CN108494525B - Self-adaptive selection method for combining repetition times and transmission block size in NB-IoT (NB-IoT) - Google Patents

Self-adaptive selection method for combining repetition times and transmission block size in NB-IoT (NB-IoT) Download PDF

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CN108494525B
CN108494525B CN201810184497.5A CN201810184497A CN108494525B CN 108494525 B CN108494525 B CN 108494525B CN 201810184497 A CN201810184497 A CN 201810184497A CN 108494525 B CN108494525 B CN 108494525B
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黄磊
韩圣千
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0006—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission format
    • H04L1/0007—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission format by modifying the frame length
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/12—Arrangements for detecting or preventing errors in the information received by using return channel
    • H04L1/16—Arrangements for detecting or preventing errors in the information received by using return channel in which the return channel carries supervisory signals, e.g. repetition request signals
    • H04L1/18—Automatic repetition systems, e.g. Van Duuren systems
    • H04L1/1867—Arrangements specially adapted for the transmitter end
    • H04L1/189—Transmission or retransmission of more than one copy of a message

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Abstract

The invention discloses a self-adaptive selection method for combining repetition times and transmission block sizes in a narrowband Internet of things, and belongs to the technical field of wireless communication. The self-adaptive selection method comprises the steps of respectively determining the size of a transmission block and the self-adaptive threshold of recalculation times; then realizing the self-adaptation of the repetition times and the transmission blocks respectively; until all data is transferred. Aiming at any given uplink or downlink time frequency resource allocation, the invention realizes the combined optimization of the transmission block size self-adaption on a small time scale and the repetition times self-adaption on a large time scale; compared with the existing two-separation design, the method can effectively eliminate the problem of sudden throughput drop caused by repeated hard switching, and remarkably improve the transmission rate of the system.

