CN111131100A - NBIOT system multi-cell iterative interference cancellation detection method - Google Patents

NBIOT system multi-cell iterative interference cancellation detection method Download PDF

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CN111131100A
CN111131100A CN201911370607.8A CN201911370607A CN111131100A CN 111131100 A CN111131100 A CN 111131100A CN 201911370607 A CN201911370607 A CN 201911370607A CN 111131100 A CN111131100 A CN 111131100A
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frequency domain
sss signal
sss
steps
interference cancellation
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CN111131100B (en
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景振海
李宇
丁杰伟
张为民
周俊
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Jiangsu Keda Hengxin Semiconductor Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03821—Inter-carrier interference cancellation [ICI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/005—Interference mitigation or co-ordination of intercell interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0069—Cell search, i.e. determining cell identity [cell-ID]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/08—Access restriction or access information delivery, e.g. discovery data delivery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03592—Adaptation methods
    • H04L2025/03598—Algorithms
    • H04L2025/03611—Iterative algorithms

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Computer Security & Cryptography (AREA)
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  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a NBIOT system multi-cell iterative interference cancellation detection method, which comprises the following steps: initializing an iteration counter lambda to be 0 and simultaneously generating a local SSS signal set, and extracting 12 subcarrier signals r on 11 symbols of a frequency domain as frequency domain receiving SSS signals; cross-correlating the frequency domain received SSS signals with a local SSS signal set; performing peak value threshold-crossing detection on the obtained cross-correlation value; performing LS channel estimation on the frequency domain receiving SSS signals which pass through the threshold, and further obtaining the channel response of LS; regenerating the ID receiving SSS signal according to the obtained channel response and the detected ID local SSS signal; and step S20 is re-entered as a new frequency domain received SSS signal after subtracting the ID received SSS signal from the frequency domain received SSS signal, and the iteration is performed until all the specified neighbor cells are detected completely or the maximum number of iterative detections is reached. The invention can accurately detect a plurality of neighbor cells in a plurality of cells and reduce false alarm and missed detection probability, and can obviously reduce the detection SINR threshold of the neighbor cells by adopting an iteration method.

