CN115277317B - Channel estimation method, system, equipment and computer readable storage medium - Google Patents
Channel estimation method, system, equipment and computer readable storage medium Download PDFInfo
- Publication number
- CN115277317B CN115277317B CN202210905867.6A CN202210905867A CN115277317B CN 115277317 B CN115277317 B CN 115277317B CN 202210905867 A CN202210905867 A CN 202210905867A CN 115277317 B CN115277317 B CN 115277317B
- Authority
- CN
- China
- Prior art keywords
- target
- sequence
- channel
- delay
- target sequence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- 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
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Monitoring And Testing Of Transmission In General (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The application discloses a channel estimation method, a system, equipment and a computer readable storage medium, wherein a target large-delay channel to be estimated is obtained, and the target large-delay channel is characterized by h= (h) 0 ,…,h L‑1 ) T Wherein h is 0 And h L‑m ~h L‑1 Is not zero, h 1 ~h L‑m‑1 Is zero; generating a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1; acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted through a target large-delay channel; and carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result. In the method, the first target sequence and the second target sequence can be generated based on the channel vector length L of the target large-delay channel and the value of the channel quantity m with zero, and then the optimal estimation of the large-delay channel can be completed at a low cost based on the second target sequence and the second target sequence.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a channel estimation method, system, device, and computer readable storage medium.
Background
In the field of communication, a complex communication environment can bring a large time delay multipath effect to the propagation of a wireless signal, so that the difficulty of channel estimation is increased, and the communication quality is seriously affected. The frequency hopping communication system is widely applied to communication systems by virtue of its excellent anti-interference performance, and since frequency hopping communication transmits information on a single frequency band, communication is generally performed by a time domain single carrier scheme. However, how to research a new zero correlation zone (Zero Correction Zone, ZCZ) sequence which can enable the channel estimation performance to reach the Lower Bound (CRLB) of the caramerro based on the channel characteristics of the outdoor scene, and meanwhile, reduce the design difficulty of the sequence, and finally, realize high-speed and high-reliability wireless communication under the complex communication environment is a problem to be solved.
The existing Least Square (LS) method is a classical time domain channel estimation method, has the advantages of low computational complexity, low hardware realization cost and the like, and is widely applied to various time domain single carrier communication systems. Under the multipath channel, the performance of least squares channel estimation depends on the correlation of the training Sequence, and a Perfect Sequence (Perfect Sequence) can optimize the channel estimation performance, so that crlb.fan et al put forward the concept of ZCZ Sequence in 1999 after analyzing the characteristics of the multipath channel. Fan et al state that the delay of the effective path of the multipath channel is limited and that the channel estimation performance can be optimized when the maximum multipath delay of the multipath channel is smaller than the size of the zero correlation zone of the sequence correlation. Furthermore, in 2001 Spasojevic et al indicated that complementary sequences could be used in the form of bilateral channel estimates in a single carrier communication system. In 2007, fan et al extended the concept of ZCZ into the category of complementary sequences and proposed zero correlation complementary pairs (Zero Complementary Pair, ZCP). When the maximum multipath time delay of the multipath channel is smaller than the zero correlation zone size of the sequence aperiodic correlation sum, the channel estimation performance can be optimized. It should be noted that designing a ZCP (or single sequence) with a large ZCZ interval is a challenging problem, and in general, the larger the ZCZ interval, the more difficult the design.
The performance of a wireless communication system is greatly affected by wireless channels, such as shadow fading, frequency selective fading, and the like. Therefore, it is important for a wireless communication system to obtain accurate channel information so that a transmission signal is correctly demodulated at a receiving end. Under a large-delay channel model, accurate channel estimation requires a larger ZCZ zone of a sequence, which also means that the difficulty of sequence design is greater.
In summary, how to complete the optimal estimation of the large delay channel with a small cost is a problem to be solved by those skilled in the art.
Disclosure of Invention
The purpose of the present application is to provide a channel estimation method, which can solve the technical problem of how to complete the optimal estimation of a large-delay channel with a small cost to a certain extent. The application also provides a channel estimation system, a device and a computer readable storage medium.
In order to achieve the above object, the present application provides the following technical solutions:
a method of channel estimation, comprising:
obtaining a target large-delay channel to be estimated, wherein the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero;
generating a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1;
acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted by the target large-delay channel;
and carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result.
