Browsing by Author "Chiang, MY"

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Two-stage dynamic uplink channel and slot assignment for GPRS
(2003-09-01)
Hsu, YC
;
Lin, YD
;
Chiang, MY
;
資訊工程學系
;
Department of Computer Science
General packet radio service (GPRS) uses a two-stage mechanism to allocate uplink radio resource to mobile stations (MSs). In stage-1, the base station (BS) assigns several packet data channels (PDCHs) to an MS. Furthermore, a PDCH may be assigned to multiple MSs. In stage-2, therefore, the BS selects one of the multiplexed MSs in a PDCH to use the radio resource. In this paper, maintaining a load balance between PDCHs in stage-1 is examined and several selection schemes to lower the mis-selection rate in stage-2 are proposed. From our simulation results, the cost deduced from the poor load balancing and selection schemes render a lower system throughput and a non-negligible increase in packet queuing delay. Among the various stage-2 selection policies, round robin with linearly-accumulated adjustment (RRLAA) has the lowest mis-selection rate and outperforms the one without any heuristic by up to 50%.
Two-stage dynamic uplink channel and slot assignment for GPRS
(2001)
Lin, YD
;
Hsu, YC
;
Chiang, MY
;
資訊工程學系
;
Department of Computer Science
General Packet Radio Service (GPRS) uses a two-stage mechanism to allocate uplink radio resource to Mobile Stations (MSs). In stage-1, the Base Station (BS) assigns several Packet Data CHannels (PDCHs) to an MS. Furthermore, a PDCH may be assigned to multiple MSs. In stage-2, therefore, the BS selects one of the multiplexed MSs in a PDCH to use the radio resource. In this work, maintaining a load balance between PDCHs in stage-1 is examined and several selection schemes to lower the mis-selection rate in stage-2 are proposed. From our simulation results, the cost deduced from the poor load balancing and selection schemes render a lower system throughput and a non-negligible increase In packet queuing delay. Among the various stage-2 selection policies, Round Robin with Linearly-Accumulated Adjustment (RRLAA) has the lowest mis-selection rate and outperforms the one without any heuristic up to 50%.