1,311 research outputs found
Communicating Using an Energy Harvesting Transmitter: Optimum Policies Under Energy Storage Losses
In this paper, short-term throughput optimal power allocation policies are
derived for an energy harvesting transmitter with energy storage losses. In
particular, the energy harvesting transmitter is equipped with a battery that
loses a fraction of its stored energy. Both single user, i.e. one
transmitter-one receiver, and the broadcast channel, i.e., one
transmitter-multiple receiver settings are considered, initially with an
infinite capacity battery. It is shown that the optimal policies for these
models are threshold policies. Specifically, storing energy when harvested
power is above an upper threshold, retrieving energy when harvested power is
below a lower threshold, and transmitting with the harvested energy in between
is shown to maximize the weighted sum-rate. It is observed that the two
thresholds are related through the storage efficiency of the battery, and are
nondecreasing during the transmission. The results are then extended to the
case with finite battery capacity, where it is shown that a similar
double-threshold structure arises but the thresholds are no longer monotonic. A
dynamic program that yields an optimal online power allocation is derived, and
is shown to have a similar double-threshold structure. A simpler online policy
is proposed and observed to perform close to the optimal policy.Comment: Submitted to IEEE Transactions on Wireless Communications, August
201
On Resource Allocation in Fading Multiple Access Channels - An Efficient Approximate Projection Approach
We consider the problem of rate and power allocation in a multiple-access
channel. Our objective is to obtain rate and power allocation policies that
maximize a general concave utility function of average transmission rates on
the information theoretic capacity region of the multiple-access channel. Our
policies does not require queue-length information. We consider several
different scenarios. First, we address the utility maximization problem in a
nonfading channel to obtain the optimal operating rates, and present an
iterative gradient projection algorithm that uses approximate projection. By
exploiting the polymatroid structure of the capacity region, we show that the
approximate projection can be implemented in time polynomial in the number of
users. Second, we consider resource allocation in a fading channel. Optimal
rate and power allocation policies are presented for the case that power
control is possible and channel statistics are available. For the case that
transmission power is fixed and channel statistics are unknown, we propose a
greedy rate allocation policy and provide bounds on the performance difference
of this policy and the optimal policy in terms of channel variations and
structure of the utility function. We present numerical results that
demonstrate superior convergence rate performance for the greedy policy
compared to queue-length based policies. In order to reduce the computational
complexity of the greedy policy, we present approximate rate allocation
policies which track the greedy policy within a certain neighborhood that is
characterized in terms of the speed of fading.Comment: 32 pages, Submitted to IEEE Trans. on Information Theor
Partially-Distributed Resource Allocation in Small-Cell Networks
We propose a four-stage hierarchical resource allocation scheme for the
downlink of a large-scale small-cell network in the context of orthogonal
frequency-division multiple access (OFDMA). Since interference limits the
capabilities of such networks, resource allocation and interference management
are crucial. However, obtaining the globally optimum resource allocation is
exponentially complex and mathematically intractable. Here, we develop a
partially decentralized algorithm to obtain an effective solution. The three
major advantages of our work are: 1) as opposed to a fixed resource allocation,
we consider load demand at each access point (AP) when allocating spectrum; 2)
to prevent overloaded APs, our scheme is dynamic in the sense that as the users
move from one AP to the other, so do the allocated resources, if necessary, and
such considerations generally result in huge computational complexity, which
brings us to the third advantage: 3) we tackle complexity by introducing a
hierarchical scheme comprising four phases: user association, load estimation,
interference management via graph coloring, and scheduling. We provide
mathematical analysis for the first three steps modeling the user and AP
locations as Poisson point processes. Finally, we provide results of numerical
simulations to illustrate the efficacy of our scheme.Comment: Accepted on May 15, 2014 for publication in the IEEE Transactions on
Wireless Communication
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