Description

Self-adaptive selection method for combining repetition times and transmission block size in NB-IoT (NB-IoT)
Technical Field
The invention belongs to the technical field of wireless communication, and relates to a self-adaptive selection method combining the repetition times and the Size of a Transmission Block (TBS) in a Narrowband Internet of Things (Narrowband-Internet of Things, NB-IoT).
Background
The 3GPP, 6 months 2016, first proposed NB-IoT access technology in LTE R13 release. As a promising new radio access technology, NB-IoT may coexist with already deployed GSM, LTE, etc. networks. Compared with Machine Type Communication (MTC), NB-IoT has wider coverage, extremely low power consumption, capability of deploying a large number of terminals, lower data rate requirements, occupying a very narrow frequency band (200kHz), and the like, and may be deployed in resource blocks that are not used within an LTE subcarrier guard interval, or may be deployed in a frequency band other than LTE alone. See in particular reference [1]3GPP 36.888, Study on provisioning of low-cost Machine-Type Communications (MTC) UEs based on LTE. Reference [2] J.Gozalvez, "New 3GPP Standard for IoT [ Mobile Radio ]," in IEEE Vehicular Technology Magazine, vol.11, No.1, pp.14-20, March 2016. Reference [3] S.Landstrm, J.Bergstrm, E.Westerberg, D.Hammarwall, "NB-IoT: A sustamable Technology for connecting biolistics of devices," in Ericsson Technology Review, vol.93, No.3, pp.2-11, April 2016.
To extend coverage, NB-IoT systems employ two link adaptation techniques, namely, repetition number and transport block size adaptive selection. The selection of the size of the transmission block is an adaptive technology based on small-scale channel information, and the size of the transmission block can rapidly adjust the modulation and coding mode of transmission at millisecond level according to the change of a channel, so as to change the number of data bits contained in each transmission block. For example, when the channel quality is poor, a lower modulation order and coding rate is selected, which results in a smaller transport block; when the channel quality is better, a higher modulation order and coding rate can be selected, and a larger transmission block is generated. The repetition times refer to the repetition of the original data, and the signal to noise ratio of the receiving end is improved by increasing the data redundancy. Unlike the adaptive selection of the size of the transmission block, the adaptation of the number of repetitions is an adaptive technique on a larger time scale, which affects the transmission frame structure, the pilot insertion manner, etc. of the system, and therefore cannot be adjusted quickly with small-scale channels. In the existing industry, the adaptation of the repetition times is provided on the premise of not adopting the adaptation of the size of a transmission block, only the edge signal-to-noise ratio of a network is considered, when the edge signal-to-noise ratio is low, the repetition times are increased to reduce the error rate, and when the edge signal-to-noise ratio is high, the repetition times can be reduced on the premise of ensuring the error rate.
When the number of repetitions and the size of the transmission block are considered to be adaptively adjusted, for a lower edge signal-to-noise ratio, the error rate can be reduced by increasing the number of repetitions, or the size of the transmission block can be reduced and coupled with each other; this coupling relationship also exists for higher edge snr scenarios. At this point, the number of repetitions of the split design and transport block size adaptation no longer apply.
Disclosure of Invention
The invention provides a self-adaptive selection method for combining the repetition times and the size of a transmission block in NB-IoT (NB-IoT) to solve the problem of expanding the coverage range of uplink and downlink data transmission under a time-varying channel of the NB-IoT. The self-adaptive selection method comprises the following steps:
first, an adaptive threshold for the transport block size is determined.
And secondly, determining an adaptive threshold of recalculation times.
And thirdly, realizing the self-adaption of the repetition times.
And fourthly, realizing the self-adaptation of the transmission block.
And fifthly, finishing data transmission.
And repeating the third step to the fourth step until all data is transmitted.
The invention has the advantages that:
aiming at any given uplink or downlink time-frequency resource allocation, the size self-adaption of a transmission block on a small time scale and the self-adaption joint optimization of the repeated times on a large time scale are realized; compared with the existing two-separation design, the method can effectively eliminate the problem of sudden throughput drop caused by repeated hard switching, and remarkably improve the transmission rate of the system.
Drawings
Fig. 1 is a flowchart of an adaptive selection method combining the number of repetitions and the transport block size in NB-IoT according to the present invention.