Preferably, the generating a first target sequence and a second target sequence satisfying aperiodic autocorrelation and being zero when the time delay is 1.ltoreq.τ.ltoreq.m-1 and the time delay is L-m.ltoreq.τ.ltoreq.L-1 includes:
acquiring a first initial sequence and a second initial sequence, wherein the first initial sequence and the second initial sequenceAperiodic autocorrelation and satisfactionAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents the first initial sequence, b represents the second initial sequence;
generating the first target sequence and the second target sequence which meet aperiodic autocorrelation and are zero when time delay is 1-tau-m-1 and time delay L-m-tau-1 is less than or equal to L-1 based on the first initial sequence and the second initial sequence according to a first generation formula;
the first generation formula includes:
c=[a,b];d=[a,-b];
wherein c represents the first target sequence; d represents the second target sequence.
Preferably, the performing channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result includes:
generating an initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L;
partitioning the target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values;
deleting the large-delay channel block with zero value in the target large-delay channel to obtain a processed large-delay channel;
splitting and deleting the initial pilot frequency matrix to obtain a target pilot frequency matrix corresponding to the processing large-delay channel;
and carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain the channel estimation result.
Preferably, the generating the initial pilot matrix corresponding to the target large delay channel based on the first target sequence, the second target sequence and L includes:
and generating the initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L according to the sequence correlation.
Preferably, the channel estimation for the target large-delay channel based on the target pilot matrix and the target receiving sequence to obtain the channel estimation result includes:
and carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence according to a least square method to obtain the channel estimation result.
A channel estimation system, comprising:
a first acquisition module, configured to acquire a target large-delay channel to be estimated, where the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero;
the first generation module is used for generating a first target sequence and a second target sequence which meet the aperiodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1;
the second acquisition module is used for acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted through the target large-delay channel;
and the first estimation module is used for carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result.
Preferably, the first generating module includes:
a first acquisition unit for acquiring a first initial sequence and a second initial sequence, the aperiodic autocorrelation sum of the first initial sequence and the second initial sequence meetingAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents the first initial sequence, b represents the first initial sequenceTwo initial sequences;
the first generation unit is used for generating the first target sequence and the second target sequence which meet aperiodic autocorrelation and are zero when the time delay is 1-m-1 and the time delay L-m- τ -1 are less than or equal to m-1 based on the first initial sequence and the second initial sequence according to a first generation formula;
the generation formula comprises:
c=[a,b];d=[a,-b];
wherein c represents the first target sequence; d represents the second target sequence.
Preferably, the first estimation module includes:
the first generation unit is used for generating an initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L;
the first blocking unit is used for blocking the target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values;
a first deleting unit, configured to delete the large delay channel block with the median value of the target large delay channel being zero, to obtain a processed large delay channel;
the first splitting unit is used for splitting and deleting the initial pilot frequency matrix to obtain a target pilot frequency matrix corresponding to the processing large-delay channel;
and the first estimation unit is used for carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain the channel estimation result.
A channel estimation device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of any one of the channel estimation methods described above when executing the computer program.
A computer readable storage medium having stored therein a computer program which when executed by a processor performs the steps of the channel estimation method as claimed in any one of the preceding claims.
According to the channel estimation method, the target large-delay channel to be estimated is obtained, and the target large-delay channel is characterized as h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero; generating a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1; acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted through a target large-delay channel; and carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result. In the method, the first target sequence and the second target sequence can be generated based on the channel vector length L of the target large-delay channel and the value of the channel quantity m with zero, and then the optimal estimation of the large-delay channel can be completed at a low cost based on the second target sequence and the second target sequence. The channel estimation system, the device and the computer readable storage medium provided by the application also solve the corresponding technical problems.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings may be obtained according to the provided drawings without inventive effort to a person skilled in the art.
Fig. 1 is a flowchart of a channel estimation method provided in an embodiment of the present application;
fig. 2 is a schematic diagram of an initial pilot matrix;
FIG. 3 is a block diagram of an initial pilot matrix;
FIG. 4 is a diagram showing the comparison of the MLS and LS algorithms of a 26-length GZCP;
FIG. 5 is a graph comparing the MLS and LS algorithms of 26-length GCP;
FIG. 6 is a diagram showing the comparison of MLS and LS algorithms of a 32-length GZCP;
FIG. 7 is a graph showing the MLS versus LS algorithm for 32-length GCP;
FIG. 8 is a diagram showing a 26-length GZCP versus GCP under the MLS algorithm;
FIG. 9 is a diagram showing the comparison of 32-length GZCP and GCP under the MLS algorithm;
fig. 10 is a schematic structural diagram of a channel estimation system according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of a fan rotation speed processing device according to an embodiment of the present application;
fig. 12 is another schematic structural diagram of a fan rotation speed processing apparatus according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Referring to fig. 1, fig. 1 is a flowchart of a channel estimation method according to an embodiment of the present application.
