Distributed resource allocation with imperfect spectrum sensing information and channel uncertainty in cognitive femtocell networks

Abstract

To meet the ever-increasing demands of mobile traffic, femtocells are considered as one of the promising solutions. In this paper, we study a sensing-based resource allocation scenario in cognitive femtocell networks and present an efficient distributed imperfect-spectrum-sensing-based resource allocation (DIRA) algorithm while considering the channel uncertainty to maximize the total data rate of cognitive femtocell networks by jointly optimizing both subchannel assignment and power allocation taking into account the influence of the sensing accuracy. However, the general optimization problem turns out to be a mixed integer programming problem. In order to make it tractable, the original optimization problem is divided into two sub-optimization problems,namely,optimal subchannel allocation and optimal power allocation. Specifically, the proposed distributed fairness-based subchannel allocation (DFSA) algorithm guarantees fairness by introducing channel condition difference and satisfaction degree as the indicators of subchannel allocation. Additionally, optimal power allocation with the consideration of imperfect spectrum sensing and interference uncertainty is performed using the proposed chance-constrained power optimization (CPO) algorithm. Bernstein's approximation is conducted to make the chance constraint tractable. Simulation results illustrate that the distributed imperfect-spectrum-sensing-based resource allocation (DIRA) algorithm can provide considerable fairness among femtocells and at the same time maximize the total data rate of the cognitive femtocell network.

Model of dynamics of the grouping states of radio electronic means in the problems of ensuring electromagnetic compatibility

“…Despite the general problem of optimizing the radio frequency resource when using femtocells in a macro-network of mobile communications, the optimization problem is solved in [11], which combines two subtasks, namely, the optimal distribution of subchannels and the optimal power distribution of the REM of the macro-net and femtocells. To solve this problem of integer programming, an efficient resource allocation algorithm based on the distributed spectral sounding of the DIRA spectrum (Distributed Imperfect-Spectrum-Sensing-Based Resource Allocation) is proposed.…”

“…In the system of grouping REM during its operation, an appropriate redistribution of resources *( ) Y t is implemented, which is determined by models of stationary states described by the tasks of maximizing the entropy of the system [9][10][11] ( )…”

“…The formation of a model of the form (5) for a distribution process with constraints and heterogeneous resources remains an unresolved problem [9][10][11]. Let's manage to build such a model only for those cases when the dynamics of the distribution process is Markov, for the constraints of the balance type.…”

“…process is Markov [9][10][11], since it does not matter when and how the macro system transitioned in its current state, but only that the system uses the current time-frequency, polarization, time resource or spatial.…”