Fig. 2 is a timing chart of a downlink data channel when the number of repetitions is 1.
Fig. 3 shows simulation results of the repetition number adaptation.
Fig. 4 is a simulation result of channel throughput.
Fig. 5 is a simulation result of the hard handoff for the number of repetitions.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
The self-adaptive selection method for combining the repetition times and the transport block size TBS in the narrowband Internet of things NB-IoT, disclosed by the invention, as shown in the flow chart of fig. 1, comprises the following steps:
first, an adaptive threshold for the transport block size is determined.
Giving an uplink or downlink data channel of an NB-IoT system, and under each possible repetition frequency (denoted as R, and the value set of R is R), obtaining a relation curve of a Block error rate (BLER) and a signal-to-noise ratio (SNR) of each transmission Block size under an additive white Gaussian channel by adopting a Monte Carlo simulation method, wherein the size of the transmission Block is uniquely determined by a TBS number i and a time-frequency resource number j in a TBS table and denoted as BijAnd the value sets of I and J are respectively I and J. Further, aiming at the transmissionTransport block size BijIn the case of (1), the SNR corresponding to 10% BLER is obtained, and represents that the number of repetitions is r and the transport block size is BijThe adaptive threshold of the corresponding transport block size is recorded as
Figure GDA0002637183230000031
The unit is dB.
And secondly, determining an adaptive threshold of recalculation times.
Firstly, the allocated time frequency resource and the repetition times, namely r and j, are fixed, and B of the sending end is used for simulating each timeij(I ∈ I) is determined by the equivalent SNR (equivalent SNR represents the lowest transmission SNR on the premise that BLER meets the transmission requirement) by: when r and j are fixed, all of the first step are selected
Figure GDA0002637183230000032
Not more than the equivalent SNR, all of which satisfy the condition
Figure GDA0002637183230000033
Corresponding to BijFrom B satisfying the conditionijThe largest value is selected for transmission. The equivalent SNR is obtained by the receiving end through channel estimation and is fed back to the transmitting end. And counting the total bit number which is transmitted correctly, and dividing the total bit number by the total transmission time to obtain the throughput. And changing the SNR, and continuing to perform simulation to obtain a change relation curve of the throughput and the SNR when the repetition times r and the time-frequency resource j are fixed. And then changing the repetition times r, and continuously repeating the process to obtain a change relation curve of the throughput and the SNR corresponding to different repetition times when the time-frequency resource j is fixed.
And after obtaining the change relation curve of the throughput and the SNR under different repetition times, selecting the repetition time with the maximum throughput under each SNR as the optimal repetition time of the transmission data under the SNR. The optimal number of repetitions changes when the SNR passes certain threshold values, and the zero boundary of these SNRs is the adaptive threshold for the number of repetitions, denoted SRjkJ represents the number of the time-frequency resource, K represents the number of the adaptive threshold when the time-frequency resource is fixed, and the value set of K is K.
And thirdly, realizing the self-adaption of the repetition times.
In the process of actually transmitting data, when the time frequency resource j allocated in the uplink or the downlink is known, and when the average SNR of an actual transmission channel is known, the self-adaptive threshold SR according to the repetition timesjkThe adaptive threshold for SNR between some two adjacent repetition times, SR, can be obtainedjk≤SNR<SRj(k+1)Further, the optimal repetition number under the SNR can be uniquely determined, and the self-adaption of the repetition number is realized.
And fourthly, realizing the self-adaption of the size of the transmission block.
After the repetition number r used by data transmission is determined, the self-adaptive threshold of the size of the transmission block with the repetition number r can be obtained
Figure GDA0002637183230000034
A set of (a). Then, the equivalent SNR obtained according to the channel estimation of the receiving end is compared with
Figure GDA0002637183230000035
Making a comparison, selecting all of the SNR not greater than the equivalent SNR
Figure GDA0002637183230000036
Corresponding to BijOf the largest one BijValue is recorded as B'ijFor actual transmission.
And fifthly, finishing data transmission.
And repeating the third step to the fourth step until all data is transmitted.
Examples