The channel estimation method provided by the embodiment of the application can comprise the following steps:
step S101: acquiring a target large-delay channel to be estimated, wherein the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 The value of (2) is zero.
In practical application, a target large-delay channel to be estimated can be obtained first, and the target large-delay channel is characterized as h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero, L represents the channel vector length, h represents the response value of each channel path, and the values of L and h can rootThe delay size and the chip transmission rate of the system are determined according to the channel model.
Step S102: generating a first target sequence and a second target sequence which satisfy the aperiodic autocorrelation and are zero when the time delay is not less than 1 and not more than m-1 and the time delay is not less than L-m and not more than T and not more than L-1.
In practical application, after the target large delay channel to be estimated is acquired, a first target sequence and a second target sequence which meet the aperiodic autocorrelation and are zero when the delay tau is more than or equal to 1 and less than or equal to m-1 and the delay L-m is more than or equal to tau and less than or equal to L-1 can be generated.
It should be noted that, the aperiodic autocorrelation in the present application refers to: for the sequence a= (a (0), a (1), a (N-1)), its aperiodic autocorrelation is defined as
In a specific application scene, in the process of generating a first target sequence and a second target sequence which satisfy non-periodic autocorrelation and are zero when the time delay is 1- τ -1 and the time delay is L-m- τ -1, the first initial sequence and the second initial sequence which satisfy ZCP (zero-cross correlation) can be obtained, namely, the non-periodic autocorrelation of the first initial sequence and the second initial sequence and the non-periodic autocorrelation of the second initial sequence satisfyAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents a first initial sequence, b represents a second initial sequence; according to a first generation formula, a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is 1-tau-1 and the time delay is L-m-tau-1 are rapidly generated based on the first initial sequence and the second initial sequence;
the first generation formula includes:
c=[a,b];d=[a,-b];
wherein c represents a first target sequence; d represents a second target sequence.
Step S103: and acquiring target receiving sequences of the first target sequence and the second target sequence after being transmitted through the target large-delay channel.
In practical application, after generating a first target sequence and a second target sequence which satisfy non-periodic autocorrelation and are zero when time delay is 1- τ -1 and time delay is L-m- τ -1, the target receiving sequence after the first target sequence and the second target sequence are transmitted through the target large-delay channel can be obtained, so that channel estimation can be carried out on the target large-delay channel based on the target receiving sequence, the first target sequence and the second target sequence.
Step S104: and carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result.
In practical application, after the target receiving sequence of the first target sequence and the second target sequence transmitted by the target large-delay channel is obtained, the channel estimation can be performed on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence, so as to obtain a channel estimation result.
In a specific application scenario, in a process of performing channel estimation on a target large-delay channel based on a first target sequence, a second target sequence and a target receiving sequence to obtain a channel estimation result, an initial pilot matrix corresponding to the target large-delay channel can be generated based on the first target sequence, the second target sequence and L, as shown in FIG. 2; partitioning a target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values; deleting a large delay channel block with zero value in a target large delay channel to obtain a processed large delay channel; splitting and deleting the initial pilot matrix to obtain a target pilot matrix corresponding to the processing of the large-delay channel, as shown in fig. 3; and carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain a channel estimation result.
In a specific application scenario, in the process of generating the initial pilot matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and the L, the initial pilot matrix corresponding to the target large-delay channel may be generated based on the first target sequence, the second target sequence and the L according to the sequence arrival correlation, and specifically, the first target sequence and the second target sequence may be used as the first of the initial pilot matricesColumn, move the first column down one bit to get the second column, move the first column down two bits to get the third column, and so on, finally a pilot sequence will generate a matrix with (n+l-1) x L size, P 1 And P 2 Representing the first target sequence and the second target sequence, the two matrices are connected together up and down to form a large pilot matrix, i.e., an initial pilot matrix, whose size is 2 (n+l-1) x L, as shown in fig. 2, and the last column is the first column shifted down by L-1 bits.
In a specific application scenario, in the process of performing channel estimation on a target large-delay channel based on a target pilot matrix and a target receiving sequence to obtain a channel estimation result, the channel estimation on the target large-delay channel can be performed based on the target pilot matrix and the target receiving sequence according to a least square method, such as MLS (Modified LS) algorithm, to obtain the channel estimation result.
It should be noted that, assume that the target reception sequence is:
when the first target sequence and the second target sequence meet the non-periodic autocorrelation sum and are zero when the time delay is 1-m-1 and the time delay is L-m-1, at the momentFor diagonal alignment, the delay range equivalent to the pilot sequence P satisfying the autocorrelation of 0 is equal to or greater than the multipath delay range of the channel, the estimated variance is minimum, and the optimal channel estimation performance is achieved, and for convenience of explanation, the first target sequence and the second target sequence at this time may be referred to as GZCPs ((general Z-Complementary Pairs).
