Channel based adaptive resource allocation at the MAC layer in UMTS TD-CDMA systems

Abstract

In this paper we propose a scheduling strategy at MAC level for the TDDflCDMA UMTS Third Generation air intelface. More precisely, we consider the uplink of a singlecell pedestrian outdoor scenario.Wthin this context we investigate the advantage of scheduling the direrent services that can be offered to the system, characterized by different quality and delay requirements, taking both the service priority and the channel state into account.The characteristics of the TDDflCDMA transmission system, the power control algorithm and a frequency selective fading channel are considered in our approach, which is semi-analytical and allows the evaluation of the statistics of the Frame Error Rate and the average transmitted power per &a unit, which is a measure of eflciency from the energy management point of view.The pelformunce of the scheduling algorithm we propose is compared to a more traditional scheduling approach which takes only the priority of services into account.

Optimal energy allocation for delay-constrained data transmission over a time-varying channel

“…Ferracioli et al [5] propose a scheduling scheme for the third generation cellular air interface standard that takes channel state into account and seeks to balance service priority and energy efficiency. Wong et al [17] study channel allocation algorithms for cellular base stations.…”

Wide-Band TD-CDMA MAC With Minimum-Power Allocation and Rate- and BER-Scheduling for Wireless Multimedia Networks

“…If denotes the number of code channels of all mobile terminals in a time slot, it is given by (10) When minimum-power allocation is used, must satisfy the constraint in (9). As a result, in order to maximize , we need to solve the following optimization problem: Find a vector that satisfies (11) and maximizes the objective function in (10). According to the theory of linear programming, is maximized at one of the extreme points given by (11).…”

“…As a result, in order to maximize , we need to solve the following optimization problem: Find a vector that satisfies (11) and maximizes the objective function in (10). According to the theory of linear programming, is maximized at one of the extreme points given by (11). By investigating (11), we know the set of extreme points consists of .…”

“…Power levels of all code channels are assumed to be equal in WISPER, i.e., the power levels are not minimized. Although power control is used in [11] to determine the transmitted power levels of mobile terminals in Universal Mobile Telecommunication System (UMTS) TD-CDMA networks, the capacity of a time slot is assumed to be fixed. The resource allocation algorithm in [12] considers different received power levels for various service types, but the power level of a service type is assumed to be fixed.…”

Dynamic reconfiguration and routing algorithms for IP-over-WDM networks with stochastic traffic

“…Ferracioli et al [8] propose a scheduling scheme for the third generation cellular air interface standard that takes channel state into account and seeks to balance service priority and energy efficiency. Wong et al [9] study channel allocation algorithms for cellular base stations.…”