The present invention provides an adaptive selection method for combining the number of repetitions and TBS in NB-IoT, and a flowchart thereof is shown in fig. 1. And the example simulation uses a matlab simulation platform to perform simulation analysis on the actual effect of the method.
For downlink data transmission of narrowband internet of things, TBS table (namely B) of the downlink data transmission methodij) As shown in table 1 below:
table 1 TBS table for downlink data channel
Figure GDA0002637183230000041
As can be seen from table 1 above, the set I is {0,1,2,3,4,5,6,7,8,9,10,11,12}, and the set J is {0,1,2,3,4,5,6,7 }.
The simulation takes downlink data transmission as an example, the number of occupied subframes is 3, i.e. the frequency resource number j is 2, and the set of repetition times R is {1,2,4,8,16,32 }. One subframe has a time domain length of 1 millisecond (ms), and its downlink timing is limited as follows according to NB-IoT standard [1 ]:
(1) after the transmission of the narrowband downlink control channel (NPDCCH) is finished, the transmission of the narrowband downlink data channel (NPDSCH) needs to be carried out at an interval of 4 ms;
(2) after the transmission of the narrow-band downlink data channel is finished, the transmission of an uplink control channel (NPUCCH) carrying ACK/NACK information needs to be carried out at an interval of 12 ms;
(3) after the transmission of the uplink control channel is finished, the transmission of the next downlink control channel is continued at least 3 ms;
(4) the downlink control channel must be transmitted on the sub-frame with the sub-frame number of multiple of 8, otherwise, the downlink control channel needs to wait until the next sub-frame with the sub-frame number of multiple of 8.
The number of repetitions of the downlink control channel is set to be the same as the number of repetitions of the downlink data channel. An example of a downlink data channel timing when the number of repetitions is 1 is shown in fig. 2. In fig. 2, SF denotes a subframe number, BS denotes a base station, and UE denotes a user. According to the above principle, it is possible to obtain:
(1) when the repetition times is 1, the time length of transmitting data once is 32 ms;
(2) when the repetition number is 2, the time length of transmitting data once is 32 ms;
(3) when the repetition times are 4, the time length of transmitting data for one time is 40 ms;
(4) when the repetition number is 8, the time length for transmitting data once is 56 ms;
(5) when the repetition number is 16, the time length for transmitting data once is 88 ms;
(6) when the number of repetitions is 32, the duration of one-time data transmission is 152 ms.
The specific implementation steps are as follows:
step 1, determining a self-adaptive threshold of the size of a transmission block.
The time frequency resource label j is fixed as 2, and the self-adaptive switching threshold to be determined at the moment is
Figure GDA0002637183230000051
Where i is {0,1,2,3,4,5,6,7,8,9,10,11,12} and r is {1,2,4,8,16,32}, all threshold values are obtained by simulation according to the first step in the embodiments
Figure GDA0002637183230000052
Table 2 gives all r ═ 1 as an example
Figure GDA0002637183230000053
The result of the values is in dB.
Table 2 all when r is 1
Figure GDA0002637183230000054
Value of
Figure GDA0002637183230000055
And 2, determining the self-adaptive threshold of the recalculation times.
When obtaining
Figure GDA0002637183230000056
Thereafter, according to a second step in the specific embodiment, an adaptive threshold SR for the corresponding recalculation times may be determinedjk。
Figure 3 shows the signal-to-noise ratio on the horizontal axis and the throughput on the vertical axis, from which it can be seen that the adaptive threshold SR for the number of recalculations is2kA total of 4, each being SR21＝-3.7dB，SR22＝-1.2dB，SR23＝1.8dB，SR246.7 dB. To ensure maximum throughput at different SNRs, when the SNR is less than SR21Then, the optimal number of repetitions is 32; when SNR is greater than SR21dB less than SR22In dB, the optimal repetition number is 16; when SNR is greater than SR22dB less than SR23In dB, the optimal repetition frequency is 8; when SNR is greater than SR23dB less than SR24In dB, the optimal repetition frequency is 4; when SNR is greater than SR24In dB, the optimal number of repetitions is 2.
And 3, completing the transmission of all data.
In this step, a thousand Monte Carlo simulations are performed at each SNR, and transmission of all data is completed according to the third and fourth steps in the specific embodiment. The average throughput under each signal-to-noise ratio is counted, a curve of the throughput changing along with the SNR is obtained as shown in fig. 4, and the simulation result of the hard handoff with the number of times of repetition is shown in fig. 5. Therefore, compared with the prior hard handover with the repetition times, the adaptive transmission technology with the combined optimization of the repetition times and the TBS can effectively solve the problem of sudden throughput drop and can fully utilize resources for data transmission.