According to the channel estimation method, the target large-delay channel to be estimated is obtained, and the target large-delay channel is characterized as h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero; generating a satisfactory aperiodicThe autocorrelation sum is zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1; acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted through a target large-delay channel; and carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result. In the method, the first target sequence and the second target sequence can be generated based on the channel vector length L of the target large-delay channel and the value of the channel quantity m with zero, and then the optimal estimation of the large-delay channel can be completed at a low cost based on the second target sequence and the second target sequence.
To facilitate an understanding of the present application, it is now assumed that the present application is used to solve the problem of estimating the SUI-6Channel model in a 1.6MHz single carrier communication system model. The chip transmission rate under the system is 1.22Mcps, and the channel has response at time delays of 14 mu s and 20 mu s, so that the channel parameter is E (|h|) = [1,0 19 ,0.4,0 4 ,0.2] Τ ;
Assuming that the target sequence is 26 long GZCP, the aperiodic autocorrelation sum is:
[52,0 7 ,12,6,-6,4,-10,-2,2,-4,2,2,0 8 ];
the first target sequence may be:
[1,1,1,1,1,1,1,1,1,-1,1,-1,-1,1,1,1,-1,-1,-1,1,-1,1,-1,1,1,-1];
the second target sequence may be:
[1,1,-1,-1,-1,-1,1,1,-1,1,1,-1,-1,-1,1,1,-1,1,1,-1,-1,1,-1,1,-1,1];
assuming that the target sequence is 28 long GZCP, the aperiodic autocorrelation sum is:
[56,0 5 ,-4,-4,-8,8,-8,14,0,4,4,0,0,2,0,-10,0 8 ];
the first target sequence may be:
[-1,-1,-1,-1,-1,-1,1,-1,1,1,1,-1,-1,1,-1,1,-1,-1,-1,1,1,1,-1,-1,1,-1,1,-1];
the second target sequence may be:
[1,1,1,-1,-1,1,1,-1,-1,1,-1,-1,1,1,1,1,-1,1,-1,-1,-1,-1,-1,1,-1,-1,1,-1];
assuming that the target sequence is 30 long GZCP, the aperiodic autocorrelation sum is:
[60,0 6 ,4,8,-4,8,-2,-4,-6,0,-2,4,6,0,-2,0 10 ];
the first target sequence may be:
[-1,1,1,1,1,-1,-1,1,-1,1,-1,1,1,-1,1,-1,-1,-1,1,1,1,1,1,1,1,-1,1,1,1,-1];
the second target sequence may be:
[1,-1,-1,-1,-1,1,1,-1,1,-1,1,-1,-1,1,1,-1,1,1,-1,-1,1,1,1,1,1,-1,1,1,1,-1];
assuming that the target sequence is 31 long GZCP, the aperiodic autocorrelation sum is:
[62,0 5 ,-10,2,18,2,2,-2,0,8,-8,8,6,6,-6,-2,0 6 ,2,-2,-2,-2,2];
the first target sequence may be:
[-1,1,-1,-1,1,-1,1,1,1,1,-1,1,1,-1,1,-1,1,1,-1,1,1,1,-1,1,1,1,-1,1,1,1,-1];
the second target sequence may be:
[1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,-1,1,-1,1,1,1,-1,-1,-1,-1,-1,1,1,1,1,-1,-1,-1,1];
assuming that the target sequence is 32 long GZCP, the aperiodic autocorrelation sum is:
[64,0 5 ,-2,-8,-16,0,4,8,0,4,6,8,-2,0,-6,0 7 ,2,0 3 ,-4,0];
the first target sequence may be:
[1,-1,1,1,-1,1,1,-1,1,1,-1,1,1,-1,-1,1,1,1,-1,1,1,1,1,-1,1,-1,1,-1,-1,-1,-1,1];
the second target sequence may be:
[1,1,1,-1,-1,-1,-1,-1,-1,-1,1,1,1,-1,1,1,1,-1,-1,-1,-1,1,1,-1,-1,1,-1,1,-1,1,-1,-1];
assuming that the target sequence is 33 long GZCP, the aperiodic autocorrelation sum is:
[66,0 5 ,14,4,2,-14,-6,-2,-2,2,0,-14,2,-4,-4,6,0 6 ,-2,-4,2,2,-2,-2,-2];
the first target sequence may be:
[1,1,1,-1,-1,1,-1,1,1,-1,-1,-1,1,1,1,1,1,-1,1,1,-1,1,-1,-1,-1,-1,1,-1,-1,-1,-1,-1,-1];
the second target sequence may be:
[1,1,1,-1,-1,1,1,-1,1,1,-1,-1,1,-1,1,-1,-1,-1,1,-1,1,-1,1,-1,1,1,-1,-1,1,1,1,1,-1]。
in order to facilitate understanding of the effect of the application, the shortcomings of difficult design and insufficient quantity of the traditional channel estimation sequence pair under the condition are analyzed by taking a large-delay channel model as a background, so that an LS algorithm is improved based on the shortcomings, GZCPs are provided, and compared with the traditional channel estimation sequence pair, the GZCPs have lower requirements on zero correlation zones and great advantages in length and quantity. Therefore, the GZCPs is more suitable for estimating a large-delay channel under the MLS algorithm. At present, simulation comparison is carried out on GZCPs and GCPs, the advantages of the MLS algorithm under the large-delay channel compared with the LS algorithm and the effectiveness of estimating the large-delay channel by using the GZCPs are proved, and corresponding comparison results can be referred to fig. 4 to 9. As can be seen from fig. 4 to fig. 7, the estimation performance of GZCPs under the MLS algorithm is significantly better than that of LS algorithm, and the estimation results of GCPs under the MLS algorithm and LS algorithm are the same due to the complete complementarity of GCPs; in addition, fig. 8 and 9 show that GZCPs and GCPs have the same channel estimation result under the MLS algorithm. Thus, by simulation comparison, the GZCPs and the GCPs have the same channel estimation result under the MLS algorithm. Therefore, under the condition that the channel is a priori information of a large time delay channel, the channel estimation by using the GZCPs is accurate and reliable.