Description

NBIOT system multi-cell iterative interference cancellation detection method
Technical Field
The invention relates to the technical field of communication, in particular to a NBIOT system multi-cell iterative interference cancellation detection method.
Background
The narrowband internet of things (NB-IoT) is a cellular communication system with low cost, large capacity, low power consumption, and wide coverage, and is receiving more and more attention in the industry as the internet of things is in large-scale application and is developing.
The first step of NB IoT communication is initial cell search, and after obtaining time synchronization and frequency synchronization, performs cell ID search synchronization using SSS, including: a serving cell search and a subsequent neighbor cell search. In the existing neighbor cell ID search synchronization method, a local SSS signal set constructed by a terminal and a received SSS signal are mutually correlated, and several peak values with the largest correlation value are selected for threshold detection to obtain a plurality of neighbor cell IDs and realize neighbor cell synchronization. Since the peak values are different in size, that is, the SINR of the SSS signal of each detected neighbor cell is different, the threshold of the conventional method is not easy to be determined, which easily causes a false alarm or missed detection.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a multi-cell iterative interference cancellation detection method of an NBIOT system, which can accurately detect a plurality of neighbor cells in a plurality of cells and reduce false alarm and missed detection probability. The technical scheme is as follows:
a NBIOT system multi-cell iterative interference cancellation detection method comprises the following steps:
s10, initializing an iteration counter lambda to be 0, simultaneously generating a local SSS signal set, and extracting 12 subcarrier signals r on 11 symbols of a frequency domain as frequency domain receiving SSS signals after obtaining cell time-frequency synchronization;
s20, performing cross correlation on the frequency domain receiving SSS signals and a local SSS signal set;
s30, performing peak value threshold-crossing detection on the obtained cross-correlation value;
s40, performing LS channel estimation on the SSS signals received by the frequency domain which pass the threshold, and further obtaining the channel response of LS;
s50, regenerating the ID receiving SSS signal according to the obtained channel response and the detected ID local SSS signal;
and S60, subtracting the ID receiving SSS signal from the frequency domain receiving SSS signal, and then re-entering the step S20 as a new frequency domain receiving SSS signal, and iterating until the detection of all specified adjacent cells is completed or the maximum iteration detection times is reached.
As a further improvement of the present invention, the set of local SSS signals is:
xi,j＝[x0,i,j,x1,i,j,...,x131,i,j]T
i＝0,1,2,3
j＝0,1,...,503
the frequency domain received SSS signal is: r ═ r0,r1,...,r131]T。
As a further improvement of the present invention, the step S20 specifically includes:
Figure BDA0002339566160000021
Figure BDA0002339566160000022
i＝0,1,2,3
j＝0,1,...,503
wherein the content of the first and second substances,
Figure BDA0002339566160000023
the reconstructed signal output for the lambda-1 th iteration.
As a further improvement of the present invention, the step S30 includes:
s31, performing peak detection on the obtained cross correlation value; the method specifically comprises the following steps:
Figure BDA0002339566160000024
s32, calculating the background noise; the method specifically comprises the following steps:
Figure BDA0002339566160000025
s33, peak value threshold-crossing detection is carried out; the method specifically comprises the following steps:
Figure BDA0002339566160000031
therein, βλIs the threshold scaling factor for the lambda iteration.
As a further improvement of the present invention, the step S40 includes:
s41, extracting a frequency domain receiving SSS signal sequence passing a threshold; the method specifically comprises the following steps:
Figure BDA0002339566160000032
s42, channel estimation is carried out; the method specifically comprises the following steps:
Figure BDA0002339566160000033
Figure BDA0002339566160000034
s43, making inter-symbol average; the method specifically comprises the following steps:
Figure BDA0002339566160000035
Figure BDA0002339566160000036
k＝0,1,...,11
s44, frequency domain MMSE filtering is carried out; the method specifically comprises the following steps:
hmmse＝Whs
Figure BDA0002339566160000037
wherein, W is a frequency domain MMSE filter;
s45, channel response extended to 132 length:
Figure BDA0002339566160000038
as a further improvement of the present invention, the regenerating the ID receiving SSS signal is:
Figure BDA0002339566160000039
Figure BDA0002339566160000041
where diag (a) denotes the expansion of the a vector into a matrix with a as the object line element.
As a further improvement of the present invention, in the step S60, the step S20 is re-entered as a new frequency domain received SSS signal after subtracting the ID received SSS signal from the frequency domain received SSS signal, which specifically includes:
rλ+1＝rλ-sλ
λ＝λ+1
wherein r isλ+1The SSS signal is received for the new frequency domain.
The invention has the beneficial effects that:
the NBIOT system multi-cell iterative interference cancellation detection method of the invention takes signals of other cells as interference during each detection, thereby easily determining the threshold, and removes the cell signal from the received signal after detecting the cell with strong signal, so that the SINR of the subsequent cell signal is strengthened, and the detection stage is returned for repeated iterative calculation. The method can accurately detect a plurality of neighbor cells in a plurality of cells and reduce false alarm and missed detection probability, and meanwhile, the iterative method can obviously reduce the detection SINR threshold of the neighbor cells, and the detection threshold is easier to set.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
Fig. 1 is a flowchart of an NBIOT system multi-cell iterative interference cancellation detection method in an embodiment of the present invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
Examples
As shown in fig. 1, the method for detecting multi-cell iterative interference cancellation in an NBIOT system in an embodiment of the present invention includes the following steps:
s10, initializing an iteration counter lambda to be 0, simultaneously generating a local SSS signal set, and extracting 12 subcarrier signals r on 11 symbols of a frequency domain as frequency domain receiving SSS signals after obtaining cell time-frequency synchronization;
wherein the set of local SSS signals is:
xi,j＝[x0,i,j,x1,i,j,...,x131,i,j]T
i＝0,1,2,3
j＝0,1,...,503
the frequency domain received SSS signal is: r ═ r0,r1,...,r131]T。
S20, performing cross correlation on the frequency domain receiving SSS signals and a local SSS signal set; the method specifically comprises the following steps:
Figure BDA0002339566160000051
Figure BDA0002339566160000052
i＝0,1,2,3
j＝0,1,...,503
wherein, yi,jIs a value of the cross-correlation value,
Figure BDA0002339566160000053
the reconstructed signal output for the lambda-1 th iteration.
S30, performing peak value threshold-crossing detection on the obtained cross-correlation value;
specifically, step S30 includes:
s31, performing peak detection on the obtained cross correlation value; the method specifically comprises the following steps:
Figure BDA0002339566160000054
s32, calculating the background noise; the method specifically comprises the following steps:
Figure BDA0002339566160000055
s33, peak value threshold-crossing detection is carried out; the method specifically comprises the following steps:
Figure BDA0002339566160000061
therein, βλIs the threshold scaling factor for the lambda iteration.
S40, performing LS channel estimation on the SSS signals received by the frequency domain which pass the threshold, and further obtaining the channel response of LS;
specifically, step S40 includes:
s41, extracting a frequency domain receiving SSS signal sequence passing a threshold; the method specifically comprises the following steps:
Figure BDA0002339566160000062
s42, channel estimation is carried out; the method specifically comprises the following steps:
Figure BDA0002339566160000063
Figure BDA0002339566160000064
s43, making inter-symbol average; the method specifically comprises the following steps:
Figure BDA0002339566160000065
Figure BDA0002339566160000066
k＝0,1,...,11
s44, frequency domain MMSE filtering is carried out; the method specifically comprises the following steps:
hmmse＝Whs
Figure BDA0002339566160000067
wherein, W is a frequency domain MMSE filter;
s45, channel response extended to 132 length:
Figure BDA0002339566160000068
s50, regenerating the ID receiving SSS signal according to the obtained channel response and the detected ID local SSS signal;
wherein, regenerating the ID received SSS signal is:
Figure BDA0002339566160000071
Figure BDA0002339566160000072
where diag (a) denotes the expansion of the a vector into a matrix with a as the object line element.
And S60, subtracting the ID receiving SSS signal from the frequency domain receiving SSS signal, and then re-entering the step S20 as a new frequency domain receiving SSS signal to perform cross correlation with the local SSS signal set, and repeating the steps until all the specified neighbor cells are detected or the maximum iterative detection times are reached.
In step S60, the step S20 is resumed after subtracting the ID received SSS signal from the frequency domain received SSS signal, and includes:
rλ+1＝rλ-sλ
λ＝λ+1
wherein r isλ+1The SSS signal is received for the new frequency domain.
The above embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.

