Large-scale Fading Parameters Research Articles

Measurement-Based Analysis on Vehicle-to-Vehicle Connectivity in Tunnel Environment

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity.

Learning-Based Downlink Power Allocation in Cell-Free Massive MIMO Systems

This paper considers a cell-free massive multiple-input multiple-output (MIMO) system that consists of a large number of geographically distributed access points (APs) serving multiple users via coherent joint transmission. The downlink performance of the system is evaluated, with maximum ratio and regularized zero-forcing precoding, under two optimization objectives for power allocation: sum spectral efficiency (SE) maximization and proportional fairness. We present iterative centralized algorithms for solving these problems. Aiming at a less computationally complex and also distributed scalable solution, we train a deep neural network (DNN) to approximate the same network-wide power allocation. Instead of training our DNN to mimic the actual optimization procedure, we use a heuristic power allocation, based on large-scale fading (LSF) parameters, as the pre-processed input to the DNN. We train the DNN to refine the heuristic scheme, thereby providing higher SE, using only local information at each AP. Another distributed DNN that exploits side information assumed to be available at the central processing unit is designed for improved performance. Further, we develop a clustered DNN model where the LSF parameters of a small number of APs, forming a cluster within a relatively large network, are used to jointly approximate the power coefficients of the cluster.

Analysis of Quantized MRC-MRT Precoder For FDD Massive MIMO Two-Way AF Relaying

The maturing massive multiple-input multiple-output (MIMO) literature has provided asymptotic limits for the rate and energy efficiency (EE) of maximal ratio combining/ maximal ratio transmission (MRC-MRT) relaying on two-way relays (TWRs) using the amplify-and-forward (AF) principle. Most of these studies consider time-division duplexing and a fixed number of users. To fill the gap in the literature, we analyze the MRC-MRT precoder performance of an N-antenna AF massive MIMO TWR, which operates in a frequency-division duplex mode to enable two-way communication between 2M = [N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">α</sup> ] single-antenna users, with α ∈ [0, 1), divided equally into two groups of M users. We assume that the relay has realistic imperfect uplink channel state information (CSI), and that quantized downlink CSI is fed back by the users relying on B ≥ 1 bits per-user per relay antenna. We prove that for such a system with α ∈ [0, 1), the MRC-MRT precoder asymptotically cancels the multi-user interference (MUI) when the supremum and infimum of large-scale fading parameters are strictly nonzero and finite, respectively. Furthermore, its per-user pairwise error probability converges to that of an equivalent AWGN channel, as both N and the number of users 2M = [N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">α</sup> ] tend to infinity, with a relay power scaling of P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> = (2ME <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> /N) and E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> being a constant. We also derive upper bounds for both the per-user rate and EE. We analytically show that the quantized MRC-MRT precoder requires as few as B = 2 bits to yield a BER, EE, and per-user rate close to the respective unquantized counterparts. Finally, we show that the analysis developed herein to derive a bound on α for MUI cancellation is applicable both to Gaussian as well as to any arbitrary non-Gaussian complex channels.

On the Ergodic Capacity of Distributed MIMO Antenna Systems

We consider distributed multiple-input---multiple-output (MIMO) antenna systems, along with their certain generalizations. We show that distributed MIMO configuration can be mapped to a semicorrelated (one side correlated) Wishart model. For a given set of large-scale fading parameters, associated with the path loss and shadow fading, we derive exact and closed-form results for the marginal density of eigenvalues of $$\mathbf{H}^\dag \mathbf{H}$$H?H (or $$\mathbf{H} \mathbf{H} ^\dag$$HH?), where $$\mathbf{H}$$H is the channel matrix. We also obtain exact and closed-form expressions for the ergodic channel capacity with the aid of Meijer G-function. The ergodic capacity of semicorrelated Rayleigh fading channel follows as a special case. All analytical results are validated by comparison with Monte-Carlo simulations.

Spectral efficiency analysis for downlink massive MIMO systems with MRT precoding

As an important part of the channel fading, large scale fading should be considered in downlink massive multiple-input multiple-output (MIMO) systems. This paper investigates the downlink massive MIMO system over a large scale fading channel, when the base station takes advantage of maximum-radio transmission (MRT) precoding. The cases when the base station has perfect and imperfect channel state information (CSI) are considered respectively. Specially, through the analysis of single user's ergodic achievable rate, some novel and approximate expressions for the spectral efficiency (SE) are derived. Based on the approximate SE, the effect of the channel estimation error is analyzed intuitively. In addition, the average SE of all the users with different large-scale fading parameters is carefully investigated. Simulations validate that all the theoretical results coincide with numerical results and the large scale fading factors have little influence on SE reduction resulted from channel estimation.

Measurements and Analysis of Large-Scale Fading Characteristics in Curved Subway Tunnels at 920 MHz, 2400 MHz, and 5705 MHz

Wave propagation characteristics in curved tunnels are of importance for designing reliable communications in subway systems. This paper presents the extensive propagation measurements conducted in two typical types of subway tunnels—traditional arched “Type I” tunnel and modern arched “Type II” tunnel—with 300- and 500-m radii of curvature with different configurations—horizontal and vertical polarizations at 920, 2400, and 5705 MHz, respectively. Based on the measurements, statistical metrics of propagation loss and shadow fading (path-loss exponent, shadow fading distribution, autocorrelation, and crosscorrelation) in all the measurement cases are extracted. Then, the large-scale fading characteristics in the curved subway tunnels are compared with the cases of road and railway tunnels, the other main rail traffic scenarios, and some “typical” scenarios to give a comprehensive insight into the propagation in various scenarios where the intelligent transportation systems are deployed. Moreover, for each of the large-scale fading parameters, extensive analysis and discussions are made to reflect the physical laws behind the observations. The quantitative results and findings are useful to realize intelligent transportation systems in the subway system.

A NOVEL MGF BASED ANALYSIS OF CHANNEL CAPACITY OF GENERALIZED-K FADING WITH MAXIMAL-RATIO COMBINING DIVERSITY

In this paper, we have analyzed the channel capacity by using the maximal-ratio combing (MRC) diversity scheme for communication systems operating over a composite fading environment modeled by the Generalized-K distribution at the receiver. For the Generalized-K fading channel with arbitrary values for small and large scale fading parameters, we have derived a closed-form expression for the moment generating function (MGF) of the received signal-to-noise ratio (SNR) and utilized it to obtain a novel closed-form expressions for the channel capacity under difierent adaptive transmission schemes. The result of the proposed methods is compared with other reported literature to support the analysis.