numerical results are provided to verify the correctness of our derivations. Additionally, the effects of fading parameters, path-loss exponent, and density ratios are also analyzed.

Performance of MRC receiver over Hoyt/lognormal composite fading channel

ABSTRACTIn this article, mixture gamma (MG) distribution is used for analysing the performance of L-Hoyt/lognormal composite fading channel. To overcome small-scale fading effect, micro-diversity using maximum ratio combining (MRC) is used at the receiver. Due to mathematical complexity, performance analysis of composite (L-Hoyt/lognormal) fading models is not present in closed form. The analytical expressions for the performance measure are derived in the form of received signal-to-noise ratio (SNR). The impact of system parameters on the energy detector (ED) performance is studied in terms of receiver operating characteristic (ROC) and area under the ROC curve (AUC). Further, the detection threshold parameter is optimised by minimising the total probability of error for L-Hoyt/lognormal channel. The accuracy of the proposed closed-form expressions is validated by comparing all the results with the Monte-Carlo/exact simulations.

Iterative Search Algorithm to Maximize System Capacity in Time-Varying MIMO DAS

In this paper, an iterative search algorithm to maximize system capacity in a time-varying MIMO distributed antenna system (DAS) is proposed. A common DAS model is employed, in which the transmit antennas are distributively located and the receiver can move arbitrarily in the region. Due to the small-scale fading effect and the receiver movement, the transmitters and receiver cannot obtain accurate channel state information (CSI) or optimize the system capacity. Therefore, we present a time-varying MIMO DAS model and corresponding channel evolution model to predict the time-varying channel. With the channel evolution model, the proposed iterative search algorithm can calculate the precoding matrix, and an iterative search process is employed to determine the optimal precoding matrix from a precoding matrix set. Meanwhile, error analysis show the error on the instantaneous mutual information with the proposed algorithm has a close relationship with the element number of the precoding matrix set and small-scale fading evolution coefficient. We also propose a non-uniform power allocation strategy which can improve the system capacity. Simulation results are presented to verity the analysis above and demonstrate the performance of system capacity with the proposed iterative search algorithm.

An empirical analysis of the radio propagation characteristics in high-speed railway environment

For a wireless mobile network, a profile of radio propagation characteristics is the key to study any wireless techniques, especially in High-Speed Railway (HSR) environment. Unfortunately, such a profile is not available so far, which leads manifold challenges to wireless study for HSR scenarios. In this paper, we focus on this topic, and try to obtain this profile in various kinds of HSR scenarios based on previous field tests in China. Our study reveals that the Line-Of-Sight (LOS) propagation path plays a predominant role in the HSR scenarios, which can suppress the shadow fading. Finally, we find out that each kind of small-scale fading effects has a unique profile on different wireless mobile systems for HSR scenarios. As a result, this study presents a theoretical guidance for studying any wireless techniques in HSR environment, e.g., cell handover for HSR.

Upper Bound on Uplink Sum Rate for Multi-Cell Massive MU-MIMO Systems With ZF Receivers

In this letter, uplink sum rate for multi-cell massive multi-user multiple-input multiple-output (MU-MIMO) systems with zero-forcing receivers is analyzed. To be practical, imperfect channel state information obtained through uplink training is assumed, and both large scale path loss and small scale fading effects are considered. A tight upper bound on sum rate is derived in closed form, which is applicable to MU-MIMO systems with any number of receiving antennas. The tightness of the upper bound is theoretically proved for massive MU-MIMO systems and is further demonstrated by computer simulations. The result thus enables a better understanding of multi-cell massive MU-MIMO systems and facilitates system design in practice.