Non-cooperative resource competition game by virtual referee in multi-cell OFDMA networks

Abstract

Abstract-In this paper, a distributive non-cooperative game is proposed to perform sub-channel assignment, adaptive modulation, and power control for multi-cell multi-user Orthogonal Frequency Division Multiplexing Access (OFDMA) networks. Each individual user's goal is to minimize his/her own transmitted power in a distributed manner under the constraints that the desirable rate is achieved and the transmitted power is bounded. The pure non-cooperative game may result in non-convergence or some undesirable Nash Equilibriums with low system and individual performances. To enhance the performances, a virtual referee is introduced to the networks and is in charge of monitoring and improving the outcome of non-cooperative competition for resources among the distributed users. If the game outcome is not desirable, either the required transmission rates should be reduced or some users should be prevented from using some radio resources such as sub-channels, so that the rest of users can share the limited resources more efficiently. Moreover, it can be shown that the introduction of the virtual referee does not increase the complexity of the networks. From the simulation results in a two-cell case, the proposed scheme reduces the transmitted power by 80% and 25% compared with the fixed channel assignment algorithm and the iterative water-filling algorithm in the literature, respectively. The achievable rate can be improved by 10%. In a multi-cell case, the proposed scheme can have up to 40% power reduction compared with the iterative water-filling algorithm when the co-channel interferences are severe.

Opportunistic distributed channel access for a dense wireless small‐cell zone

“…2a depicts (expected rate -ρ) vs. symmetric threshold h th for SUE 1. The expected rate of an SUE in G 1 is given by (8). The value of h th for which the expected rate is equal to ρ, is the solution of (12) and defines the unique equilibrium s sym th = h th of G 1 according to Theorem 1.…”

“…Similarly the cardinality of N −bi has binomial distribution with parameters N −bi and p exist . In (8) there are two values that depend on the distribution of cardinalities N bi {i} and N −bi . The probability of no collisionp sym 1 (N bik ) and the feasible SINR region D, both of which decrease as the number of SUEs in a cell increases.…”

“…Next we use these observations to simplify (7) [25]. Let us define the binomial random variable X ∼ B 1 (N −bi , q 1 (h th )), then the expected utility of player i for action T k and s sym −ith = (h th ) is given by (8) where j∈X g k j is the sum of X number of i.i.d. random variables g k j .…”

Game‐theoretic beamforming techniques for multiuser multi‐cell networks under mixed quality of service constraints

“…Accordingly, if the mixed QoS power allocation in (11) becomes infeasible during the first play round/ qualification stage, then only max-min problem will be used for both the RTUs and NRTUs of that corresponding BS. Alternatively, BS may opt to drop certain RTUs by solving the admission control problem [27]. As this totally excludes the dropped users from taking part in the bargaining process, this approach is not considered in this paper.…”

Economic Approaches for Cognitive Radio Networks: A Survey

“…In [7], a distributed non-cooperative game is proposed for joint subchannel assignment, adaptive modulation and power control for multi-cell multi-user OFDMA networks. In order to improve the performance of Nash equilibrium points, a virtual referee is introduced in the system that can modify the rule of the resource competition game for efficient resource sharing.…”