General Auction-Theoretic Strategies for Distributed Partner Selection in Cooperative Wireless Networks

TL;DR

This paper introduces auction-based strategies for selecting cooperative partners in wireless networks, balancing individual incentives and network fairness, with proven robustness under uncertainty.

Contribution

It develops novel auction mechanisms for partner selection in cooperative wireless networks, addressing asymmetrical channel conditions and limited information scenarios.

Findings

Achieves desired QoS for bidders while ensuring seller revenue.

Characterizes equilibrium outage probability and feedback bounds.

Demonstrates robustness of strategies under uncertainty.

Abstract

It is unrealistic to assume that all nodes in an ad hoc wireless network would be willing to participate in cooperative communication, especially if their desired Quality-of- Service (QoS) is achievable via direct transmission. An incentivebased auction mechanism is presented to induce cooperative behavior in wireless networks with emphasis on users with asymmetrical channel fading conditions. A single-object secondprice auction is studied for cooperative partner selection in singlecarrier networks. In addition, a multiple-object bundled auction is analyzed for the selection of multiple simultaneous partners in a cooperative orthogonal frequency-division multiplexing (OFDM) setting. For both cases, we characterize equilibrium outage probability performance, seller revenue, and feedback bounds. The auction-based partner selection allows winning bidders to achieve their desired QoS while compensating the seller who assists them. At the local level sellers aim for revenue maximization, while connections are drawn to min-max fairness at the network level. The proposed strategies for partner selection in self-configuring cooperative wireless networks are shown to be robust under conditions of uncertainty in the number of users requesting cooperation, as well as minimal topology and channel link information available to individual users.