LEARNING-BASED SEMI-PERSISTENT SCHEDULING IN WIRELESS COMMUNICATIONS
First Claim
1. A method comprising:
- scheduling in full a packet flow during a specific period of time;
collecting accumulation statistics of scheduled packet sizes (Ss) and inter-packet time intervals (Ts); and
identifying a set of peaks of highest accumulation;
when a number of {S, T} pairs contained within a tolerance size (D) of the peak is above a threshold, utilizing semi-persistent scheduling.
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Abstract
Systems and methods are provided for a learning-based determination of semi-persistent scheduling of data-packet flow wireless communication. A packetized data flow served to a wireless terminal is fully scheduled for an initial period of time in order to collect statistics associated with scheduled packet sizes (Ss) and inter-packet times (Ts). Analysis of a cumulative distribution of {S, T} pairs indicate whether a characteristic packet size (S0) and size dispersion (D0) are associated with the cumulative distribution. Inter-time intervals associated with the characteristic size and dispersion complete a transport format. Semi-persistent scheduling is utilized for a packetized flow when a characteristic transport format can be extracted, or learned, from the accumulated statistics. Extracted transport formats can be employed to optimize scheduling efficiency upon handover.
77 Citations
51 Claims
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1. A method comprising:
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scheduling in full a packet flow during a specific period of time; collecting accumulation statistics of scheduled packet sizes (Ss) and inter-packet time intervals (Ts); and
identifying a set of peaks of highest accumulation;when a number of {S, T} pairs contained within a tolerance size (D) of the peak is above a threshold, utilizing semi-persistent scheduling. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. An apparatus that operates in a wireless communication system, the apparatus comprising:
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a processor configured to schedule in full a packet flow;
to generate an accumulation distribution of scheduled packet sizes (Ss) and inter-packet time intervals (Ts); and
when a number of {S, T} pairs contained within a tolerance size (D) of a peak in the accumulation distribution is above a threshold, to implement semi-persistent scheduling; anda memory coupled to the processor. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. A wireless communication device comprising:
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means for accumulating distribution of fully scheduled packet sizes (Ss) and inter-packet time intervals (Ts); means for utilizing semi-persistent scheduling when a number of {S, T} pairs contained within a tolerance size (D) of a peak in the accumulation distribution is above a threshold; and means for utilizing semi-persistent scheduling when the accumulation statistics match a known statistics for data packets generated by a packet-flow generator, utilizing semi-persistent scheduling. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39, 40)
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41. A computer program product including a computer-readable medium comprising:
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code for causing a computer to schedule in full a packet flow; code for causing a computer to collect accumulation statistics over a specific period of time of fully scheduled packet sizes (Ss) and inter-packet time intervals (Ts); code for causing a computer to identify a set of peaks of highest accumulation; code for causing a computer to implement semi-persistent scheduling when a number of {S, T} pairs contained within a tolerance size (D) of the peak is above a threshold. - View Dependent Claims (42, 43, 44, 45, 46, 47, 48, 49, 51)
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50. The computer program product of claim 50, wherein the concatenation of S0 and D, and τ
- comprise a transport format for semi-persistent scheduling of the packet flow.
Specification