1,993 research outputs found
A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning
In this tutorial paper, a comprehensive survey is given on several major
systematic approaches in dealing with delay-aware control problems, namely the
equivalent rate constraint approach, the Lyapunov stability drift approach and
the approximate Markov Decision Process (MDP) approach using stochastic
learning. These approaches essentially embrace most of the existing literature
regarding delay-aware resource control in wireless systems. They have their
relative pros and cons in terms of performance, complexity and implementation
issues. For each of the approaches, the problem setup, the general solution and
the design methodology are discussed. Applications of these approaches to
delay-aware resource allocation are illustrated with examples in single-hop
wireless networks. Furthermore, recent results regarding delay-aware multi-hop
routing designs in general multi-hop networks are elaborated. Finally, the
delay performance of the various approaches are compared through simulations
using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201
On the Performance of Short Block Codes over Finite-State Channels in the Rare-Transition Regime
As the mobile application landscape expands, wireless networks are tasked
with supporting different connection profiles, including real-time traffic and
delay-sensitive communications. Among many ensuing engineering challenges is
the need to better understand the fundamental limits of forward error
correction in non-asymptotic regimes. This article characterizes the
performance of random block codes over finite-state channels and evaluates
their queueing performance under maximum-likelihood decoding. In particular,
classical results from information theory are revisited in the context of
channels with rare transitions, and bounds on the probabilities of decoding
failure are derived for random codes. This creates an analysis framework where
channel dependencies within and across codewords are preserved. Such results
are subsequently integrated into a queueing problem formulation. For instance,
it is shown that, for random coding on the Gilbert-Elliott channel, the
performance analysis based on upper bounds on error probability provides very
good estimates of system performance and optimum code parameters. Overall, this
study offers new insights about the impact of channel correlation on the
performance of delay-aware, point-to-point communication links. It also
provides novel guidelines on how to select code rates and block lengths for
real-time traffic over wireless communication infrastructures
Enabling Techniques Design for QoS Provision in Wireless Communications
Guaranteeing Quality of Service (QoS) has become a recognized feature in the design of wireless communications. In this thesis, the problem of QoS provision is addressed from different prospectives in several modern communication systems.
In the first part of the thesis, a wireless communication system with the base station (BS) associated by multiple subscribers (SS) is considered, where different subscribers require different QoS. Using the cross-layer approach, the conventional single queue finite state Markov chain system model is extended to multiple queues\u27 scenario by combining the MAC layer queue status with the physical layer channel states, modeled by finite state Markov channel (FSMC). To provide the diverse QoS to different subscribers, a priority-based rate allocation (PRA) algorithm is proposed to allocate the physical layer transmission rate to the multiple medium access control (MAC) layer queues, where different queues are assigned with different priorities, leading to their different QoS performance and thus, the diverse QoS are guaranteed.
Then, the subcarrier allocation in multi-user OFDM (MU-OFDM) systems is stuied, constrained by the MAC layer diverse QoS requirements. A two-step cross-layer dynamic subcarrier allocation algorithm is proposed where the MAC layer queue status is firstly modeled by a finite state Markov chain, using which MAC layer diverse QoS constraints are transformed to the corresponding minimum physical layer data rate of each user. Then, with the purpose of maximizing the system capacity, the physical layer OFDM subcarriers are allocated to the multiple users to satisfy their minimum data rate requirements, which is derived by the MAC layer queue status model.
Finally, the problem of channel assignment in IEEE 802.11 wireless local area networks (WLAN) is investigated, oriented by users\u27 QoS requirements. The number of users in the IEEE 802.11 channels is first determined through the number of different channel impulse responses (CIR) estimated at physical layer. This information is involved thereafter in the proposed channel assignment algorithm, which aims at maximum system throughput, where we explore the partially overlapped IEEE 802.11 channels to provide additional frequency resources. Moreover, the users\u27 QoS requirements are set to trigger the channel assignment process, such that the system can constantly maintain the required QoS
CMD: A Multi-Channel Coordination Scheme for Emergency Message Dissemination in IEEE 1609.4
In the IEEE 1609.4 legacy standard for multi-channel communications in
vehicular ad hoc networks(VANETs), the control channel (CCH) is dedicated to
broadcast safety messages while the service channels (SCH's) are dedicated to
transmit infotainment service content. However, the SCH can be used as an
alternative to transmit high priority safety messages in the event that they
are invoked during the service channel interval (SCHI). This implies that there
is a need to transmit safety messages across multiple available utilized
channels to ensure that all vehicles receive the safety message. Transmission
across multiple SCH's using the legacy IEEE 1609.4 requires multiple channel
switching and therefore introduces further end-to-end delays. Given that safety
messaging is a life critical application, it is important that optimal
end-to-end delay performance is derived in multi-channel VANET scenarios to
ensure reliable safety message dissemination. To tackle this challenge, three
primary contributions are in this article: first, a channel coordinator
selection approach based on the least average separation distance (LAD) to the
vehicles that expect to tune to other SCH's and operates during the control
channel interval (CCHI) is proposed. Second, a model to determine the optimal
time intervals in which CMD operates during the CCHI is proposed. Third, a
contention back-off mechanism for safety message transmission during the SCHI
is proposed. Computer simulations and mathematical analysis show that CMD
performs better than the legacy IEEE 1609.4 and a selected state-of-the-art
multi-channel message dissemination schemes in terms of end-to-end delay and
packet reception ratio.Comment: 15 pages, 10 figures, 7 table
Scheduling and Power Control for Wireless Multicast Systems via Deep Reinforcement Learning
Multicasting in wireless systems is a natural way to exploit the redundancy
in user requests in a Content Centric Network. Power control and optimal