It should be noted that, for two sequences a and b of length N, if the aperiodic autocorrelation sum satisfies:
then sequences a and b are said to be a pair of non-periodic complete complementary sequences or GCP (Golay complementary pair); at this time, for the channel with the maximum multipath time delay of L-1, when N is more than or equal to L, the channel information obtained by using the aperiodic complementary pair to perform bilateral channel estimation is the most accurate, but the number of complementary pairs meeting the condition is less and the length is limited, and when N is an odd number, two completely complementary sequences are not present, but the defect is not present in the application;
if the aperiodic autocorrelation sum satisfies:
and satisfy ρ a (Z)+ρ b (Z) +.0, sequences a and b are referred to as ZCPs. At this time, for the channel with the maximum multipath time delay of L-1, when Z is larger than or equal to L, ZCPs are used as bilateral channel estimation to obtain accurate channel information, the number of ZCPs is more than that of non-periodic complementary sequence pairs, but the number of ZCPs is still insufficient, and when N is odd, the optimal ZCPs can only reachThis application does not suffer from this disadvantage.
In addition, although GCPs and ZCPs can achieve optimal estimation of h when the zero correlation zone is greater than or equal to L, and a sequence meeting the condition is easy to find when the channel delay is smaller, in a large-delay channel scene (L is larger), it is difficult to find ZCPs or GCPs which are suitable in length and can perform optimal estimation on h, and a large channel impact response time interval of a large-delay channel model (most of the middle of the vector h is 0) is a main reason for increasing the lengths of ZCPs and GCPs required by channel estimation. Under the condition of channel prior information, the method and the device give up the estimation of the channel non-response part so as to reduce the sequence requirement, further increase the number of sequences meeting the condition and facilitate the accurate estimation of the channel with large time delay.
Referring to fig. 10, fig. 10 is a schematic structural diagram of a channel estimation system according to an embodiment of the present application.
The channel estimation system provided by the embodiment of the application comprises:
a first obtaining module 101, configured to obtain a target large-delay channel to be estimated, where the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero;
a first generating module 102, configured to generate a first target sequence and a second target sequence that satisfy the aperiodic autocorrelation and are zero when the time delay is 1- τ -1 and the time delay is L-m- τ -1;
a second obtaining module 103, configured to obtain a target receiving sequence after the first target sequence and the second target sequence are transmitted through the target large-delay channel;
the first estimation module 104 is configured to perform channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence, so as to obtain a channel estimation result.
The first generation module of the channel estimation system provided in the embodiment of the present application may include:
a first acquisition unit for acquiring a first initial sequence and a second initial sequence, and the aperiodic autocorrelation sum of the first initial sequence and the second initial sequence satisfiesAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents a first initial sequence, b represents a second initial sequence;
the first generation unit is used for generating a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1 based on the first initial sequence and the second initial sequence according to a first generation formula;
the first generation formula includes:
c=[a,b];d=[a,-b];
wherein c represents a first target sequence; d represents a second target sequence.
