Resource allocation for 5G technologies under statistical queueing constraints

As the launch of fifth generation (5G) wireless networks is approaching, recent years have witnessed comprehensive discussions about a possible 5G standard. Many transmission scenarios and technologies have been proposed and initial over-the-air experimental trials have been conducted. Most of the existing literature studies on 5G technologies have mainly focused on the physical layer parameters and quality of service (QoS) requirements, e.g., achievable data rates. However, the demand for delay-sensitive data traffic over wireless networks has increased exponentially in the recent years, and is expected to further increase by the time of 5G. Therefore, other constraints at the data-link layer concerning the buffer overflow and delay violation probabilities should also be regarded. It follows that evaluating the performance of the 5G technologies when such constraints are considered is a timely task. Motivated by this fact, in this thesis we explore the performance of three promising 5G technologies when operating under certain QoS at the data-link layer. We follow a cross-layer approach to examine the interplay between the physical and data-link layers when statistical QoS constraints are inflicted in the form of limits on the delay violation and buffer overflow probabilities. Noting that wireless systems, generally, have limited physical resources, in this thesis we mainly target designing adaptive resource allocation schemes to maximize the system performance under such QoS constraints. We initially investigate the throughput and energy efficiency of a general class of multiple-input multiple-output (MIMO) systems with arbitrary inputs. As a cross-layer evaluation tool, we employ the effective capacity as the main performance metric, which is the maximum constant data arrival rate at a buffer that can be sustained by the channel service process under specified QoS constraints. We obtain the optimal input covariance matrix that maximizes the effective capacity under a short-term average power budget. Then, we perform an asymptotic analysis of the effective capacity in the low signal-to-noise ratio and large-scale antenna (massive MIMO) regimes. Such analysis has a practical importance for 5G scenarios that necessitate low latency, low power consumption, and/or ability to simultaneously support massive number of users. Non-orthogonal multiple access (NOMA) has attracted significant attention in the recent years as a promising multiple access technology for 5G. In this thesis, we consider a two-user power-domain NOMA scheme in which both transmitters employ superposition coding and the receiver applies successive interference cancellation (SIC) with a certain order. For practical concerns, we consider limited transmission power budgets at the transmitters, and assume that both transmitters have arbitrarily distributed input signals. We again exploit the effective capacity as the main cross-layer performance measure. We provide a resource management scheme that can jointly obtain the optimal power allocation policies at the transmitters and the optimal decoding order at the receiver, with the goal of maximizing the effective capacity region that provides the maximum allowable sustainable arrival rate region at the transmitters' buffers under QoS guarantees. In the recent years, visible light communication (VLC) has emerged as a potential transmission technology that can utilize the visible light spectrum for data transmission along with illumination. Different from the existing literature studies on VLC, in this thesis we consider a VLC system in which the access point (AP) is unaware of the channel conditions, thus the AP sends the data at a fixed rate. Under this assumption, and considering an ON-OFF data source, we provide a cross-layer study when the system is subject to statistical buffering constraints. To this end, we employ the maximum average data arrival rate at the AP buffer and the non-asymptotic bounds on buffering delay as the main performance measures. To facilitate our analysis, we adopt a two-state Markov process to model the fixed-rate transmission strategy, and we then formulate the steady-state probabilities of the channel being in the ON and OFF states. The coexistence of radio frequency (RF) and VLC systems in typical indoor environments can be leveraged to support vast user QoS needs. In this thesis, we examine the benefits of employing both technologies when operating under statistical buffering limitations. Particularly, we consider a multi-mechanism scenario that utilizes RF and VLC links for data transmission in an indoor environment. As the transmission technology is the main physical resource to be concerned in this part, we propose a link selection process through which the transmitter sends data over the link that sustains the desired QoS guarantees the most. Considering an ON-OFF data source, we employ the maximum average data arrival rate at the transmitter buffer and the non-asymptotic bounds on data buffering delay as the main performance measures. We formulate the performance measures under the assumption that both links are subject to average and peak power constraints

Effective Capacity in Cognitive Radio Broadcast Channels

In this paper, we investigate effective capacity by modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations. We initially describe three different cooperative channel sensing strategies with different hard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist possibly four different transmission scenarios. We provide the instantaneous ergodic capacities of the channel between the ST and each SR in all of these scenarios. Granting that transmission outage arises when the instantaneous transmission rate is greater than the instantaneous ergodic capacity, we establish two different transmission rate policies for the SUs when the channel is sensed as idle. One of these policies features a greedy approach disregarding a possible transmission outage, and the other favors a precautious manner to prevent this outage. Subsequently, we determine the effective capacity region of this channel model, and we attain the power allocation policies that maximize this region. Finally, we present the numerical results. We first show the superiority of Majority rule when the channel sensing results are good. Then, we illustrate that a greedy transmission rate approach is more beneficial for the SUs under strict interference power constraints, whereas sending with lower rates will be more advantageous under loose interference constraints.Comment: Submitted and Accepted to IEEE Globecom 201

