13,350 research outputs found
Analysis of a Cooperative Strategy for a Large Decentralized Wireless Network
This paper investigates the benefits of cooperation and proposes a relay
activation strategy for a large wireless network with multiple transmitters. In
this framework, some nodes cooperate with a nearby node that acts as a relay,
using the decode-and-forward protocol, and others use direct transmission. The
network is modeled as an independently marked Poisson point process and the
source nodes may choose their relays from the set of inactive nodes. Although
cooperation can potentially lead to significant improvements in the performance
of a communication pair, relaying causes additional interference in the
network, increasing the average noise that other nodes see. We investigate how
source nodes should balance cooperation vs. interference to obtain reliable
transmissions, and for this purpose we study and optimize a relay activation
strategy with respect to the outage probability. Surprisingly, in the high
reliability regime, the optimized strategy consists on the activation of all
the relays or none at all, depending on network parameters. We provide a simple
closed-form expression that indicates when the relays should be active, and we
introduce closed form expressions that quantify the performance gains of this
scheme with respect to a network that only uses direct transmission.Comment: Updated version. To appear in IEEE Transactions on Networkin
Power Allocation for Adaptive OFDM Index Modulation in Cooperative Networks
In this paper, we propose a power allocation strategy for the adaptive
orthogonal frequency-division multiplexing (OFDM) index modulation (IM) in
cooperative networks. The allocation strategy is based on the
Karush-Kuhn-Tucker (KKT) conditions, and aims at maximizing the average network
capacity according to the instantaneous channel state information (CSI). As the
transmit power at source and relay is constrained separately, we can thus
formulate an optimization problem by allocating power to active subcarriers.
Compared to the conventional uniform power allocation strategy, the proposed
dynamic strategy can lead to a higher average network capacity, especially in
the low signal-to-noise ratio (SNR) region. The analysis is also verified by
numerical results produced by Monte Carlo simulations. By applying the proposed
power allocation strategy, the efficiency of adaptive OFDM IM can be enhanced
in practice, which paves the way for its implementation in the future,
especially for cell-edge communications
Decentralized Delay Optimal Control for Interference Networks with Limited Renewable Energy Storage
In this paper, we consider delay minimization for interference networks with
renewable energy source, where the transmission power of a node comes from both
the conventional utility power (AC power) and the renewable energy source. We
assume the transmission power of each node is a function of the local channel
state, local data queue state and local energy queue state only. In turn, we
consider two delay optimization formulations, namely the decentralized
partially observable Markov decision process (DEC-POMDP) and Non-cooperative
partially observable stochastic game (POSG). In DEC-POMDP formulation, we
derive a decentralized online learning algorithm to determine the control
actions and Lagrangian multipliers (LMs) simultaneously, based on the policy
gradient approach. Under some mild technical conditions, the proposed
decentralized policy gradient algorithm converges almost surely to a local
optimal solution. On the other hand, in the non-cooperative POSG formulation,
the transmitter nodes are non-cooperative. We extend the decentralized policy
gradient solution and establish the technical proof for almost-sure convergence
of the learning algorithms. In both cases, the solutions are very robust to
model variations. Finally, the delay performance of the proposed solutions are
compared with conventional baseline schemes for interference networks and it is
illustrated that substantial delay performance gain and energy savings can be
achieved
Opportunistic Relay Selection with Limited Feedback
It has been shown that a decentralized relay selection protocol based on
opportunistic feedback from the relays yields good throughput performance in
dense wireless networks. This selection strategy supports a hybrid-ARQ
transmission approach where relays forward parity information to the
destination in the event of a decoding error. Such an approach, however,
suffers a loss compared to centralized strategies that select relays with the
best channel gain to the destination. This paper closes the performance gap by
adding another level of channel feedback to the decentralized relay selection
problem. It is demonstrated that only one additional bit of feedback is
necessary for good throughput performance. The performance impact of varying
key parameters such as the number of relays and the channel feedback threshold
is discussed. An accompanying bit error rate analysis demonstrates the
importance of relay selection.Comment: 5 pages, 6 figures, to appear in Proceedings of 2007 IEEE Vehicular
Technology Conference-Spring in Dublin, Irelan
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