136 research outputs found
Adaptive Resource Allocation for Statistical QoS Provisioning in Mobile Wireless Communications and Networks
Due to the highly-varying wireless channels over time, frequency, and space
domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has
become a recognized feature in the next-generation wireless networks. In this dissertation,
we study the adaptive wireless resource allocation problems for statistical QoS
provisioning, such as guaranteeing the specified delay-bound violation probability,
upper-bounding the average loss-rate, optimizing the average goodput/throughput,
etc., in several typical types of mobile wireless networks.
In the first part of this dissertation, we study the statistical QoS provisioning for
mobile multicast through the adaptive resource allocations, where different multicast
receivers attempt to receive the common messages from a single base-station sender
over broadcast fading channels. Because of the heterogeneous fading across different
multicast receivers, both instantaneously and statistically, how to design the efficient
adaptive rate control and resource allocation for wireless multicast is a widely cited
open problem. We first study the time-sharing based goodput-optimization problem
for non-realtime multicast services. Then, to more comprehensively characterize the
QoS provisioning problems for mobile multicast with diverse QoS requirements, we
further integrate the statistical delay-QoS control techniques — effective capacity
theory, statistical loss-rate control, and information theory to propose a QoS-driven
optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS
requirements, sustainable traffic load, and the average loss rate through the adaptive
resource allocations and queue management. Furthermore, we study the adaptive
resource allocation problems for multi-layer video multicast to satisfy diverse statistical
delay and loss QoS requirements over different video layers. In addition,
we derive the efficient adaptive erasure-correction coding scheme for the packet-level
multicast, where the erasure-correction code is dynamically constructed based on multicast
receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile
multicast networks.
In the second part of this dissertation, we design the adaptive resource allocation
schemes for QoS provisioning in unicast based wireless networks, with emphasis
on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and
power allocation schemes for multi-user downlink transmissions (with independent
messages) in cellular networks to maximize the delay-QoS-constrained sum system
throughput. Second, we propose the delay-QoS-aware base-station selection schemes
in distributed multiple-input-multiple-output systems. Third, we study the queueaware
spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning.
Analyses and simulations are presented to show the advantages of our proposed
schemes and the impact of delay-QoS requirements on adaptive resource allocations
in various environments
Theories and Models for Internet Quality of Service
We survey recent advances in theories and models for Internet Quality of Service (QoS). We start with the theory of network calculus, which lays the foundation for support of deterministic performance guarantees in networks, and illustrate its applications to integrated services, differentiated services, and streaming media playback delays. We also present mechanisms and architecture for scalable support of guaranteed services in the Internet, based on the concept of a stateless core. Methods for scalable control operations are also briefly discussed. We then turn our attention to statistical performance guarantees, and describe several new probabilistic results that can be used for a statistical dimensioning of differentiated services. Lastly, we review recent proposals and results in supporting performance guarantees in a best effort context. These include models for elastic throughput guarantees based on TCP performance modeling, techniques for some quality of service differentiation without access control, and methods that allow an application to control the performance it receives, in the absence of network support
Algorithm design for scheduling and medium access control in heterogeneous mobile networks
MenciĂłn Internacional en el tĂtulo de doctorThe rapid growth of wireless mobile devices has led to saturation and congestion of wireless channels – a well-known fact. In the recent years, this issue is further exacerbated by the ever-increasing demand for traffic intensed multimedia content applications, which include but are not limited to social media, news and video streaming applications. Therefore the development of highly efficient content distribution technologies is of utmost importance, specifically to cope with the scarcity and the high cost of wireless resources. To this aim, this thesis investigates the challenges and the considerations required to design efficient techniques to improve the performance of wireless networks. Since wireless signals are prone to fluctuations and mobile users are, with high likelihood, have difference channel qualities, we particularly focus on the scenarios with heterogeneous user distribution. Further, this dissertation considers two main techniques to cope with mobile users demand and the limitation of wireless resources. Firstly, we propose an opportunistic multicast scheduling to efficiently distribute or disseminate data to all users with low delay. Secondly, we exploit the Millimeter-Wave (mm-Wave) frequency band that has a high potential of meeting the high bandwidth demand. In particular, we propose a channel access mechanism and a scheduling algorithm that take into account the limitation of the high frequency band (i.e., high path loss).
