A cellular neural network and utility-based radio resource scheduler for multimedia CDMA communication systems

Abstract

Abstract-The paper proposes a cellular neural network and utility (CNNU)-based radio resource scheduler for multimedia CDMA communication systems supporting differentiated quality-of-service (QoS). Here, we dene a relevant utility function for each connection, which is its radio resource function weighted by a QoS requirement deviation function and a fairness compensation function. We also propose cellular neural networks (CNN) to design the utility-based radio resource scheduler according to the Lyapunov method to solve the constrained optimization problem. The CNN is powerful for complicated optimization problems and has been proved that it can rapidly converge to a desired equilibrium; the utility-based scheduling algorithm can efciently utilize the radio resource for system, keep the QoS requirements of connections guaranteed, and provide the weighted fairness for connections. Therefore, the CNNUbased scheduler, which determines a radio resource assignment vector for all connections by maximizing an overall system utility, can achieve high system throughput and keep the performance measures of all connections to meet their QoS requirements. Simulation results show that the CNNU-based scheduler attains the average system throughput greater than the EXP [9] and the HOLPRO [5] scheduling schemes by an amount of 23% and 33%, respectively, in the QoS guaranteed region.Index Terms-Cellular neural networks (CNN), fairness, quality of service (QoS), radio resource, scheduling, utility function.

Delay constrained throughput optimised joint scheduling and link adaptation scheme based on imperfect channel state information

“…To this end, λ i and μ i , 1 ≤ i ≤ N are to be set during an iterative procedure according to (22) after iterations. Thus the required computational cost of this scheme is quite comparable with utility based scheduling in [1–15].…”

“…Thus the required computational cost of this scheme is quite comparable with utility based scheduling in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

“…To evaluate the performance of a system with discrete rates, the AMC transmission modes of the IEEE 802.11a standard are used. The parameters according to (11) are derived by curve fitting and listed in Table 1.…”

“…Moreover, delay constraints are to be provisioned for real time wireless applications such as multimedia. Utility based scheduling is a common solution in which different utility functions are assigned to the users based on their throughput requirements and delay constraints [1][2][3][4][5][6][7][8][9][10][11][12][13]. At each instant, a link with a maximum utility function is activated.…”

“…At each instant, a link with a maximum utility function is activated. Different utility functions are presented in [11, 12]. Utility function may depend on the backlogged data, queue length or imposed delay [13].…”