2,408 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
Scheduling strategies for LTE uplink with flow behaviour analysis
Long Term Evolution (LTE) is a cellular technology developed to support\ud
diversity of data traffic at potentially high rates. It is foreseen to extend the capacity and improve the performance of current 3G cellular networks. A key\ud
mechanism in the LTE traffic handling is the packet scheduler, which is in charge of allocating resources to active flows in both the frequency and time dimension. In this paper we present a performance comparison of two distinct scheduling schemes for LTE uplink (fair fixed assignment and fair work-conserving) taking into account both packet level characteristics and flow level dynamics due to the random user behaviour. For that purpose, we apply a combined analytical/simulation approach which enables fast evaluation of performance measures such as mean flow transfer times manifesting the impact of resource allocation strategies. The results show that the resource allocation strategy has a crucial impact on performance and that some trends are observed only if flow level dynamics are considered
Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks with Base Station Coordination
This paper addresses the problem of energy-efficient resource allocation in
the downlink of a cellular OFDMA system. Three definitions of the energy
efficiency are considered for system design, accounting for both the radiated
and the circuit power. User scheduling and power allocation are optimized
across a cluster of coordinated base stations with a constraint on the maximum
transmit power (either per subcarrier or per base station). The asymptotic
noise-limited regime is discussed as a special case. %The performance of both
an isolated and a non-isolated cluster of coordinated base stations is examined
in the numerical experiments. Results show that the maximization of the energy
efficiency is approximately equivalent to the maximization of the spectral
efficiency for small values of the maximum transmit power, while there is a
wide range of values of the maximum transmit power for which a moderate
reduction of the data rate provides a large saving in terms of dissipated
energy. Also, the performance gap among the considered resource allocation
strategies reduces as the out-of-cluster interference increases.Comment: to appear on IEEE Transactions on Wireless Communication
Asymptotic Close To Optimal Joint Resource Allocation and Power Control in the Uplink of Two-cell Networks
In this paper, we investigate joint resource allocation and power control
mechanisms for two-cell networks, where each cell has some sub-channels which
should be allocated to some users. The main goal persuaded in the current work
is finding the best power and sub-channel assignment strategies so that the
associated sum-rate of network is maximized, while a minimum rate constraint is
maintained by each user. The underlying optimization problem is a highly
non-convex mixed integer and non-linear problem which does not yield a trivial
solution. In this regard, to tackle the problem, using an approximate function
which is quite tight at moderate to high signal to interference plus noise
ratio (SINR) region, the problem is divided into two disjoint sub-channel
assignment and power allocation problems. It is shown that having fixed the
allocated power of each user, the subchannel assignment can be thought as a
well-known assignment problem which can be effectively solved using the
so-called Hungarian method. Then, the power allocation is analytically derived.
Furthermore, it is shown that the power can be chosen from two extremal points
of the maximum available power or the minimum power satisfying the rate
constraint. Numerical results demonstrate the superiority of the proposed
approach over the random selection strategy as well as the method proposed in
[3] which is regarded as the best known method addressed in the literature
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
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