2,026 research outputs found
Power-Efficient Radio Resource Allocation for Low-Medium -Altitude Aerial Platform Based TD-LTE Networks
In order to provide an increased capacity, throughput and QoS guarantee for terrestrial users in emergency scenarios, a low-medium-altitude aerial platform based time-division-duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Additionally a power-efficient radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game. Our simulation results demonstrate that the proposed algorithm imposes an attractive tradeoff between the achievable throughput and the power consumption while ensuring fairness among users
Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems
Most existing work on adaptive allocation of subcarriers and power in
multiuser orthogonal frequency division multiplexing (OFDM) systems has focused
on homogeneous traffic consisting solely of either delay-constrained data
(guaranteed service) or non-delay-constrained data (best-effort service). In
this paper, we investigate the resource allocation problem in a heterogeneous
multiuser OFDM system with both delay-constrained (DC) and
non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate
of all the users with NDC traffic while maintaining guaranteed rates for the
users with DC traffic under a total transmit power constraint. Through our
analysis we show that the optimal power allocation over subcarriers follows a
multi-level water-filling principle; moreover, the valid candidates competing
for each subcarrier include only one NDC user but all DC users. By converting
this combinatorial problem with exponential complexity into a convex problem or
showing that it can be solved in the dual domain, efficient iterative
algorithms are proposed to find the optimal solutions. To further reduce the
computational cost, a low-complexity suboptimal algorithm is also developed.
Numerical studies are conducted to evaluate the performance the proposed
algorithms in terms of service outage probability, achievable transmission rate
pairs for DC and NDC traffic, and multiuser diversity.Comment: 29 pages, 8 figures, submitted to IEEE Transactions on Wireless
Communication
Joint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network
Load imbalance, together with inefficient utilization of system resource, constitute major factors responsible for poor overall performance in Long Term Evolution (LTE) network. In this paper, a novel scheme of joint dynamic resource allocation and load balancing is proposed to achieve a balanced performance improvement in 3rd Generation Partnership Project (3GPP) LTE Self-Organizing Networks (SON). The new method which aims at maximizing network resource efficiency subject to inter-cell interference and intra-cell resource constraints is implemented in two steps. In the first step, an efficient resource allocation, including user scheduling and power assignment, is conducted in a distributed manner to serve as many users in the whole network as possible. In the second step, based on the resource allocation scheme, the optimization objective namely network resource efficiency can be calculated and load balancing is implemented by switching the user that can maximize the objective function. Lagrange Multipliers method and heuristic algorithm are used to resolve the formulated optimization problem. Simulation results show that our algorithm achieves better performance in terms of user throughput, fairness, load balancing index and unsatisfied user number compared with the traditional approach which takes resource allocation and load balancing into account, respectively
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
Adaptive Multi-objective Optimization for Energy Efficient Interference Coordination in Multi-Cell Networks
In this paper, we investigate the distributed power allocation for multi-cell
OFDMA networks taking both energy efficiency and inter-cell interference (ICI)
mitigation into account. A performance metric termed as throughput contribution
is exploited to measure how ICI is effectively coordinated. To achieve a
distributed power allocation scheme for each base station (BS), the throughput
contribution of each BS to the network is first given based on a pricing
mechanism. Different from existing works, a biobjective problem is formulated
based on multi-objective optimization theory, which aims at maximizing the
throughput contribution of the BS to the network and minimizing its total power
consumption at the same time. Using the method of Pascoletti and Serafini
scalarization, the relationship between the varying parameters and minimal
solutions is revealed. Furthermore, to exploit the relationship an algorithm is
proposed based on which all the solutions on the boundary of the efficient set
can be achieved by adaptively adjusting the involved parameters. With the
obtained solution set, the decision maker has more choices on power allocation
schemes in terms of both energy consumption and throughput. Finally, the
performance of the algorithm is assessed by the simulation results.Comment: 29 page
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