Multicast scheduling has emerged as one of the most promising techniques for multicast applications when multiple users require the same content from the base station. Unlike a unicast scheduler which sequentially serves the individual users, a multicast scheduler efficiently utilizes the wireless resources by simultaneously transmitting to multiple users. Precisely, it multiplies the gain in terms of the system throughput compared to unicast transmissions. In spite of the fact that multicast schedulers are more efficient than unicast schedulers, scheduling for multicast transmission is a challenging task. In particular, base station can only chose one rate to transmit to all users. While determining the rate for users with a similar instantaneous channel quality is straight forward, it is non-trivial when users have different instantaneous channel qualities, i.e., when the channel is heterogeneous. In such a scenario, on one hand, transmitting at a low rate results in low throughput. On the other hand, transmitting at a high rate causes some users to fail to receive the transmitted packet while others successfully receive it but with a rate lower than their maximum rate. The most common and simplest multicasting technique, i.e., broadcasting, transmits to all receivers using the maximum rate that is supported by the worst receiver.
In recent years, opportunistic schedulers have been considered for multicasting. Opportunistic multicast schedulers maximize instantaneous throughput and transmit at a higher rate to serve only a subset of the multicast users. While broadcasting suffers from high delay for all users due to low transmission rate, the latter causes a long delay for the users with worse channel quality as they always favor users with better channel quality. To address these problems, we designed an opportunistic multicast scheduling mechanism that aims to achieve high throughput as well as low delay. Precisely, we are solving the finite horizon problem for multicasting. Our goal is that all multicast users receive the same amount of data within the shortest amount of time.
Although our proposed opportunistic multicast scheduling mechanism improves the system throughput and reduces delay, a common problem in multicast scheduling is that its throughput performance is limited by the worst user in the system. To overcome this problem, transmit beamforming can be used to adjust antenna gains to the different receivers. This allows improving the SNR of the receiver with the worst channel SNR at the expense of worsening the SNR of the better channel receivers. In the first part of this thesis, two different versions of the finite horizon problem are considered: (i) opportunistic multicast scheduling and (ii) opportunistic multicast beamforming.
In recent years, many researchers venture into the potential of communication over mm-Wave band as it potentially solves the existing network capacity problem. Since beamforming is capable to concentrate the transmit energy in the direction of interest, this technique is particularly beneficial to improve signal quality of the highly attenuated mm-Wave signal. Although directional beamforming in mm-Wave offers multi-gigabit-per-second data rates, directional communication severely deteriorates the channel sensing capability of a user. For instance, when a user is not within the transmission coverage or range of the communicating users, it is unable to identify the state of the channel (i.e., busy or free). As a result, this leads to a problem commonly known as the deafness problem. This calls for rethinking of the legacy medium access control and scheduling mechanisms for mm-Wave communication. Further, without omni-directional transmission, disseminating or broadcasting global information also becomes complex. To cope with these issues, we propose two techniques in the second part of this thesis. First, leveraging that recent mobile devices have multiple wireless interface, we present a dual-band solution. This solution exploits the omni-directional capable lower frequency bands (i.e., 2.4 and 5 GHz) to transmit control messages and the mm-Wave band for high speed data transmission. Second, we develop a decentralized scheduling technique which copes with the deafness problem in mm-Wave through a learning mechanism.
In a nutshell, this thesis explores solutions which (i) improve the utilization of the network resources through multicasting and (ii) meet the mobile user demand with the abundant channel resources available at high frequency bands.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en IngenierĂa TelemáticaPresidente: Ralf Steinmetz.- Secretario: Carlos JesĂşs Bernardos Cano.- Vocal: Jordi Domingo Pascua
Advances in Internet Quality of Service
We describe recent advances in theories and architecture that support performance guarantees needed for quality of service networks. We start with deterministic computations and give applications to integrated services, differentiated services, and playback delays. We review the methods used for obtaining a scalable integrated services support, based on the concept of a stateless core. New probabilistic results that can be used for a statistical dimensioning of differentiated services are explained; some are based on classical queuing theory, while others capitalize on the deterministic results. Then we discuss performance guarantees in a best effort context; we review: methods to provide some quality of service in a pure best effort environment; methods to provide some quality of service differentiation without access control, and methods that allow an application to control the performance it receives, in the absence of network support
Framework for Content Distribution over Wireless LANs
Wireless LAN (also called as Wi-Fi) is dominantly considered as the most pervasive
technology for Intent access. Due to the low-cost of chipsets and support for high data
rates, Wi-Fi has become a universal solution for ever-increasing application space
which includes, video streaming, content delivery, emergency communication,
vehicular communication and Internet-of-Things (IoT).
Wireless LAN technology is defined by the IEEE 802.11 standard. The 802.11
standard has been amended several times over the last two decades, to incorporate the
requirement of future applications. The 802.11 based Wi-Fi networks are
infrastructure networks in which devices communicate through an access point.
