9,158 research outputs found
A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs
This paper considers proportional fairness amongst ACs in an EDCA WLAN for
provision of distinct QoS requirements and priority parameters. A detailed
theoretical analysis is provided to derive the optimal station attempt
probability which leads to a proportional fair allocation of station
throughputs. The desirable fairness can be achieved using a centralised
adaptive control approach. This approach is based on multivariable statespace
control theory and uses the Linear Quadratic Integral (LQI) controller to
periodically update CWmin till the optimal fair point of operation. Performance
evaluation demonstrates that the control approach has high accuracy performance
and fast convergence speed for general network scenarios. To our knowledge this
might be the first time that a closed-loop control system is designed for EDCA
WLANs to achieve proportional fairness
Multiuser Switched Diversity Scheduling Schemes
Multiuser switched-diversity scheduling schemes were recently proposed in
order to overcome the heavy feedback requirements of conventional opportunistic
scheduling schemes by applying a threshold-based, distributed, and ordered
scheduling mechanism. The main idea behind these schemes is that slight
reduction in the prospected multiuser diversity gains is an acceptable
trade-off for great savings in terms of required channel-state-information
feedback messages. In this work, we characterize the achievable rate region of
multiuser switched diversity systems and compare it with the rate region of
full feedback multiuser diversity systems. We propose also a novel proportional
fair multiuser switched-based scheduling scheme and we demonstrate that it can
be optimized using a practical and distributed method to obtain the feedback
thresholds. We finally demonstrate by numerical examples that
switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the
ultimate network capacity of full feedback systems in Rayleigh fading
conditions.Comment: Accepted at IEEE Transactions on Communications, to appear 2012,
funded by NPRP grant 08-577-2-241 from QNR
An Optimal Application-Aware Resource Block Scheduling in LTE
In this paper, we introduce an approach for application-aware resource block
scheduling of elastic and inelastic adaptive real-time traffic in fourth
generation Long Term Evolution (LTE) systems. The users are assigned to
resource blocks. A transmission may use multiple resource blocks scheduled over
frequency and time. In our model, we use logarithmic and sigmoidal-like utility
functions to represent the users applications running on different user
equipments (UE)s. We present an optimal problem with utility proportional
fairness policy, where the fairness among users is in utility percentage (i.e
user satisfaction with the service) of the corresponding applications. Our
objective is to allocate the resources to the users with priority given to the
adaptive real-time application users. In addition, a minimum resource
allocation for users with elastic and inelastic traffic should be guaranteed.
Every user subscribing for the mobile service should have a minimum
quality-of-service (QoS) with a priority criterion. We prove that our
scheduling policy exists and achieves the maximum. Therefore the optimal
solution is tractable. We present a centralized scheduling algorithm to
allocate evolved NodeB (eNodeB) resources optimally with a priority criterion.
Finally, we present simulation results for the performance of our scheduling
algorithm and compare our results with conventional proportional fairness
approaches. The results show that the user satisfaction is higher with our
proposed method.Comment: 5 page
Weighted Max-Min Resource Allocation for Frequency Selective Channels
In this paper, we discuss the computation of weighted max-min rate allocation
using joint TDM/FDM strategies under a PSD mask constraint. We show that the
weighted max-min solution allocates the rates according to a predetermined rate
ratio defined by the weights, a fact that is very valuable for
telecommunication service providers. Furthermore, we show that the problem can
be efficiently solved using linear programming. We also discuss the resource
allocation problem in the mixed services scenario where certain users have a
required rate, while the others have flexible rate requirements. The solution
is relevant to many communication systems that are limited by a power spectral
density mask constraint such as WiMax, Wi-Fi and UWB
Opportunistic transmission scheduling for next generation wireless communication systems with multimedia services
The explosive growth of the Internet and the continued dramatic increase for all wireless services are fueling the demand for increased capacity, data rates, and support of different quality of service (QoS) requirements for different classes of services. Since in the current and future wireless communication infrastructures, the performances of the various services are strongly correlated, as the resources are shared among them, dynamic resource allocation methods should be employed. With the demand for high data rate and support of multiple QoS, the transmission scheduling plays a key role in the efficient resource allocation process in wireless systems. The fundamental problem of scheduling the users\u27 transmissions and allocating the available resources in a realistic CDMA wireless system that supports multi-rate multimedia services, with efficiency and fairness, is investigated and analyzed in this dissertation.
Our proposed approach adopts the use of dynamically assigned data rates that match the channel capacity in order to improve the system throughput and overcome the problems associated with the location-dependent and time-dependent errors and channel conditions, the variable system capacity and the transmission power limitation. We first introduce and describe two new scheduling algorithms, namely the Channel Adaptive Rate Scheduling (CARS) and Fair Channel Adaptive Rate Scheduling (FCARS). CARS exploits the channel variations to reach high throughput, by adjusting the transmission rates according to the varying channel conditions and by performing an iterative procedure to determine the power index that a user can accept by its current channel condition and transmission power. Based on the assignment of CARS and to overcome potential unfair service allocation, FCARS implements a compensation algorithm, in which the lagging users can receive compensation service when the corresponding channel conditions improve, in order to achieve asymptotic throughput fairness, while still maintaining all the constraints imposed by the system.
Furthermore the problem of opportunistic fair scheduling in the uplink transmission of CDMA systems, with the objective of maximizing the uplink system throughput, while satisfying the users\u27 QoS requirements and maintaining the long-term fairness among the various users despite their different varying channel conditions, is rigorously formulated, and a throughput optimal fair scheduling policy is obtained. The corresponding problem is expressed as a weighted throughput maximization problem, under certain power and QoS constraints, where the weights are the control parameters that reflect the fairness constraints. With the introduction of the power index capacity it is shown that this optimization problem can be converted into a binary knapsack problem, where all the corresponding constraints are replaced by the users\u27 power index capacities at some certain system power index. It is then argued that the optimal solution can be obtained as a global search within a certain range, while a stochastic approximation method is presented in order to effectively identify the required control parameters. Finally, since some real-time services may demand certain amount of service within specific short span of time in order to avoid service delays, the problem of designing policies that can achieve high throughput while at the same time maintain short term fairness, is also considered and investigated. To this end a new Credit-based Short-term Fairness Scheduling (CSFS) algorithm, which achieves to provide short-term fairness to the delay-sensitive users while still schedules opportunistically the non-delay-sensitive users to obtain high system throughput, is proposed and evaluated
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