Effective Capacity in Multiple Access Channels with Arbitrary Inputs

In this paper, we consider a two-user multiple access fading channel under quality-of-service (QoS) constraints. We initially formulate the transmission rates for both transmitters, where the transmitters have arbitrarily distributed input signals. We assume that the receiver performs successive decoding with a certain order. Then, we establish the effective capacity region that provides the maximum allowable sustainable arrival rate region at the transmitters' buffers under QoS guarantees. Assuming limited transmission power budgets at the transmitters, we attain the power allocation policies that maximize the effective capacity region. As for the decoding order at the receiver, we characterize the optimal decoding order regions in the plane of channel fading parameters for given power allocation policies. In order to accomplish the aforementioned objectives, we make use of the relationship between the minimum mean square error and the first derivative of the mutual information with respect to the power allocation policies. Through numerical results, we display the impact of input signal distributions on the effective capacity region performance of this two-user multiple access fading channel

Performance Analysis of Energy-Detection-Based Massive SIMO

Recently, communications systems that are both energy efficient and reliable are under investigation. In this paper, we concentrate on an energy-detection-based transmission scheme where a communication scenario between a transmitter with one antenna and a receiver with significantly many antennas is considered. We assume that the receiver initially calculates the average energy across all antennas, and then decodes the transmitted data by exploiting the average energy level. Then, we calculate the average symbol error probability by means of a maximum a-posteriori probability detector at the receiver. Following that, we provide the optimal decision regions. Furthermore, we develop an iterative algorithm that reaches the optimal constellation diagram under a given average transmit power constraint. Through numerical analysis, we explore the system performance

Design of a Cognitive VLC Network with Illumination and Handover Requirements

In this paper, we consider a cognitive indoor visible light communications (VLC) system, comprised of multiple access points serving primary and secondary users through the orthogonal frequency division multiple access method. A cognitive lighting cell is divided into two non-overlapping regions that distinguish the primary and secondary users based on the region they are located in. Under the assumption of equal-power allocation among subcarriers, each region is defined in terms of its physical area and the number of allocated subcarriers within that region. In this paper, we provide the lighting cell design with cognitive constraints that guarantee fulfilling certain illumination, user mobility, and handover requirements in each cell. We further argue that, under some conditions, a careful assignment of the subcarriers in each region can mitigate the co-channel interference in the overlapping areas of adjacent cells. Numerical results depict the influence of different system parameters, such as user density, on defining both regions. Finally, a realistic example is implemented to assess the performance of the proposed scheme via Monte Carlo simulations

Fotografía DE MUJER CON TRAJE LLENO DE ABALORIOS [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

A VLC-based Footprinting Localization Algorithm for Internet of Underwater Things in 6G networks

International audienceIn the upcoming advent of 6G networks, underwater communications are expected to play a relevant role in the context of overlapping hybrid wireless networks, following a multilayer architecture i.e., aerial-ground-underwater. The concept of Internet of Underwater Things defines different communication and networking technologies, as well as positioning and tracking services, suitable for harsh underwater scenarios. In this paper, we present a footprinting localization algorithm based on optical wireless signals in the visible range. The proposed technique is based on a hybrid Radio Frequency (RF) and Visible Light Communication (VLC) network architecture, where a central RF sensor node holds an environment channel gain map i.e., database, that is exploited for localization estimation computation. A recursive localization algorithm allows to estimate user positions with centimeter-based accuracy, in case of different turbidity scenarios

On the Noise Effect of Fingerprinting-Based Positioning Error in Underwater Visible Light Networks

This paper assesses the performance of a localization technique for underwater visible light networks. The proposed approach is based on a fingerprinting technique, collecting the channel impulse responses from different wireless optical signals in the visible range. A local database related to the power level distribution within a maritime environment is built and exploited to estimate user position, e.g., a diver moving in a given space for underwater fish monitoring. In this paper, we investigate on the noise effect on the localization accuracy in underwater scenarios and for different water turbidity coefficient and we demonstrate that the estimation error suffers on variable channel impulse responses. Different configuration parameters and environmental scenarios have been considered, showing that the LED transmitter deployment can be effective in the localization estimation. A comparison of the proposed localization approach to the traditional triangulation method has been finally carried out, showing the effectiveness of the fingerprinting-based solution for a lower number of LED transmitters