Claims (1)

1. An adaptive selection method for combining the repetition number and the transport block size in NB-IoT (NB-IoT), comprising the following steps: comprises the following steps of (a) carrying out,
firstly, determining a self-adaptive threshold of the size of a transmission block;
in particular to a method for preparing a high-performance nano-silver alloy,
giving an uplink or downlink data channel of an NB-IoT system, and under each possible repetition frequency, obtaining a relation curve of the transmission block error rate and the signal-to-noise ratio of each transmission block size under an additive white Gaussian channel by adopting a Monte Carlo simulation method, wherein the size of the transmission block is uniquely determined by a TBS number i and a time-frequency resource number j in a TBS table and is marked as BijI and J, and the value sets of the I and the J are respectively I and J; set I ═ 0,1,2,3,4,5,6,7,8,9,10,11,12, and set J ═ 0,1,2,3,4,5,6, 7;
the TBS table is:
Figure FDA0002659195100000011
further, for a transport block size of BijIn the case of (1), the SNR corresponding to 10% BLER is obtained, and represents that the number of repetitions is r and the transport block size is BijThe adaptive threshold of the corresponding transport block size is recorded as
Figure FDA0002659195100000012
The unit is dB;
secondly, determining a self-adaptive threshold of the repetition times;
in particular to a method for preparing a high-performance nano-silver alloy,
firstly, the allocated time frequency resource and the repetition times, namely r and j, are fixed, and B of the sending end is used for simulating each timeijThe equivalent signal-to-noise ratio SNR is determined by the following method: when r and j are fixed, all of the first step are selected
Figure FDA0002659195100000021
Not more than the equivalent SNR, all of which satisfy the condition
Figure FDA0002659195100000022
Corresponding to BijFrom B satisfying the conditionijSelecting the maximum value for transmission; the equivalent SNR is obtained by the receiving end through channel estimation and is fed back to the transmitting end; counting the total bit number which is transmitted correctly, and dividing the total bit number by the total transmission time to obtain the throughput; changing the SNR, and continuing simulation to obtain a change relation curve of the throughput and the SNR when the repetition times r and the time-frequency resource j are fixed; changing the repetition times r, and continuously repeating the process to obtain a change relation curve of the throughput and the SNR corresponding to different repetition times when the time-frequency resource j is fixed; selecting the repetition number corresponding to the maximum throughput under each SNR as the optimal repetition number of the transmission data under the SNR, wherein the optimal repetition number changes when the SNR passes through certain critical point values, and the critical point values of the SNR are the self-adaptive threshold of the repetition numberIs denoted as SRjkJ represents the number of the time-frequency resource, K represents the number of the adaptive threshold when the time-frequency resource is fixed, and the value set of K is K;
thirdly, realizing the self-adaption of the repetition times; in the process of actually transmitting data, when the time frequency resource j allocated in the uplink or the downlink is known, and when the average SNR of an actual transmission channel is known, the self-adaptive threshold SR according to the repetition timesjkObtaining an adaptive threshold for SNR between some two adjacent repetition times, i.e. SRjk≤SNR<SRj(k+1)Further, the optimal repetition times under the SNR are uniquely determined, and the self-adaption of the repetition times is realized;
fourthly, realizing the self-adaptation of the transmission block;
in particular to a method for preparing a high-performance nano-silver alloy,
after the repetition number r used by data transmission is determined, the self-adaptive threshold of the size of the transmission block with the repetition number r is obtained
Figure FDA0002659195100000023
I ∈ I; then, the equivalent SNR obtained according to the channel estimation of the receiving end is compared with
Figure FDA0002659195100000024
Making a comparison, selecting all of the SNR not greater than the equivalent SNR
Figure FDA0002659195100000025
Corresponding to BijOf the largest one BijValue is recorded as B'ijFor actual transmission;
fifthly, completing data transmission;
and repeating the third step to the fourth step until all data is transmitted.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101207461A (en) * 2007-12-10 2008-06-25 华为技术有限公司 Method and apparatus for self-adapting regulation of threshold value
CN101754267A (en) * 2008-12-09 2010-06-23 中兴通讯股份有限公司 Link self-adaption transmission method and equipment
CN104468048A (en) * 2014-12-15 2015-03-25 武汉理工大学 Method for determining HAR Q-I type available AMC scheme according to retransmission and combination method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101207461A (en) * 2007-12-10 2008-06-25 华为技术有限公司 Method and apparatus for self-adapting regulation of threshold value
CN101754267A (en) * 2008-12-09 2010-06-23 中兴通讯股份有限公司 Link self-adaption transmission method and equipment
CN104468048A (en) * 2014-12-15 2015-03-25 武汉理工大学 Method for determining HAR Q-I type available AMC scheme according to retransmission and combination method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Uplink scheduling and link adaptation for Narrowband Internet of Things systems;Changsheng Yu 等;《IEEE》;20170206;第1724-1734页 *

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