Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks

Abstract

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Collaborative Resource Management for Negotiable Multi-Operator Small Cell Networks

“…However, an increment in average system capacity would also depend upon the schemes used for resource allocations. To compare and evaluate the performance of multi-operator small cells collaboration with different resource allocation schemes, we considered the best-response (BR) strategy based different schemes, namely BR (Simultaneous), BR (Sequential), and marginal contribution-based best-response (MCBR) with neighborhood and complete information [40,41]. We averaged the performance for 200 randomly generated deployments of small cells that belong to the two MNOs in a cluster and its associated MSs.…”