2,569 research outputs found
Distributive Network Utility Maximization (NUM) over Time-Varying Fading Channels
Distributed network utility maximization (NUM) has received an increasing
intensity of interest over the past few years. Distributed solutions (e.g., the
primal-dual gradient method) have been intensively investigated under fading
channels. As such distributed solutions involve iterative updating and explicit
message passing, it is unrealistic to assume that the wireless channel remains
unchanged during the iterations. Unfortunately, the behavior of those
distributed solutions under time-varying channels is in general unknown. In
this paper, we shall investigate the convergence behavior and tracking errors
of the iterative primal-dual scaled gradient algorithm (PDSGA) with dynamic
scaling matrices (DSC) for solving distributive NUM problems under time-varying
fading channels. We shall also study a specific application example, namely the
multi-commodity flow control and multi-carrier power allocation problem in
multi-hop ad hoc networks. Our analysis shows that the PDSGA converges to a
limit region rather than a single point under the finite state Markov chain
(FSMC) fading channels. We also show that the order of growth of the tracking
errors is given by O(T/N), where T and N are the update interval and the
average sojourn time of the FSMC, respectively. Based on this analysis, we
derive a low complexity distributive adaptation algorithm for determining the
adaptive scaling matrices, which can be implemented distributively at each
transmitter. The numerical results show the superior performance of the
proposed dynamic scaling matrix algorithm over several baseline schemes, such
as the regular primal-dual gradient algorithm
Wireless Network Control with Privacy Using Hybrid ARQ
We consider the problem of resource allocation in a wireless cellular
network, in which nodes have both open and private information to be
transmitted to the base station over block fading uplink channels. We develop a
cross-layer solution, based on hybrid ARQ transmission with incremental
redundancy. We provide a scheme that combines power control, flow control, and
scheduling in order to maximize a global utility function, subject to the
stability of the data queues, an average power constraint, and a constraint on
the privacy outage probability. Our scheme is based on the assumption that each
node has an estimate of its uplink channel gain at each block, while only the
distribution of the cross channel gains is available. We prove that our scheme
achieves a utility, arbitrarily close to the maximum achievable utility given
the available channel state information
Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks
This paper addresses the cell association problem in the downlink of a
multi-tier heterogeneous network (HetNet), where base stations (BSs) have
finite number of resource blocks (RBs) available to distribute among their
associated users. Two problems are defined and treated in this paper: sum
utility of long term rate maximization with long term rate quality of service
(QoS) constraints, and global outage probability minimization with outage QoS
constraints. The first problem is well-suited for low mobility environments,
while the second problem provides a framework to deal with environments with
fast fading. The defined optimization problems in this paper are solved in two
phases: cell association phase followed by the optional RB distribution phase.
We show that the cell association phase of both problems have the same
structure. Based on this similarity, we propose a unified distributed algorithm
with low levels of message passing to for the cell association phase. This
distributed algorithm is derived by relaxing the association constraints and
using Lagrange dual decomposition method. In the RB distribution phase, the
remaining RBs after the cell association phase are distributed among the users.
Simulation results show the superiority of our distributed cell association
scheme compared to schemes that are based on maximum signal to interference
plus noise ratio (SINR)
Cost minimization for fading channels with energy harvesting and conventional energy
In this paper, we investigate resource allocation strategies for a
point-to-point wireless communications system with hybrid energy sources
consisting of an energy harvester and a conventional energy source. In
particular, as an incentive to promote the use of renewable energy, we assume
that the renewable energy has a lower cost than the conventional energy. Then,
by assuming that the non-causal information of the energy arrivals and the
channel power gains are available, we minimize the total energy cost of such a
system over fading slots under a proposed outage constraint together with
the energy harvesting constraints. The outage constraint requires a minimum
fixed number of slots to be reliably decoded, and thus leads to a mixed-integer
programming formulation for the optimization problem. This constraint is
useful, for example, if an outer code is used to recover all the data bits.
Optimal linear time algorithms are obtained for two extreme cases, i.e., the
number of outage slot is or . For the general case, a lower bound
based on the linear programming relaxation, and two suboptimal algorithms are
proposed. It is shown that the proposed suboptimal algorithms exhibit only a
small gap from the lower bound. We then extend the proposed algorithms to the
multi-cycle scenario in which the outage constraint is imposed for each cycle
separately. Finally, we investigate the resource allocation strategies when
only causal information on the energy arrivals and only channel statistics is
available. It is shown that the greedy energy allocation is optimal for this
scenario.Comment: to appear in IEEE Transactions on Wireless Communication
Subcarrier and Power Allocation for LDS-OFDM System
Low Density Signature-Orthogonal Frequency Division Multiplexing (LDS-OFDM) has been introduced recently as an efficient multiple access technique. In this paper, we focus on the subcarrier and power allocation scheme for uplink LDS-OFDM system. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solutions is extremely high. We propose a heuristic subcarrier and power allocation algorithm to maximize the weighted sum-rate. The simulation results show that the proposed algorithm can significantly increase the spectral efficiency of the system. Furthermore, it is shown that LDS-OFDM system can achieve an outage probability much less than that for OFDMA system
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