Power Allocation and Spectrum Sharing in Multi-User, Multi-Channel Systems With Strategic Users

Abstract

We consider the decentralized power allocation and spectrum sharing problem in multi-user, multichannel systems with strategic users. We present a mechanism/game form that has the following desirable features. (1) It is individually rational. (2) It is budget balanced at every Nash equilibrium of the game induced by the game form as well as off equilibrium. (3) The allocation corresponding to every Nash equilibrium (NE) of the game induced by the mechanism is a Lindahl allocation, that is, a weakly Pareto optimal allocation. Our proposed game form/mechanism achieves all the above desirable properties without any assumption about, concavity, differentiability, monotonicity, or quasi-linearity of the users' utility functions.

Dynamic Downlink Frequency and Power Allocation in OFDMA Cellular Networks

“…Thus, practical suboptimal methods need to be developed to perform resource allocations. In [12], the authors propose a game theoretic approach for the joint spectrum sharing and power allocation problem in non-cellular multi-user multi-channel systems, where users directly communicate with one another. The spectrum and power assignments in [13] are jointly determined according to secondary users' requirements in cognitive radio networks, which however cannot be directly applied to cellular networks either.…”

Efficient Network Sharing With Asymmetric Constraint Information

“…[19]), power allocation and spectrum sharing problem (e.g. [18]), networked public good [20], networked private good [21]. Sinha et al studied a relatively more general setting in [22], which is also a subclass of the problem that we study in this work.…”

“…In this section, we consider the fog-based user-provided network (UPN) as a concrete example of the DeNUM framework, to demonstrate the effectiveness of the DeNUM Mechanism, the DeNUM Algorithm, and the DyDeNUM Mechanism. Such 18 The relative error is defined as…”

“…Note that each agent initializes her price proposal p j,n [0] = C by the same constant in the DyDeNUM Mechanism. The algorithm iteratively computes each agent's message and action until convergence (lines [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. For each iteration, agents update their messages and actions in a Gauss-Seidel fashion (lines [6][7][8][9][10][11][12][13][14].…”

“…Second, existing mechanisms proposed for network resource allocation are often applicable to only specific networking scenarios (e.g. flow control problems [13]- [17], power and spectrum allocation [18], and electric vehicles systems [19]). These mechanisms often do not work for more general and sophisticated NUM Problems or the general network sharing framework.…”