2,413 research outputs found
Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method
This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and non-convex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information
Joint User-Association and Resource-Allocation in Virtualized Wireless Networks
In this paper, we consider a down-link transmission of multicell virtualized
wireless networks (VWNs) where users of different service providers (slices)
within a specific region are served by a set of base stations (BSs) through
orthogonal frequency division multiple access (OFDMA). In particular, we
develop a joint BS assignment, sub-carrier and power allocation algorithm to
maximize the network throughput, while satisfying the minimum required rate of
each slice. Under the assumption that each user at each transmission instance
can connect to no more than one BS, we introduce the user-association factor
(UAF) to represent the joint sub-carrier and BS assignment as the optimization
variable vector in the mathematical problem formulation. Sub-carrier reuse is
allowed in different cells, but not within one cell. As the proposed
optimization problem is inherently non-convex and NP-hard, by applying the
successive convex approximation (SCA) and complementary geometric programming
(CGP), we develop an efficient two-step iterative approach with low
computational complexity to solve the proposed problem. For a given
power-allocation, Step 1 derives the optimum userassociation and subsequently,
for an obtained user-association, Step 2 find the optimum power-allocation.
Simulation results demonstrate that the proposed iterative algorithm
outperforms the traditional approach in which each user is assigned to the BS
with the largest average value of signal strength, and then, joint sub-carrier
and power allocation is obtained for the assigned users of each cell.
Especially, for the cell-edge users, simulation results reveal a coverage
improvement up to 57% and 71% for uniform and non-uniform users distribution,
respectively leading to more reliable transmission and higher spectrum
efficiency for VWN
Advanced Radio Resource Management for Multi Antenna Packet Radio Systems
In this paper, we propose fairness-oriented packet scheduling (PS) schemes
with power-efficient control mechanism for future packet radio systems. In
general, the radio resource management functionality plays an important role in
new OFDMA based networks. The control of the network resource division among
the users is performed by packet scheduling functionality based on maximizing
cell coverage and capacity satisfying, and certain quality of service
requirements. Moreover, multiantenna transmit-receive schemes provide
additional flexibility to packet scheduler functionality. In order to mitigate
inter-cell and co-channel interference problems in OFDMA cellular networks soft
frequency reuse with different power masks patterns is used. Stemming from the
earlier enhanced proportional fair scheduler studies for single-input
multiple-output (SIMO) and multiple-input multipleoutput (MIMO) systems, we
extend the development of efficient packet scheduling algorithms by adding
transmit power considerations in the overall priority metrics calculations and
scheduling decisions. Furthermore, we evaluate the proposed scheduling schemes
by simulating practical orthogonal frequency division multiple access (OFDMA)
based packet radio system in terms of throughput, coverage and fairness
distribution among users. As a concrete example, under reduced overall transmit
power constraint and unequal power distribution for different sub-bands, we
demonstrate that by using the proposed power-aware multi-user scheduling
schemes, significant coverage and fairness improvements in the order of 70% and
20%, respectively, can be obtained, at the expense of average throughput loss
of only 15%.Comment: 14 Pages, IJWM
Analytical Model of Proportional Fair Scheduling in Interference-limited OFDMA/LTE Networks
Various system tasks like interference coordination, handover decisions,
admission control etc. in upcoming cellular networks require precise mid-term
(spanning over a few seconds) performance models. Due to channel-dependent
scheduling at the base station, these performance models are not simple to
obtain. Furthermore, upcoming cellular systems will be interference-limited,
hence, the way interference is modeled is crucial for the accuracy. In this
paper we present an analytical model for the SINR distribution of the
\textit{scheduled} subcarriers of an OFDMA system with proportional fair
scheduling. The model takes the precise SINR distribution into account. We
furthermore refine our model with respect to uniform modulation and coding, as
applied in LTE networks. The derived models are validated by means of
simulations. In additon, we show that our models are approximate estimators for
the performance of rate-based proportional fair scheduling, while they
outperform some simpler prediction models from related work significantly.Comment: 7 pages, 6 figures. This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Scheduling for Multi-Camera Surveillance in LTE Networks
Wireless surveillance in cellular networks has become increasingly important,
while commercial LTE surveillance cameras are also available nowadays.
Nevertheless, most scheduling algorithms in the literature are throughput,
fairness, or profit-based approaches, which are not suitable for wireless
surveillance. In this paper, therefore, we explore the resource allocation
problem for a multi-camera surveillance system in 3GPP Long Term Evolution
(LTE) uplink (UL) networks. We minimize the number of allocated resource blocks
(RBs) while guaranteeing the coverage requirement for surveillance systems in
LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation
Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an
Integer Linear Programming formulation for general cases to find the optimal
solution. Moreover, we present a baseline algorithm and devise an approximation
algorithm to solve the problem. Simulation results based on a real surveillance
map and synthetic datasets manifest that the number of allocated RBs can be
effectively reduced compared to the existing approach for LTE networks.Comment: 9 pages, 10 figure
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