However, in 2010, Wi-Fi Alliance has released a specification to standardize direct
communication in Wi-Fi networks. The technology is called Wi-Fi Direct. Wi-Fi
Direct after 9 years of its release is still used for very basic services (connectivity, file
transfer etc.), despite the potential to support a wide range of applications. The reason
behind the limited inception of Wi-Fi Direct is some inherent shortcomings that limit
its performance in dense networks. These include the issues related to topology
design, such as non-optimal group formation, Group Owner selection problem,
clustering in dense networks and coping with device mobility in dynamic networks. Furthermore, Wi-Fi networks also face challenges to meet the growing number of Wi
Fi users. The next generation of Wi-Fi networks is characterized as ultra-dense
networks where the topology changes frequently which directly affects the network
performance. The dynamic nature of such networks challenges the operators to design
and make optimum planifications.
In this dissertation, we propose solutions to the aforementioned problems. We
contributed to the existing Wi-Fi Direct technology by enhancing the group formation
process. The proposed group formation scheme is backwards-compatible and
incorporates role selection based on the device's capabilities to improve network
performance. Optimum clustering scheme using mixed integer programming is
proposed to design efficient topologies in fixed dense networks, which improves
network throughput and reduces packet loss ratio. A novel architecture using
Unmanned Aeriel Vehicles (UAVs) in Wi-Fi Direct networks is proposed for
dynamic networks. In ultra-dense, highly dynamic topologies, we propose cognitive
networks using machine-learning algorithms to predict the network changes ahead of
time and self-configuring the network
Recommended from our members
Integrated cellular and device-to-device networks
textDevice-to-device (D2D) networking enables direct discovery and communication between cellular subscribers that are in proximity, thus bypassing the base stations (BSs). In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled broadband communication technology is also required by public safety networks that must function when cellular networks are not available. Integrating D2D into cellular networks, however, poses many challenges and risks to the long-standing cellular architecture, which is centered around the BSs. This dissertation identifies outstanding technical challenges in D2D-enabled cellular networks and addresses them with novel models and fundamental analysis. First, this dissertation develops a baseline hybrid network model consisting of both ad hoc nodes and cellular infrastructure. This model uses Poisson point processes to model the random and unpredictable locations of mobile users. It also captures key features of multicast D2D including multicast receiver heterogeneity and retransmissions while being tractable for analytical purpose. Several important multicast D2D metrics including coverage probability, mean number of covered receivers per multicast session, and multicast throughput are analytically characterized under the proposed model. Second, D2D mode selection which means that a potential D2D pair can switch between direct and cellular modes is incorporated into the hybrid network model. The extended model is applied to study spectrum sharing between cellular and D2D communications. Two spectrum sharing models, overlay and underlay, are investigated under a unified analytical framework. Analytical rate expressions are derived and applied to optimize the design of spectrum sharing. It is found that, from an overall mean-rate perspective, both overlay and underlay bring performance improvements (vs. pure cellular). Third, the single-antenna hybrid network model is extended to multi-antenna transmission to study the interplay between massive MIMO (multi-input multiple-output) and underlaid D2D networking. The spectral efficiency of such multi-antenna hybrid networks is investigated under both perfect and imperfect channel state information (CSI) assumptions. Compared to the case without D2D, there is a loss in cellular spectral efficiency due to D2D underlay. With perfect CSI, the loss can be completely overcome if the number of canceled D2D interfering signals is scaled appropriately. With imperfect CSI, in addition to pilot contamination, a new asymptotic underlay contamination effect arises. Finally, motivated by the fact that transmissions in D2D discovery are usually not or imperfectly synchronized, this dissertation studies the effect of asynchronous multicarrier transmission and proposes a tractable signal-to-interference-plus-noise ratio (SINR) model. The proposed model is used to analytically characterize system-level performance of asynchronous wireless networks. The loss from lack of synchronization is quantified, and several solutions are proposed and compared to mitigate the loss.Electrical and Computer Engineerin
A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond
Today's wireless networks allocate radio resources to users based on the
orthogonal multiple access (OMA) principle. However, as the number of users
increases, OMA based approaches may not meet the stringent emerging
requirements including very high spectral efficiency, very low latency, and
massive device connectivity. Nonorthogonal multiple access (NOMA) principle
emerges as a solution to improve the spectral efficiency while allowing some
degree of multiple access interference at receivers. In this tutorial style
paper, we target providing a unified model for NOMA, including uplink and
downlink transmissions, along with the extensions tomultiple inputmultiple
output and cooperative communication scenarios. Through numerical examples, we
compare the performances of OMA and NOMA networks. Implementation aspects and
open issues are also detailed.Comment: 25 pages, 10 figure
A survey of flooding, gossip routing, and related schemes for wireless multi- hop networks
Flooding is an essential and critical service in computer networks that is
used by many routing protocols to send packets from a source to all nodes in
the network. As the packets are forwarded once by each receiving node, many
copies of the same packet traverse the network which leads to high redundancy
and unnecessary usage of the sparse capacity of the transmission medium.