Claims (7)

1. A NBIOT system multi-cell iterative interference cancellation detection method is characterized by comprising the following steps:
s10, initializing an iteration counter lambda to be 0, simultaneously generating a local SSS signal set, and extracting 12 subcarrier signals r on 11 symbols of a frequency domain as frequency domain receiving SSS signals after obtaining cell time-frequency synchronization;
s20, performing cross correlation on the frequency domain receiving SSS signals and a local SSS signal set;
s30, performing peak value threshold-crossing detection on the obtained cross-correlation value;
s40, performing LS channel estimation on the SSS signals received by the frequency domain which pass the threshold, and further obtaining the channel response of LS;
s50, regenerating the ID receiving SSS signal according to the obtained channel response and the detected ID local SSS signal;
and S60, subtracting the ID receiving SSS signal from the frequency domain receiving SSS signal, and then re-entering the step S20 as a new frequency domain receiving SSS signal, and iterating until the detection of all specified adjacent cells is completed or the maximum iteration detection times is reached.
2. The NBIOT system multi-cell iterative interference cancellation detection method of claim 1, wherein the set of local SSS signals is:
xi,j＝[x0,i,j,x1,i,j,...,x131,i,j]T
i＝0,1,2,3
j＝0,1,...,503
the frequency domain received SSS signal is: r ═ r0,r1,...,r131]T。
3. The NBIOT system multi-cell iterative interference cancellation detection method of claim 2, wherein the step S20 specifically comprises:
Figure FDA0002339566150000011
Figure FDA0002339566150000012
i＝0,1,2,3
j＝0,1,...,503
wherein the content of the first and second substances,
Figure FDA0002339566150000021
the reconstructed signal output for the lambda-1 th iteration.
4. The NBIOT system multi-cell iterative interference cancellation detection method of claim 3, wherein the step S30 comprises:
s31, performing peak detection on the obtained cross correlation value; the method specifically comprises the following steps:
Figure FDA0002339566150000022
s32, calculating the background noise; the method specifically comprises the following steps:
Figure FDA0002339566150000023
s33, peak value threshold-crossing detection is carried out; the method specifically comprises the following steps:
Figure FDA0002339566150000024
therein, βλIs the threshold scaling factor for the lambda iteration.
5. The NBIOT system multi-cell iterative interference cancellation detection method of claim 4, wherein the step S40 comprises:
s41, extracting a frequency domain receiving SSS signal sequence passing a threshold; the method specifically comprises the following steps:
Figure FDA0002339566150000025
s42, channel estimation is carried out; the method specifically comprises the following steps:
Figure FDA0002339566150000026
Figure FDA0002339566150000027
s43, making inter-symbol average; the method specifically comprises the following steps:
Figure FDA0002339566150000028
Figure FDA0002339566150000029
k＝0,1,...,11
s44, frequency domain MMSE filtering is carried out; the method specifically comprises the following steps:
hmmse＝Whs
Figure FDA0002339566150000031
wherein, W is a frequency domain MMSE filter;
s45, channel response extended to 132 length:
Figure FDA0002339566150000032
6. the NBIOT system multi-cell iterative interference cancellation detection method of claim 5, wherein the regenerating the ID received SSS signal is:
Figure FDA0002339566150000033
Figure FDA0002339566150000034
where diag (a) denotes the expansion of the a vector into a matrix with a as the object line element.
7. The NBIOT system multi-cell iterative interference cancellation detection method of claim 6, wherein the step S60 re-enters the step S20 as a new frequency-domain received SSS signal after subtracting the ID received SSS signal from the frequency-domain received SSS signal, specifically comprising:
rλ+1＝rλ-sλ
λ＝λ+1
wherein r isλ+1The SSS signal is received for the new frequency domain.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102469475A (en) * 2010-11-19 2012-05-23 中兴通讯股份有限公司 Method and device for interference cancellation in wireless communication system
CN103581069A (en) * 2012-07-23 2014-02-12 美国博通公司 Secondary synchronization signal detection with interference cancelation for LTE
CN104093168A (en) * 2014-07-31 2014-10-08 武汉邮电科学研究院 LTE (Long Term Evolution) common-frequency adjacent region detection method and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102469475A (en) * 2010-11-19 2012-05-23 中兴通讯股份有限公司 Method and device for interference cancellation in wireless communication system
CN103581069A (en) * 2012-07-23 2014-02-12 美国博通公司 Secondary synchronization signal detection with interference cancelation for LTE
CN104093168A (en) * 2014-07-31 2014-10-08 武汉邮电科学研究院 LTE (Long Term Evolution) common-frequency adjacent region detection method and device

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