In the channel estimation system provided in the embodiment of the present application, the first estimation module may include:
the first generation unit is used for generating an initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L;
the first blocking unit is used for blocking the target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values;
the first deleting unit is used for deleting the large-delay channel block with zero value in the target large-delay channel to obtain a processed large-delay channel;
the first splitting unit is used for splitting and deleting the initial pilot frequency matrix to obtain a target pilot frequency matrix corresponding to the processing of the large-delay channel;
and the first estimation unit is used for carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain a channel estimation result.
The description of the corresponding parts in the channel estimation method provided in the embodiment of the present application may refer to the above embodiment, and will not be repeated here.
The application also provides a channel estimation device and a computer readable storage medium, which have the corresponding effects of the channel estimation method provided by the embodiment of the application. Referring to fig. 11, fig. 11 is a schematic structural diagram of a fan rotation speed processing apparatus according to an embodiment of the present application.
The fan rotation speed processing device provided in the embodiment of the present application includes a memory 201 and a processor 202, where the memory 201 stores a computer program, and the processor 202 implements the steps of the channel estimation method described in any of the embodiments above when executing the computer program.
Referring to fig. 12, another channel estimation apparatus provided in an embodiment of the present application may further include: an input port 203 connected to the processor 202 for transmitting an externally input command to the processor 202; a display unit 204 connected to the processor 202, for displaying the processing result of the processor 202 to the outside; a communication module 205 connected to the processor 202, for implementing communication between the channel estimation device and the outside world. The display unit 204 may be a display panel, a laser scanning display, or the like; communication means employed by the communication module 205 include, but are not limited to, mobile high definition link technology (HML), universal Serial Bus (USB), high Definition Multimedia Interface (HDMI), wireless connection: wireless fidelity (WiFi), bluetooth communication, bluetooth low energy communication, ieee802.11s based communication.
The embodiment of the application provides a computer readable storage medium, in which a computer program is stored, where the computer program when executed by a processor implements the steps of the channel estimation method described in any of the embodiments above.
The computer readable storage medium referred to in this application includes Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The description of the relevant parts in the channel estimation system, the device and the computer readable storage medium provided in the embodiments of the present application refers to the detailed description of the corresponding parts in the channel estimation method provided in the embodiments of the present application, and will not be repeated here. In addition, the parts of the above technical solutions provided in the embodiments of the present application, which are consistent with the implementation principles of the corresponding technical solutions in the prior art, are not described in detail, so that redundant descriptions are avoided.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A method of channel estimation, comprising:
obtaining a target large-delay channel to be estimated, wherein the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero;
generating a first target sequence and a second target sequence which meet the non-periodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1;
acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted by the target large-delay channel;
performing channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result;
wherein the generating of the first target sequence and the second target sequence satisfying the aperiodic autocorrelation and being zero when the time delay is 1- τ -1 and the time delay is L-m- τ -1 comprises the following steps:
acquiring a first initial sequence and a second initial sequence, wherein the aperiodic autocorrelation sum of the first initial sequence and the second initial sequence meetsAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents the first initial sequence, b represents the second initial sequence;
generating the first target sequence and the second target sequence which meet aperiodic autocorrelation and are zero when time delay is 1-tau-m-1 and time delay L-m-tau-1 is less than or equal to L-1 based on the first initial sequence and the second initial sequence according to a first generation formula;
the first generation formula includes:
c=[a,b];d=[a,-b];
wherein c represents the first target sequence; d represents the second target sequence;
the channel estimation of the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence is performed to obtain a channel estimation result, which includes:
generating an initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L;
partitioning the target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values;
deleting the large-delay channel block with zero value in the target large-delay channel to obtain a processed large-delay channel;
splitting and deleting the initial pilot frequency matrix to obtain a target pilot frequency matrix corresponding to the processing large-delay channel;
and carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain the channel estimation result.
2. The method of claim 1, wherein the generating the initial pilot matrix corresponding to the target large delay channel based on the first target sequence, the second target sequence, and L comprises:
and generating the initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L according to the sequence correlation.
3. The method of claim 2, wherein the performing channel estimation on the target large-delay channel based on the target pilot matrix and the target receiving sequence to obtain the channel estimation result comprises:
and carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence according to a least square method to obtain the channel estimation result.
