100 research outputs found
Myopic Coding in Multiple Relay Channels
In this paper, we investigate achievable rates for data transmission from
sources to sinks through multiple relay networks. We consider myopic coding, a
constrained communication strategy in which each node has only a local view of
the network, meaning that nodes can only transmit to and decode from
neighboring nodes. We compare this with omniscient coding, in which every node
has a global view of the network and all nodes can cooperate. Using Gaussian
channels as examples, we find that when the nodes transmit at low power, the
rates achievable with two-hop myopic coding are as large as that under
omniscient coding in a five-node multiple relay channel and close to that under
omniscient coding in a six-node multiple relay channel. These results suggest
that we may do local coding and cooperation without compromising much on the
transmission rate. Practically, myopic coding schemes are more robust to
topology changes because encoding and decoding at a node are not affected when
there are changes at remote nodes. Furthermore, myopic coding mitigates the
high computational complexity and large buffer/memory requirements of
omniscient coding.Comment: To appear in the proceedings of the 2005 IEEE International Symposium
on Information Theory, Adelaide, Australia, September 4-9, 200
Optimal Routing for the Gaussian Multiple-Relay Channel with Decode-and-Forward
In this paper, we study a routing problem on the Gaussian multiple relay
channel, in which nodes employ a decode-and-forward coding strategy. We are
interested in routes for the information flow through the relays that achieve
the highest DF rate. We first construct an algorithm that provably finds
optimal DF routes. As the algorithm runs in factorial time in the worst case,
we propose a polynomial time heuristic algorithm that finds an optimal route
with high probability. We demonstrate that that the optimal (and near optimal)
DF routes are good in practice by simulating a distributed DF coding scheme
using low density parity check codes with puncturing and incremental
redundancy.Comment: Accepted and to be presented at the 2007 IEEE International Symposium
on Information Theory (ISIT 2007), Acropolis Congress and Exhibition Center,
Nice, France, June 24-29 200
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach
This paper investigates the price-based resource allocation strategies for
the uplink transmission of a spectrum-sharing femtocell network, in which a
central macrocell is underlaid with distributed femtocells, all operating over
the same frequency band as the macrocell. Assuming that the macrocell base
station (MBS) protects itself by pricing the interference from the femtocell
users, a Stackelberg game is formulated to study the joint utility maximization
of the macrocell and the femtocells subject to a maximum tolerable interference
power constraint at the MBS. Especially, two practical femtocell channel
models: sparsely deployed scenario for rural areas and densely deployed
scenario for urban areas, are investigated. For each scenario, two pricing
schemes: uniform pricing and non-uniform pricing, are proposed. Then, the
Stackelberg equilibriums for these proposed games are studied, and an effective
distributed interference price bargaining algorithm with guaranteed convergence
is proposed for the uniform-pricing case. Finally, numerical examples are
presented to verify the proposed studies. It is shown that the proposed
algorithms are effective in resource allocation and macrocell protection
requiring minimal network overhead for spectrum-sharing-based two-tier
femtocell networks.Comment: 27 pages, 7 figures, Submitted to JSA
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