Gossip routing is a well-known approach to improve the flooding in wireless
multi-hop networks. Each node has a forwarding probability p that is either
statically per-configured or determined by information that is available at
runtime, e.g, the node degree. When a packet is received, the node selects a
random number r. If the number r is below p, the packet is forwarded and
otherwise, in the most simple gossip routing protocol, dropped. With this
approach the redundancy can be reduced while at the same time the reachability
is preserved if the value of the parameter p (and others) is chosen with
consideration of the network topology. This technical report gives an overview
of the relevant publications in the research domain of gossip routing and
gives an insight in the improvements that can be achieved. We discuss the
simulation setups and results of gossip routing protocols as well as further
improved flooding schemes. The three most important metrics in this
application domain are elaborated: reachability, redundancy, and management
overhead. The published studies used simulation environments for their
research and thus the assumptions, models, and parameters of the simulations
are discussed and the feasibility of an application for real world wireless
networks are highlighted. Wireless mesh networks based on IEEE 802.11 are the
focus of this survey but publications about other network types and
technologies are also included. As percolation theory, epidemiological models,
and delay tolerant networks are often referred as foundation, inspiration, or
application of gossip routing in wireless networks, a brief introduction to
each research domain is included and the applicability of the particular
models for the gossip routing is discussed
multimedia transmission over wireless networks: performance analysis and optimal resource allocation
In recent years, multimedia applications such as video telephony, teleconferencing, and video streaming, which are delay sensitive and bandwidth intensive, have started to account for a significant portion of the data traffic in wireless networks. Such multimedia applications require certain quality of service (QoS) guarantees in terms of delay, packet loss, buffer underflows and overflows, and received multimedia quality. It is also important to note that such requirements need to be satisfied in the presence of limited wireless resources, such as power and bandwidth. Therefore, it is critical to conduct a rigorous performance analysis of multimedia transmissions over wireless networks and identify efficient resource allocation strategies.
Motivated by these considerations, in the first part of the thesis, performance of hierarchical modulation-based multimedia transmissions is analyzed. Unequal error protection (UEP) of data transmission using hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, two different types of wireless networks are considered. Specifically, multimedia transmission over cognitive radio networks and device-to-device (D2D) cellular wireless networks is addressed. Closed-form bit error rate (BER) expressions are derived and optimal power control strategies are determined.
Next, throughput and optimal resource allocation strategies are studied for multimedia transmission under delay QoS and energy efficiency (EE) constraints. A Quality-Rate (QR) distortion model is employed to measure the quality of received video in terms of peak signal-to-noise ratio (PSNR) as a function of video source rate. Effective capacity (EC) is used as the throughput metric under delay QoS constraints. In this analysis, four different wireless networks are taken into consideration:
First, D2D underlaid wireless networks are addressed. Efficient transmission mode selection and resource allocation strategies are analyzed with the goal of maximizing the quality of the received video at the receiver in a frequency-division duplexed (FDD) cellular network with a pair of cellular users, one base station and a pair of D2D users under delay QoS and EE constraints.
A full-duplex communication scenario with a pair of users and multiple subchannels in which users can have different delay requirements is addressed. Since the optimization problem is not concave or convex due to the presence of interference, optimal power allocation policies that maximize the weighted sum video quality subject to total transmission power level constraint are derived by using monotonic optimization theory. The optimal scheme is compared with two suboptimal strategies.
A full-duplex communication scenario with multiple pairs of users in which different users have different delay requirements is addressed. EC is used as the throughput metric in the presence of statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. Optimal resource allocation strategies are determined under bandwidth, power and minimum video quality constraints again using the monotonic optimization framework.
A broadcast scenario in which a single transmitter sends multimedia data to multiple receivers is considered. The optimal bandwidth allocation and the optimal power allocation/power control policies that maximize the sum video quality subject to total bandwidth and minimum EE constraints are derived. Five different resource allocation strategies are investigated, and the joint optimization of the bandwidth allocation and power control is shown to provide the best performance. Tradeoff between EE and video quality is also demonstrated.
In the final part of the thesis, power control policies are investigated for streaming variable bit rate (VBR) video over wireless links. A deterministic traffic model for stored VBR video, taking into account the frame size, frame rate, and playout buffers is considered. Power control and the transmission mode selection with the goal of maximizing the sum transmission rate while avoiding buffer underflows and overflows under transmit power constraints is exploited in a D2D wireless network. Another system model involving a transmitter (e.g., a base station (BS)) that sends VBR video data to a mobile user equipped with a playout buffer is also adopted. In this setting, both offline and online power control policies are considered in order to minimize the transmission power without playout buffer underflows and overflows. Both dynamic programming and reinforcement learning based algorithms are developed
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