Genetic algorithm aided timeslot scheduling for UTRA TDD CDMA networks

Abstract

It is demonstrated that genetic algorithms may be utilised for finding a suboptimum but highly beneficial uplink (UL) or downlink (DL) timeslot (TS) allocation for improving the achievable performance of the third generation UTRA system's time division duplex (TDD) mode. It is demonstrated that this novel GA-assisted UL=DL timeslot scheduling scheme is capable of avoiding the severe BS to BS intercell interference potentially inflicted by the UTRA TDD CDMA air interface owing to allowing all TSs to be used both in the UL and DL, hence potentially quadrupling the carried teletraffic and halving the uplink power.Introduction: Although the UTRA time division duplex (TDD) mode was contrived for the sake of improving the achievable network performance by assigning all the timeslots on a demand basis to the uplink (UL) and downlink (DL), this mode may result in an excessive BS-to-BS interference and hence in a potentially reduced number of system users. More explicitly, it was shown that the TDD mode is more prone to avalanche-like teletraffic overload and its carried teletraffic is up to a factor two lower than that of the FDD mode [1]. To mitigate this deficiency, in this Letter genetic algorithms (GAs) [2] are proposed for improving the achievable performance of the UTRA TDD mode, potentially quadrupling the teletraffic carried, and simultaneously halving the average uplink power consumption required.

An efficient local predictive method for distributed timeslot allocation in CDMA/TDD

“…We consider three types of previous schemes: Scheme 1 is a simulatedannealing-based heuristic used in [7], Scheme 2 is a genetic- algorithm-based heuristic similar to that of [7] except basic genetic operations [8], and Scheme 3 is a simple heuristic presented in [12]. In the cases of evolutionary algorithm, such as simulated annealing and genetic algorithm, typical stopping rules include bounding the number of iterations and bounding the rate of improvement at each iteration or during each set of iterations.…”