scheduling can significantly improve the wireless multicast network's
performance under fading. However, the model based approaches for power control
and scheduling studied earlier are not scalable to large state space or
changing system dynamics. In this paper, we use deep reinforcement learning
where we use function approximation of the Q-function via a deep neural network
to obtain a power control policy that matches the optimal policy for a small
network. We show that power control policy can be learnt for reasonably large
systems via this approach. Further we use multi-timescale stochastic
optimization to maintain the average power constraint. We demonstrate that a
slight modification of the learning algorithm allows tracking of time varying
system statistics. Finally, we extend the multi-timescale approach to
simultaneously learn the optimal queueing strategy along with power control. We
demonstrate scalability, tracking and cross layer optimization capabilities of
our algorithms via simulations. The proposed multi-timescale approach can be
used in general large state space dynamical systems with multiple objectives
and constraints, and may be of independent interest.Comment: arXiv admin note: substantial text overlap with arXiv:1910.0530
Delay QoS Provisioning and Optimal Resource Allocation for Wireless Networks
Recent years have witnessed a significant growth in wireless communication and networking due to the exponential growth in mobile applications and smart devices, fueling unprecedented increase in both mobile data traffic and energy demand. Among such data traffic, real-time data transmissions in wireless systems require certain quality of service (QoS) constraints e.g., in terms of delay, buffer overflow or packet drop/loss probabilities, so that acceptable performance levels can be guaranteed for the end-users, especially in delay sensitive scenarios, such as live video transmission, interactive video (e.g., teleconferencing), and mobile online gaming. With this motivation, statistical queuing constraints are considered in this thesis, imposed as limitations on the decay rate of buffer overflow probabilities. In particular, the throughput and energy efficiency of different types of wireless network models are analyzed under QoS constraints, and optimal resource allocation algorithms are proposed to maximize the throughput or minimize the delay.
In the first part of the thesis, the throughput and energy efficiency analysis for hybrid automatic repeat request (HARQ) protocols are conducted under QoS constraints. Approximations are employed for small QoS exponent values in order to obtain closed-form expressions for the throughput and energy efficiency metrics. Also, the impact of random arrivals, deadline constraints, outage probability and QoS constraints are studied. For the same system setting, the throughput of HARQ system is also analyzed using a recurrence approach, which provides more accurate results for any value of the QoS exponent. Similarly, random arrival models and deadline constraints are considered, and these results are further extended to the finite-blocklength coding regime.
Next, cooperative relay networks are considered under QoS constraints. Specifically, the throughput performance in the two-hop relay channel, two-way relay channel, and multi-source multi-destination relay networks is analyzed. Finite-blocklength codes are considered for the two-hop relay channel, and optimization over the error probabilities is investigated. For the multi-source multi-destination relay network model, the throughput for both cases of with and without CSI at the transmitter sides is studied. When there is perfect CSI at the transmitter, transmission rates can be varied according to instantaneous channel conditions. When CSI is not available at the transmitter side, transmissions are performed at fixed rates, and decoding failures lead to retransmission requests via an ARQ protocol.
Following the analysis of cooperative networks, the performance of both half-duplex and full-duplex operations is studied for the two-way multiple input multiple output (MIMO) system under QoS constraints. In full-duplex mode, the self-interference inflicted on the reception of a user due to simultaneous transmissions from the same user is taken into account. In this setting, the system throughput
is formulated by considering the sum of the effective capacities of the users in both half-duplex and full-duplex modes. The low signal to noise ratio (SNR) regime is considered and the optimal transmission/power-allocation strategies are characterized by identifying the optimal input covariance matrices.
Next, mode selection and resource allocation for device-to-device (D2D) cellular networks are studied. As the starting point, ransmission mode selection and resource allocation are analyzed for a time-division multiplexed (TDM) cellular network with one cellular user, one base station, and a pair of D2D users under rate and QoS constraints. For a more complicated setting with multiple cellular and D2D users, two joint mode selection and resource allocation algorithms are proposed. In the first algorithm, the channel allocation problem is formulated as a maximum-weight matching problem, which can be solved by employing the Hungarian algorithm. In the second algorithm, the problem is divided into three subproblems, namely user partition, power allocation and channel assignment, and a novel three-step method is proposed by combining the algorithms designed for the three subproblems.
In the final part of the thesis, resource allocation algorithms are investigated for content delivery over wireless networks. Three different systems are considered. Initially, a caching algorithm is designed, which minimizes the average delay of a single-cell network. The proposed algorithm is applicable in settings with very general popularity models, with no assumptions on how file popularity varies among different users, and this algorithm is further extended to a more general setting, in which the system parameters and the distributions of channel fading change over time. Next, for D2D cellular networks operating under deadline constraints, a scheduling algorithm is designed, which manages mode selection, channel allocation and power maximization with acceptable complexity. This proposed scheduling algorithm is designed based on the convex delay cost method for a D2D cellular network with deadline constraints in an OFDMA setting. Power optimization algorithms are proposed for all possible modes, based on our utility definition. Finally, a two-step intercell interference (ICI)-aware scheduling algorithm is proposed for cloud radio access networks (C-RANs), which performs user grouping and resource allocation with the goal of minimizing delay violation probability. A novel user grouping algorithm is developed for the user grouping step, which controls the interference among the users in the same group, and the channel assignment problem is formulated as a maximum-weight matching problem in the second step, which can be solved using standard algorithms in graph theory
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