4. A channel estimation system, comprising:
a first acquisition module, configured to acquire a target large-delay channel to be estimated, where the target large-delay channel is characterized by h= (h) 0 ,…,h L-1 ) T Wherein h is 0 And h L-m ~h L-1 Is not zero, h 1 ~h L-m-1 Is zero;
the first generation module is used for generating a first target sequence and a second target sequence which meet the aperiodic autocorrelation and are zero when the time delay is more than or equal to 1 and less than or equal to m-1 and the time delay is more than or equal to L-m and less than or equal to L-1;
the second acquisition module is used for acquiring a target receiving sequence of the first target sequence and the second target sequence after being transmitted through the target large-delay channel;
the first estimation module is used for carrying out channel estimation on the target large-delay channel based on the first target sequence, the second target sequence and the target receiving sequence to obtain a channel estimation result;
wherein, the first generation module includes:
a first acquisition unit for acquiring a first initial sequence and a second initial sequence, the aperiodic autocorrelation sum of the first initial sequence and the second initial sequence meetingAnd satisfy ρ a (Z)+ρ b (Z) +.0, wherein Z+.L, a represents the first initial sequence, b represents the second initial sequence;
the first generation unit is used for generating the first target sequence and the second target sequence which meet aperiodic autocorrelation and are zero when the time delay is 1-m-1 and the time delay L-m- τ -1 are less than or equal to m-1 based on the first initial sequence and the second initial sequence according to a first generation formula;
the first generation formula includes:
c=[a,b];d=[a,-b];
wherein c represents the first target sequence; d represents the second target sequence;
wherein the first estimation module comprises:
the first generation unit is used for generating an initial pilot frequency matrix corresponding to the target large-delay channel based on the first target sequence, the second target sequence and L;
the first blocking unit is used for blocking the target large-delay channel to obtain large-delay channel blocks with zero values and non-zero values;
a first deleting unit, configured to delete the large delay channel block with the median value of the target large delay channel being zero, to obtain a processed large delay channel;
the first splitting unit is used for splitting and deleting the initial pilot frequency matrix to obtain a target pilot frequency matrix corresponding to the processing large-delay channel;
and the first estimation unit is used for carrying out channel estimation on the target large-delay channel based on the target pilot frequency matrix and the target receiving sequence to obtain the channel estimation result.
5. A channel estimation device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the channel estimation method according to any one of claims 1 to 3 when executing said computer program.
6. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, implements the steps of the channel estimation method according to any of claims 1 to 3.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210905867.6A CN115277317B (en) | 2022-07-29 | 2022-07-29 | Channel estimation method, system, equipment and computer readable storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210905867.6A CN115277317B (en) | 2022-07-29 | 2022-07-29 | Channel estimation method, system, equipment and computer readable storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN115277317A CN115277317A (en) | 2022-11-01 |
CN115277317B true CN115277317B (en) | 2023-07-25 |
Family
ID=83770957
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210905867.6A Active CN115277317B (en) | 2022-07-29 | 2022-07-29 | Channel estimation method, system, equipment and computer readable storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115277317B (en) |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1613193A (en) * | 2002-03-22 | 2005-05-04 | 连宇通信有限公司 | Coding method for generating general spread spectrum sequence zero with zero correlation window |
CN104468038A (en) * | 2014-11-27 | 2015-03-25 | 江苏中兴微通信息科技有限公司 | MIMO leader sequence generating method and receiving device based on zero correlation zone (ZCZ) sequences |
WO2019035961A1 (en) * | 2017-08-15 | 2019-02-21 | Interdigital Patent Holdings, Inc. | Encoding data with golay sequences |
CN109561041A (en) * | 2018-12-13 | 2019-04-02 | 西南交通大学 | A kind of communication sequence building method, system, equipment and computer storage medium |
WO2021068584A1 (en) * | 2019-10-10 | 2021-04-15 | 重庆邮电大学 | Method and device for generating aperiodic four-phase z complementary sequence pair signals |
