25 research outputs found
Impact of Pointing Errors on the Performance of Mixed RF/FSO Dual-Hop Transmission Systems
In this work, the performance analysis of a dual-hop relay transmission
system composed of asymmetric radio-frequency (RF)/free-space optical (FSO)
links with pointing errors is presented. More specifically, we build on the
system model presented in [1] to derive new exact closed-form expressions for
the cumulative distribution function, probability density function, moment
generating function, and moments of the end-to-end signal-to-noise ratio in
terms of the Meijer's G function. We then capitalize on these results to offer
new exact closed-form expressions for the higher-order amount of fading,
average error rate for binary and M-ary modulation schemes, and the ergodic
capacity, all in terms of Meijer's G functions. Our new analytical results were
also verified via computer-based Monte-Carlo simulation results.Comment: 6 pages, 3 figure
Heavy Traffic Asymptotic Approach for Video Streaming over Small Cell Networks with Imperfect State Information
International audienceIn this work, we address the problem of decentralized power allocation for satisfying individual QoS constraints in video streaming in a Small Cells Network.They QoS metric we use here is the probability that the queue length at each transmitter exceeds some threshold: we want this probability to be fixed at a desired value. We focus on a model with interfering transmitter-receiver pairs. Using heavy traffic asymptotic modelling we propose a power control algorithm for the case where each base station has access to local SINR feedback, information about the queue length of its user and delayed information of the queues in the other base stations. Simulation results suggest that the proposed algorithm is quite robust in the case of delayed information sharing
Pareto Boundary of the Rate Region for Single-Stream MIMO Interference Channels: Linear Transceiver Design
We consider a multiple-input multiple-output (MIMO) interference channel
(IC), where a single data stream per user is transmitted and each receiver
treats interference as noise. The paper focuses on the open problem of
computing the outermost boundary (so-called Pareto boundary-PB) of the
achievable rate region under linear transceiver design. The Pareto boundary
consists of the strict PB and non-strict PB. For the two user case, we compute
the non-strict PB and the two ending points of the strict PB exactly. For the
strict PB, we formulate the problem to maximize one rate while the other rate
is fixed such that a strict PB point is reached. To solve this non-convex
optimization problem which results from the hard-coupled two transmit
beamformers, we propose an alternating optimization algorithm. Furthermore, we
extend the algorithm to the multi-user scenario and show convergence. Numerical
simulations illustrate that the proposed algorithm computes a sequence of
well-distributed operating points that serve as a reasonable and complete inner
bound of the strict PB compared with existing methods.Comment: 16 pages, 9 figures. Accepted for publication in IEEE Tans. Signal
Process. June. 201
A Formulation of the Log-Logistic Distribution for Fading Channel Modeling
In some scenarios, the log-logistic (LL) distribution is shown to provide the best fit to field
measurements in the context of wireless channel modeling. However, a fading channel model based
on the LL distribution has not been formulated yet. In this work, we introduce the L-distribution
as a reformulation of the LL distribution for channel modeling purposes. We provide closed-form
expressions for its PDF, CDF, and moments. Performance analysis of wireless communication systems
operating under L-fading channels is exemplified, providing exact and asymptotic expressions for
relevant metrics such as the outage probability and the average capacity. Finally, important practical
aspects related to the use of the L-distribution for channel fitting purposes are discussed in two
contexts: (i) millimeter-wave links with misaligned gain, and (ii) air–ground channels in unmanned
aerial vehicle communications.European Social and Regional FundsJunta de Andalucia P18-RT-3175
UMA20-FEDERJA-002Universidad de MalagaUniversidad de Granad
On the Sum of Order Statistics and Applications to Wireless Communication Systems Performances
We consider the problem of evaluating the cumulative distribution function
(CDF) of the sum of order statistics, which serves to compute outage
probability (OP) values at the output of generalized selection combining
receivers. Generally, closed-form expressions of the CDF of the sum of order
statistics are unavailable for many practical distributions. Moreover, the
naive Monte Carlo (MC) method requires a substantial computational effort when
the probability of interest is sufficiently small. In the region of small OP
values, we propose instead two effective variance reduction techniques that
yield a reliable estimate of the CDF with small computing cost. The first
estimator, which can be viewed as an importance sampling estimator, has bounded
relative error under a certain assumption that is shown to hold for most of the
challenging distributions. An improvement of this estimator is then proposed
for the Pareto and the Weibull cases. The second is a conditional MC estimator
that achieves the bounded relative error property for the Generalized Gamma
case and the logarithmic efficiency in the Log-normal case. Finally, the
efficiency of these estimators is compared via various numerical experiments
Homotopy continuation for spatial interference alignment in arbitrary MIMO X networks
In this paper, we propose an algorithm to design interference alignment (IA) precoding and decoding matrices for arbitrary MIMO X networks. The proposed algorithm is rooted in the homotopy continuation techniques commonly used to solve systems of nonlinear equations. Homotopy methods find the solution of a target system by smoothly deforming the solution of a start system which can be trivially solved. Unlike previously proposed IA algorithms, the homotopy continuation technique allows us to solve the IA problem for both unstructured (i.e., generic) and structured channels such as those that arise when time or frequency symbol extensions are jointly employed with the spatial dimension. To this end, we consider an extended system of bilinear equations that include the standard alignment equations to cancel the interference, and a new set of bilinear equations that preserve the desired dimensionality of the signal spaces at the intended receivers. We propose a simple method to obtain the start system by randomly choosing a set of precoders and decoders, and then finding a set of channels satisfying the system equations, which is a linear problem. Once the start system is available, standard prediction and correction techniques are applied to track the solution all the way to the target system. We analyze the convergence of the proposed algorithm and prove that, for many feasible systems and a sufficiently small continuation parameter, the algorithm converges with probability one to a perfect IA solution. The simulation results show that the proposed algorithm is able to consistently find solutions achieving the maximum number of degrees of freedom in a variety of MIMO X networks with or without symbol extensions. Further, the algorithm provides insights into the feasibility of IA in MIMO X networks for which theoretical results are scarce.This work has been supported by the Ministerio de Economía y Competitividad (MINECO) of Spain, under grants TEC2013-47141-C4-R (RACHEL), TEC2016-75067-C4-4-R (CARMEN), MTM2014-57590-P, and FPI grant BES-2014-069786
On the use of composite indicators for mobile communications network management in smart sustainable cities
Beyond 5G networks will be fundamental towards enabling sustainable mobile communication networks. One of the most challenging scenarios will be met in ultra-dense networks that are deployed in densely populated areas. In this particular case, mobile network operators should benefit from new assessment metrics and data science tools to ensure an effective management of their networks. In fact, incorporating architectures allowing a cognitive network management framework could simplify processes and enhance the network's performance. In this paper, we propose the use of composite indicators based on key performance indicators both as a tool for a cognitive management of mobile communications networks, as well as a metric which could successfully integrate more advanced user-centric measurements. Composite indicators can successfully synthesize and integrate large amounts of data, incorporating in a single index different metrics selected as triggers for autonomous decisions. The paper motivates and describes the use of this methodology, which is applied successfully in other areas with the aim of ranking metrics to simplify complex realities. A use case that is based on a universal mobile telecommunications system network is analyzed, due to technology simplicity and scalability, as well as the availability of key performance indicators. The use case focuses on analyzing the fairness of a network over different coverage areas as a fundamental metric in the operation and management of the networks. To this end, several ranking and visualization strategies are presented, providing examples of how to extract insights from the proposed composite indicator