CN114039639A (en) * | 2021-11-04 | 2022-02-11 | 电子科技大学 | Combined channel estimation and user detection method in large connection scene |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR2814877B1 (en) * | 2000-10-02 | 2003-01-03 | Mitsubishi Electric Inf Tech | CHANNEL ESTIMATION SEQUENCE AND METHOD OF ESTIMATING A TRANSMISSION CHANNEL WHICH USES SUCH A CHANNEL ESTIMATION SEQUENCE |
US20130259013A1 (en) * | 2009-06-10 | 2013-10-03 | Qualcomm Incorporated | Method and apparatus for processing primary and secondary synchronization signals for wireless communication |
US8724724B2 (en) * | 2012-06-29 | 2014-05-13 | Blackberry Limited | Zero correlation zone sequences for communication system |
EP3850773A1 (en) * | 2018-09-13 | 2021-07-21 | IDAC Holdings, Inc. | Methods, apparatuses and systems directed to complementary sequence encoding and encoded complementary sequence transmissions |
-
2022
- 2022-07-29 CN CN202210905867.6A patent/CN115277317B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1613193A (en) * | 2002-03-22 | 2005-05-04 | 连宇通信有限公司 | Coding method for generating general spread spectrum sequence zero with zero correlation window |
CN104468038A (en) * | 2014-11-27 | 2015-03-25 | 江苏中兴微通信息科技有限公司 | MIMO leader sequence generating method and receiving device based on zero correlation zone (ZCZ) sequences |
WO2019035961A1 (en) * | 2017-08-15 | 2019-02-21 | Interdigital Patent Holdings, Inc. | Encoding data with golay sequences |
CN109561041A (en) * | 2018-12-13 | 2019-04-02 | 西南交通大学 | A kind of communication sequence building method, system, equipment and computer storage medium |
WO2021068584A1 (en) * | 2019-10-10 | 2021-04-15 | 重庆邮电大学 | Method and device for generating aperiodic four-phase z complementary sequence pair signals |
CN114039639A (en) * | 2021-11-04 | 2022-02-11 | 电子科技大学 | Combined channel estimation and user detection method in large connection scene |
Non-Patent Citations (4)
Title |
---|
"Constructions_of_Cross_Z-Complementary_Pairs_With_New_Lengths";A. R. Adhikary, Z. Zhou, Y. Yang, and P. Fan;《IEEE Trans. Signal Process》;全文 * |
"Cross z-complementary pairs for optimal training in spatial modulation over frequency selective channels";Z. Liu, P. Yang, Y. L. Guan, and P. Xiao;《IEEE Trans. Signal Process》;全文 * |
Lifang Feng ; Pingzhi Fan ; Xiaohu Tang ; Kok-keong Loo."Generalized Pairwise Z-Complementary Codes".《IEEE Signal Processing Letters》.2008,全文. * |
林金朝 ; 周银萍 ; 李国军 ; 叶昌荣 ; 曾凡鑫."Ⅱ型Z-优化二元互补序列对的构造".《电子与信息学报》.2022,全文. * |
Also Published As
Publication number | Publication date |
---|---|
CN115277317A (en) | 2022-11-01 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP4359388B2 (en) | Method and apparatus for joint detection of data in a direct sequence spread spectrum communication system | |
JP5484682B2 (en) | WIRELESS COMMUNICATION DEVICE, EQUALIZER, EQUALIZER WEIGHT COEFFICIENT PROGRAM AND Equalizer Weight Coefficient Calculation Method | |
TWI258939B (en) | Method and receiver for receiving data transmitted using block space time transmit diversity (BSTTD), and code division multiple access (CDMA) communication system | |
Bhashyam et al. | Multiuser channel estimation and tracking for long-code CDMA systems | |
JPH10507598A (en) | Signal detection method in TDMA system | |
CN100550662C (en) | A kind of signal acceptance method that is used for pulse ultra-broadband communication system | |
US20080273511A1 (en) | Multi-Cell Joint-Detection Method in Time-Slotted CDMA System | |
CN113347126B (en) | Secure channel estimation method and system | |
CN101390299A (en) | Apparatus and methods for implementing a split equalizer filter for sparse channels | |
CN111953380B (en) | Non-periodic long code direct sequence spread spectrum signal time delay estimation method and system based on norm fitting | |
CN101312359A (en) | Apparatus and method for multi-cell combined channel estimation and multi-cell combined detection | |
CN115277317B (en) | Channel estimation method, system, equipment and computer readable storage medium | |
EP2642684B1 (en) | Signal processing method and apparatus in microwave communication system | |
WO2012095052A2 (en) | Method, device, and system for frequency offset estimation and channel estimation | |
CN1330101C (en) | A combined detection method for decreasing complexity in mobile communication system | |
CN101123462B (en) | A multi-path search value interposition method for direct frequency spreading code division multi-address system | |
WO2006106474A2 (en) | Method and apparatus for estimating channel in mobile communication system | |
CN104301005A (en) | Joint detection method and apparatus | |
CN107171990A (en) | Based on fractional spaced and iterative algorithm single-carrier signal time domain equalization method | |
CN107431670B (en) | Channel estimation method, device and system | |
CN104349510A (en) | Method and device of implementing wireless body area network | |
EP2485417A1 (en) | Method and device for selecting noise path | |
JPH01258511A (en) | Adaptive equalizer | |
US10673555B2 (en) | Secure channel sounding | |
CN110048974B (en) | Half code block inversion diversity method of mixed carrier system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |