CN113489660A - Channel estimation method, device and storage medium for SIMO system - Google Patents

Channel estimation method, device and storage medium for SIMO system Download PDF

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CN113489660A
CN113489660A CN202110692040.7A CN202110692040A CN113489660A CN 113489660 A CN113489660 A CN 113489660A CN 202110692040 A CN202110692040 A CN 202110692040A CN 113489660 A CN113489660 A CN 113489660A
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CN113489660B (en
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吕长伟
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Shenzhen Institute of Information Technology
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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
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • 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
    • 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
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • 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
    • H04L25/0256—Channel estimation using minimum mean square error criteria
    • 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
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Abstract

The invention discloses a channel estimation method of an SIMO system, which comprises the steps of obtaining a data frame sent by a sending end of the SIMO system; calculating the channel proportional relation of a plurality of receiving antennas of the receiving end according to the data received by each receiving antenna of the receiving end of the SIMO system; acquiring a data signal corresponding to the training sequence received by the receiving end; and optimizing the channel proportional relation and the data signal which is received by the receiving end and corresponds to the training sequence according to a set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result. Compared with the channel estimation realized only by the training sequence, the invention can greatly improve the accuracy of the channel estimation. The invention also discloses a channel estimation device and a storage medium of the SIMO system.

Description

Channel estimation method, device and storage medium for SIMO system
Technical Field
The present invention relates to the field of wireless communications, and in particular, to a method, an apparatus, and a storage medium for channel estimation in an SIMO system.
Background
The data transmitted by the existing SIMO (Single input multiple output) system each time includes: the training sequence and the data sequence. The training sequence is a redundancy sequence known by both the transmitting and receiving sides and can be used for channel estimation and the like; the data sequence is useful data actually transmitted by the system, and the receiver cannot predict the transmitted data sequence in advance, so that the receiver and the transmitter exchange information. Since the estimation of the channel is only performed by the training sequence at present, the estimation of the channel has low calculation accuracy and cannot meet the system requirement.
Disclosure of Invention
In order to overcome the defects of the prior art, an object of the present invention is to provide a channel estimation method for an SIMO system, which can solve the problems of low accuracy of channel estimation in the SIMO system in the prior art.
It is another object of the present invention to provide a channel estimation apparatus for an SIMO system, which can solve the problem of low accuracy of channel estimation in the SIMO system in the prior art.
It is another object of the present invention to provide a storage medium, which can solve the problems of low channel estimation accuracy in the SIMO system in the prior art.
One of the purposes of the invention is realized by adopting the following technical scheme:
a channel estimation method of a SIMO system, the channel estimation method comprising:
a transmission data acquisition step: acquiring a data frame sent by a sending end of the SIMO system; the data frame comprises a training sequence and a data sequence; wherein, the SIMO system comprises a transmitting end and a receiving end, the transmitting end is provided with 1 transmitting antenna, and the receiving end is provided with NSA receiving antenna, NSAre known;
a proportion estimation step: calculating the channel proportional relation of a plurality of receiving antennas of the receiving end according to the data received by each receiving antenna of the receiving end of the SIMO system; the data received by each receiving antenna is data corresponding to the data sequence in the data frame or data corresponding to the data frame; a channel is formed between the transmitting antenna of the transmitting end and each receiving antenna of the receiving end;
a received data acquisition step: acquiring a data signal corresponding to the training sequence received by the receiving end;
and (3) optimizing: and optimizing the channel proportional relation and the data signal which is received by the receiving end and corresponds to the training sequence according to a set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result.
Further, the scale estimating step includes: firstly, deducing a channel expression of each receiving antenna of a receiving end according to data corresponding to the data frame or data corresponding to the data sequence received by each receiving antenna of the receiving end; and then obtaining the channel proportion relation of a plurality of receiving antennas according to the channel expression of each receiving antenna.
Further, in the ratio estimating step: deriving a channel expression of each receiving antenna of the receiving end according to the data corresponding to the data sequence received by each receiving antenna of the receiving end specifically includes:
setting the data corresponding to the data sequence received by the ith receiving antenna of the receiving end as
Figure BDA0003127173080000021
Wherein the content of the first and second substances,
Figure BDA0003127173080000022
the nth data corresponding to the data sequence received by the ith receiving antenna of the receiving end is represented;
the channel expression h of the ith receiving antennaiExpressed as:
Figure BDA0003127173080000031
wherein z isi,nNoise of nth data corresponding to the data sequence received for an ith receiving antenna; dnIs the nth data of the data sequence; i is an element of [1, N ∈s]，n∈[1,N](ii) a N represents the data length of the data sequence;
channel proportional relation h of multiple receiving antennas1:
Figure BDA0003127173080000032
Comprises the following steps:
Figure BDA0003127173080000033
further, the scale estimating step further includes:
proportional deformation step: firstly, equation (2) is transformed into equation (3):
Figure BDA0003127173080000034
then, under the condition that the channel in one frame of data is kept unchanged, the formula (3) is transformed into a formula (4) according to an averaging algorithm;
Figure BDA0003127173080000035
obtaining the channel expression h of each receiving antenna according to the formula (4)iAnd aiThe following conditions are satisfied:
Figure BDA0003127173080000036
(5) and b is a constant.
Further, the optimizing step includes: and optimizing the channel proportional relation and the data signal corresponding to the training sequence received by the receiving end according to a set optimization criterion, solving the optimal solution of b under the condition of meeting the optimization criterion, and then obtaining the channel estimation of each receiving antenna according to the optimal solution of b and a formula (5).
Further, setting data corresponding to the training sequence received by each receiving antenna of the receiving end as
Figure BDA0003127173080000037
Wherein the content of the first and second substances,
Figure BDA0003127173080000038
represents the kth data corresponding to the training sequence received by the ith receiving antenna of the receiving end, and k belongs to [1, N ]t]；NtRepresents the data length of the training sequence;
receiving a data signal Y corresponding to the training sequence received by a receiving end under the condition that a channel in one frame of data is kept unchangedpExpressed as:
Yp＝hpT+Zp＝bapT+Zp；
Figure BDA0003127173080000041
the data signal corresponding to the training sequence is received by a receiving end;
Figure BDA0003127173080000042
is a channel vector;
Figure BDA0003127173080000043
for the transposition of the training sequence vector, T represents the transposition;
Figure BDA0003127173080000044
is a vector of coefficients of the channel scale relationship in equation (4); zpFor the noise matrix:
Figure BDA0003127173080000045
further, the optimization criteria include a least squares method and a least mean squares error method.
Further, when the optimization criterion is the least square method, the objective function is set to s (b) | | Yp-bapT||；
When S (b) is minimum, optimal solution of b
Figure BDA0003127173080000046
Comprises the following steps:
Figure BDA0003127173080000047
wherein H is a conjugate transpose;
the channel estimate is derived from equation (5) and equation (8) as:
Figure BDA0003127173080000048
the second purpose of the invention is realized by adopting the following technical scheme:
a channel estimation apparatus of an SIMO system, comprising a memory having stored thereon a channel estimation program operable on a processor, the channel estimation program being a computer program, and a processor which, when executing the channel estimation program, carries out the steps of a channel estimation method of an SIMO system as employed in one of the objects of the invention.
The third purpose of the invention is realized by adopting the following technical scheme:
a storage medium which is a computer-readable storage medium having stored thereon a channel estimation program which is a computer program that, when executed by a processor, implements the steps of a channel estimation method of an SIMO system as employed in one of the objects of the present invention.
Compared with the prior art, the invention has the beneficial effects that:
when estimating the channel, the invention firstly carries out preliminary estimation on the channel by the training sequence in the sending data, then estimates the channel by the data sequence and improves the channel estimation precision by the proportional relation between the channels, and compared with the prior art which estimates the channel only by the training sequence, the invention greatly improves the channel estimation precision.
Drawings
Fig. 1 is a schematic diagram of data communication between a sending end and a receiving end in an SIMO system according to the present invention.
Fig. 2 is a schematic structural diagram of transmitting data in the SIMO system provided in the present invention;
FIG. 3 is a flow chart of a channel estimation method for the SIMO system according to the present invention;
fig. 4 is a block diagram of a channel estimation apparatus of a SIMO system according to the present invention.
In the figure: 11. a memory; 12. a processor; 13. a communication bus; 14. a network interface.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
Example one
In order to solve the problem of low channel estimation accuracy in the prior art, the invention carries out channel estimation by combining the data sequence in the transmitted data with the training sequence, and can greatly improve the accuracy of channel estimation.
The SIMO (Single input multiple output) system applied in the present invention includes a transmitting end and a receiving end. The transmitting end is provided with 1 transmitting antenna for transmitting data signals outwards. The receiving end is provided with a plurality of receiving antennas which are respectively used for receiving the data signals sent by the transmitting antennas of the transmitting end.
The SIMO system comprises one frame of data transmitted each time: a training sequence and a data sequence. Wherein, the data and length of the training sequence are known to both the sending end and the receiving end; the length of the data sequence is known to the receiving end and the transmitting end, but the data itself is unknown to the receiving end. The position relationship between the training sequence in the data frame and the data sequence in the data frame is not specifically limited, and may be specifically adjusted according to actual requirements. Specifically, the present embodiment places all training sequences at the beginning of the data frame.
Generally, in the prior art, each channel is generally estimated through a known training sequence, that is, the channel rough estimation described in this embodiment, and the calculation result of this estimation method has low accuracy, so this embodiment implements channel estimation by adding an unknown data sequence to channel estimation and combining it with the training sequence.
The present invention provides a preferred embodiment, a channel estimation method for SIMO system, as shown in fig. 3, specifically including the following steps:
step S1, the data frame sent by the sending end of the SIMO system is acquired. Wherein the data frame comprises a training sequence and a data sequence.
As shown in fig. 1-2, in the present embodiment, the following are set: the transmitting end has 1 transmitting antenna, and the receiving end has NSA receivingAntenna, NSAre known.
Setting the length N of the training sequencetThe length of the data sequence is N, and the data of the training sequence p is denoted as pk,k＝1,2,...,NtData of the data sequence d is represented as dnN is 1, 2. In this embodiment, p denotes a training sequence, and d denotes a data sequence, which will be the same as below. N and k are numbers of data in the data sequence and the training sequence respectively, and the value range of N is [1, N]K has a value range of [1, Nt]. For the transmitting end, the length N of the training sequencetAnd the data are known, the length N of the data sequence is known; for the receiving end, the length N of the data sequence and the length N of the training sequencetThe data of the training sequence is known, but the data of the data sequence is unknown.
In this embodiment, it is further assumed that h represents channel estimation between a transmitting antenna at the transmitting end and one receiving antenna at the receiving end, and specifically refers to the specific description in the specification.
Step S2 is to calculate the channel proportional relationship of the receiving antennas on the receiving side from the data received by each receiving antenna on the receiving side of the SIMO system.
Preferably, in this embodiment, the data sequence may be used in calculating the channel proportional relationship, and the training sequence and the data sequence may also be used. Since the unknown data sequence is added to the channel estimation in this embodiment, the data sequence needs to be added when calculating the channel proportional relationship of the multiple receiving antennas. That is, in the case of the channel proportional relationship between the plurality of receiving antennas, the channel proportional relationship may be calculated according to the data corresponding to the data sequence received by each receiving antenna, or may be calculated according to the data corresponding to the training sequence and the data sequence received by each receiving antenna.
In the SIMO system in this embodiment, a channel is formed between each transmitting antenna at the transmitting end and each receiving antenna at the receiving end.
Preferably, the present embodiment calculates the channel ratio relationship based on the data sequence: setting the ith receiving antenna receiving of the receiving endTo data corresponding to the data sequence is
Figure BDA0003127173080000071
Wherein the content of the first and second substances,
Figure BDA0003127173080000072
represents the nth data corresponding to the data sequence received by the ith receiving antenna.
The channel expression h of the ith receiving antennaiExpressed as:
Figure BDA0003127173080000073
wherein z isi,nNoise of nth data corresponding to the data sequence received for an ith receiving antenna; dnIs the nth data of the data sequence; i is an element of [1, N ∈s]，n∈[1,N]。
Thus, the channel proportionality h for multiple receive antennas1:
Figure BDA0003127173080000081
Expressed as:
Figure BDA0003127173080000082
when the signal-to-noise ratio is large, the noise is negligible during signal transmission. I.e. when the noise is neglected, i.e. zi,nIf 0, equation (2) can be modified to equation (3):
Figure BDA0003127173080000083
meanwhile, under the condition that the channel is kept unchanged in the process of sending a frame data frame, the formula (3) is changed into a formula (4) according to an average algorithm:
Figure BDA0003127173080000084
from the formula (4), the channel expression h of each receiving antenna can be knowni,i＝1,2,...,NsAnd ai,i＝1,2,...,NsThe following conditions are satisfied:
Figure BDA0003127173080000085
b is the coefficient of the channel proportionality relation and is an unknown constant.
As can be seen from equation (5), the channel estimate h for each receive antenna can be obtained from equation (5) by simply obtaining the value of b.
Step S3, acquiring data corresponding to the training sequence received by the receiving end. Since the training sequence is known data, the received data corresponding to the training sequence is also known to the receiving end.
In this embodiment, data corresponding to the training sequence received by a plurality of receiving antennas at the receiving end is set as:
Figure BDA0003127173080000086
wherein the content of the first and second substances,
Figure BDA0003127173080000087
represents the kth data corresponding to the training sequence received by the ith receiving antenna of the receiving end, and k belongs to [1, N ]t]。
Under the condition that the channel is kept unchanged in the process of transmitting a frame data frame, a data signal Y corresponding to the training sequence and received by a receiving endpExpressed as:
Yp＝hpT+Zp (6)。
since h is the channel estimate, substituting equation (5) into equation (6) yields: y isp＝hpT+Zp＝bapT+Zp (7)。
Wherein the content of the first and second substances,
Figure BDA0003127173080000091
the data signal corresponding to the training sequence is received by a receiving end;
Figure BDA0003127173080000092
is a channel vector;
Figure BDA0003127173080000093
for the transposition of the training sequence vector, T represents the transposition;
Figure BDA0003127173080000094
is a vector of channel scale coefficients in formula (4); zpFor the noise matrix:
Figure BDA0003127173080000095
as can be seen from equation (5), solving for the channel estimate can be converted into solving for the value of the unknown constant b.
And step S4, optimizing the channel proportional relation and the data signal corresponding to the training sequence received by the receiving end according to the set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result.
Preferably, the optimization criterion in the present embodiment may use a solution method of the optimal solution commonly used in the prior art, such as a least square method or a least mean square error method.
Specifically, when the optimization criterion is the least square method, in order to find the optimal solution of b, the present embodiment derives the objective function according to formula (7): s (b) | | Yp-bapT||。
I.e. according to the least squares method, at the time when S (b) is minimum, the optimal solution of b
Figure BDA0003127173080000096
Comprises the following steps:
Figure BDA0003127173080000097
wherein H is a conjugate transpose.
Therefore, the channel estimation can be obtained as shown in formula (8) and formula (5)：
Figure BDA0003127173080000098
That is, under the optimization criterion of the least square method, the channel fine estimation of each receiving antenna of the receiving end is respectively as follows:
Figure BDA0003127173080000101
the invention realizes the calculation of channel estimation by combining the training sequence and the digital sequence, the channel estimation is expressed by data received by a receiving end in advance, such as the combination of the training sequence and the digital sequence or the data sequence, and then the channel proportional relation of a plurality of receiving antennas is obtained, thus the incidence relation between the channel proportional coefficient and the channel estimation can be expressed, the calculation of the channel estimation is converted into the proportional relation between the calculated channel proportional coefficient and the channel estimation, and finally the proportional relation is optimized by combining the known training sequence to calculate the channel estimation. The invention can greatly improve the accuracy of channel estimation by taking the unknown data sequence into account in the calculation of the channel estimation.
Example two
The invention provides a channel estimation device of a SIMO system. As shown in fig. 4, an internal structure of a channel estimation device of a SIMO system according to an embodiment of the present invention is schematically illustrated.
In this embodiment, the channel estimation device of the SIMO system may be a PC (Personal Computer), or may be a terminal device such as a smartphone, a tablet Computer, or a mobile Computer. The channel estimation device of the SIMO system at least comprises: a processor 12, a communication bus 13, a network interface 14, and a memory 11.
The memory 11 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 11 may in some embodiments be an internal storage unit of the channel estimation device of an SIMO system, for example a hard disk of the channel estimation device of the SIMO system. The memory 11 may be an external storage device of the channel estimation device of the SIMO system in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the channel estimation device of the SIMO system. Further, the memory 11 may also include both an internal storage unit and an external storage device of the channel estimation apparatus of the SIMO system. The memory 11 may be used not only to store application software installed in a channel estimation apparatus of an SIMO system and various kinds of data, such as a code of a channel estimation program, etc., but also to temporarily store data that has been output or is to be output.
Processor 12, which in some embodiments may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data Processing chip, is configured to execute program code stored in memory 11 or to process data, such as to perform a channel estimation procedure.
The communication bus 13 is used to realize connection communication between these components.
The network interface 14 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and is typically used to establish a communication link between the channel estimation device of the SIMO system and other electronic devices.
Optionally, the channel estimation apparatus of the SIMO system may further include a user interface, where the user interface may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further include a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. Wherein the display, which may also be appropriately referred to as a display screen or display unit, is used for displaying information processed in the channel estimation device of a SIMO system and for displaying a visualized user interface.
While fig. 4 shows only the channel estimation device of an SIMO system with components 11-14 and a channel estimation procedure, those skilled in the art will appreciate that the configuration shown in fig. 4 does not constitute a limitation of the channel estimation device of an SIMO system and may include fewer or more components than those shown, or some components in combination, or a different arrangement of components.
In the embodiment of the channel estimation apparatus of the SIMO system shown in fig. 4, the memory 11 stores a channel estimation program; the processor 12, when executing the channel estimation program stored in the memory 11, implements the following steps:
a transmission data acquisition step: acquiring a data frame sent by a sending end of the SIMO system; the data frame comprises a training sequence and a data sequence; wherein, the SIMO system comprises a transmitting end and a receiving end, the transmitting end is provided with 1 transmitting antenna, and the receiving end is provided with NSA receiving antenna, NSAre known;
a proportion estimation step: calculating the channel proportional relation of a plurality of receiving antennas of the receiving end according to the data received by each receiving antenna of the receiving end of the SIMO system; the data received by each receiving antenna is data corresponding to the data sequence in the data frame or data corresponding to the data frame; a channel is formed between the transmitting antenna of the transmitting end and each receiving antenna of the receiving end;
a received data acquisition step: acquiring a data signal corresponding to the training sequence received by the receiving end;
and (3) optimizing: and optimizing the channel proportional relation and the data signal which is received by the receiving end and corresponds to the training sequence according to a set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result.
Further, the scale estimating step includes: firstly, deducing a channel expression of each receiving antenna of a receiving end according to data corresponding to the data frame or data corresponding to the data sequence received by each receiving antenna of the receiving end; and then obtaining the channel proportion relation of a plurality of receiving antennas according to the channel expression of each receiving antenna.
Further, in the ratio estimating step: deriving a channel expression of each receiving antenna of the receiving end according to the data corresponding to the data sequence received by each receiving antenna of the receiving end specifically includes:
setting the data corresponding to the data sequence received by the ith receiving antenna of the receiving end as
Figure BDA0003127173080000131
Wherein the content of the first and second substances,
Figure BDA0003127173080000132
the nth data corresponding to the data sequence received by the ith receiving antenna of the receiving end is represented;
the channel expression h of the ith receiving antennaiExpressed as:
Figure BDA0003127173080000133
wherein z isi,nNoise of nth data corresponding to the data sequence received for an ith receiving antenna; dnIs the nth data of the data sequence; i is an element of [1, N ∈s]，n∈[1,N](ii) a N represents the data length of the data sequence;
channel proportional relation h of multiple receiving antennas1:
Figure BDA0003127173080000134
Comprises the following steps:
Figure BDA0003127173080000135
further, the scale estimating step further includes:
proportional deformation step: firstly, equation (2) is transformed into equation (3):
Figure BDA0003127173080000136
then, under the condition that the channel in one frame of data is kept unchanged, the formula (3) is transformed into a formula (4) according to an averaging algorithm;
Figure BDA0003127173080000137
obtaining the channel expression h of each receiving antenna according to the formula (4)iAnd aiThe following conditions are satisfied:
Figure BDA0003127173080000138
(5) and b is a constant.
Further, the optimizing step includes: and optimizing the channel proportional relation and the data signal corresponding to the training sequence received by the receiving end according to a set optimization criterion, solving the optimal solution of b under the condition of meeting the optimization criterion, and then obtaining the channel estimation of each receiving antenna according to the optimal solution of b and a formula (5).
Further, setting data corresponding to the training sequence received by each receiving antenna of the receiving end as
Figure BDA0003127173080000141
Wherein the content of the first and second substances,
Figure BDA0003127173080000142
represents the kth data corresponding to the training sequence received by the ith receiving antenna of the receiving end, and k belongs to [1, N ]t]；NtRepresents the data length of the training sequence;
receiving a data signal Y corresponding to the training sequence received by a receiving end under the condition that a channel in one frame of data is kept unchangedpExpressed as:
Yp＝hpT+Zp＝bapT+Zp；
Figure BDA0003127173080000143
corresponding to the training sequence received by a receiving endThe data signal of (1);
Figure BDA0003127173080000144
is a channel vector;
Figure BDA0003127173080000145
for the transposition of the training sequence vector, T represents the transposition;
Figure BDA0003127173080000146
is a vector of coefficients of the channel scale relationship in equation (4); zpFor the noise matrix:
Figure BDA0003127173080000147
further, the optimization criteria include a least squares method and a least mean squares error method.
Further, when the optimization criterion is the least square method, the objective function is set to s (b) | | Yp-bapT||；
When S (b) is minimum, optimal solution of b
Figure BDA0003127173080000148
Comprises the following steps:
Figure BDA0003127173080000149
wherein H is a conjugate transpose;
the channel estimate is derived from equation (5) and equation (8) as:
Figure BDA00031271730800001410
EXAMPLE III
A storage medium being a computer readable storage medium having stored thereon a channel estimation program being a computer program which when executed by a processor performs the steps of:
a transmission data acquisition step: for obtaining SIMO systemsA data frame sent by a sending end; the data frame comprises a training sequence and a data sequence; wherein, the SIMO system comprises a transmitting end and a receiving end, the transmitting end is provided with 1 transmitting antenna, and the receiving end is provided with NSA receiving antenna, NSAre known;
a proportion estimation step: calculating the channel proportional relation of a plurality of receiving antennas of the receiving end according to the data received by each receiving antenna of the receiving end of the SIMO system; the data received by each receiving antenna is data corresponding to the data sequence in the data frame or data corresponding to the data frame; a channel is formed between the transmitting antenna of the transmitting end and each receiving antenna of the receiving end;
a received data acquisition step: acquiring a data signal corresponding to the training sequence received by the receiving end;
and (3) optimizing: and optimizing the channel proportional relation and the data signal which is received by the receiving end and corresponds to the training sequence according to a set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result.
Further, the scale estimating step includes: firstly, deducing a channel expression of each receiving antenna of a receiving end according to data corresponding to the data frame or data corresponding to the data sequence received by each receiving antenna of the receiving end; and then obtaining the channel proportion relation of a plurality of receiving antennas according to the channel expression of each receiving antenna.
Further, in the ratio estimating step: deriving a channel expression of each receiving antenna of the receiving end according to the data corresponding to the data sequence received by each receiving antenna of the receiving end specifically includes:
setting the data corresponding to the data sequence received by the ith receiving antenna of the receiving end as
Figure BDA0003127173080000161
Wherein the content of the first and second substances,
Figure BDA0003127173080000162
the nth data corresponding to the data sequence received by the ith receiving antenna of the receiving end is represented;
the channel expression h of the ith receiving antennaiExpressed as:
Figure BDA0003127173080000163
wherein z isi,nNoise of nth data corresponding to the data sequence received for an ith receiving antenna; dnIs the nth data of the data sequence; i is an element of [1, N ∈s]，n∈[1,N](ii) a N represents the data length of the data sequence;
channel proportional relation h of multiple receiving antennas1:
Figure BDA0003127173080000164
Comprises the following steps:
Figure BDA0003127173080000165
further, the scale estimating step further includes:
proportional deformation step: firstly, equation (2) is transformed into equation (3):
Figure BDA0003127173080000166
then, under the condition that the channel in one frame of data is kept unchanged, the formula (3) is transformed into a formula (4) according to an averaging algorithm;
Figure BDA0003127173080000167
obtaining the channel expression h of each receiving antenna according to the formula (4)iAnd aiThe following conditions are satisfied:
Figure BDA0003127173080000168
(5) and b is a constant.
Further, the optimizing step includes: and optimizing the channel proportional relation and the data signal corresponding to the training sequence received by the receiving end according to a set optimization criterion, solving the optimal solution of b under the condition of meeting the optimization criterion, and then obtaining the channel estimation of each receiving antenna according to the optimal solution of b and a formula (5).
Further, setting data corresponding to the training sequence received by each receiving antenna of the receiving end as
Figure BDA0003127173080000171
Wherein the content of the first and second substances,
Figure BDA0003127173080000172
represents the kth data corresponding to the training sequence received by the ith receiving antenna of the receiving end, and k belongs to [1, N ]t]；NtRepresents the data length of the training sequence;
receiving a data signal Y corresponding to the training sequence received by a receiving end under the condition that a channel in one frame of data is kept unchangedpExpressed as:
Yp＝hpT+Zp＝bapT+Zp；
Figure BDA0003127173080000173
the data signal corresponding to the training sequence is received by a receiving end;
Figure BDA0003127173080000174
is a channel vector;
Figure BDA0003127173080000175
for the transposition of the training sequence vector, T represents the transposition;
Figure BDA0003127173080000176
is a vector of coefficients of the channel scale relationship in equation (4); zpFor the noise matrix:
Figure BDA0003127173080000177
further, the optimization criteria include a least squares method and a least mean squares error method.
Further, when the optimization criterion is the least square method, the objective function is set to s (b) | | Yp-bapT||；
When S (b) is minimum, optimal solution of b
Figure BDA0003127173080000178
Comprises the following steps:
Figure BDA0003127173080000179
wherein H is a conjugate transpose;
the channel estimate is derived from equation (5) and equation (8) as:
Figure BDA00031271730800001710
the above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.

Claims (10)

1. A channel estimation method for an SIMO system, the channel estimation method comprising:
a transmission data acquisition step: acquiring a data frame sent by a sending end of the SIMO system; the data frame comprises a training sequence and a data sequence; wherein, the SIMO system comprises a transmitting end and a receiving end, the transmitting end is provided with 1 transmitting antenna, and the receiving end is provided with NSA receiving antenna, NSAre known;
a proportion estimation step: calculating the channel proportional relation of a plurality of receiving antennas of the receiving end according to the data received by each receiving antenna of the receiving end of the SIMO system; the data received by each receiving antenna is data corresponding to the data sequence in the data frame or data corresponding to the data frame; a channel is formed between the transmitting antenna of the transmitting end and each receiving antenna of the receiving end;
a received data acquisition step: acquiring a data signal corresponding to the training sequence received by the receiving end;
and (3) optimizing: and optimizing the channel proportional relation and the data signal which is received by the receiving end and corresponds to the training sequence according to a set optimization criterion to obtain an optimization result, and obtaining the channel estimation of each receiving antenna of the receiving end according to the optimization result.
2. The channel estimation method of the SIMO system as claimed in claim 1, wherein the scale estimation step includes: firstly, deducing a channel expression of each receiving antenna of a receiving end according to data corresponding to the data frame or data corresponding to the data sequence received by each receiving antenna of the receiving end; and then obtaining the channel proportion relation of a plurality of receiving antennas according to the channel expression of each receiving antenna.
3. The channel estimation method of the SIMO system as claimed in claim 2, wherein the scale estimation step: deriving a channel expression of each receiving antenna of the receiving end according to the data corresponding to the data sequence received by each receiving antenna of the receiving end specifically includes:
setting the data corresponding to the data sequence received by the ith receiving antenna of the receiving end as
Figure FDA0003127173070000021
Wherein the content of the first and second substances,
Figure FDA0003127173070000022
the nth data corresponding to the data sequence received by the ith receiving antenna of the receiving end is represented;
the channel expression h of the ith receiving antennaiExpressed as:
Figure FDA0003127173070000023
wherein z isi,nNoise of nth data corresponding to the data sequence received for an ith receiving antenna; d represents a data sequence of length N, dnIs the nth data of the data sequence; i is an element of [1, N ∈s]，n∈[1,N](ii) a N represents the data length of the data sequence;
channel ratio of multiple receiving antennas
Figure FDA0003127173070000024
Comprises the following steps:
Figure FDA0003127173070000025
4. the channel estimation method of the SIMO system as claimed in claim 3, wherein the scale estimation step further includes:
proportional deformation step: firstly, equation (2) is transformed into equation (3):
Figure FDA0003127173070000026
then, under the condition that the channel in one frame of data is kept unchanged, the formula (3) is transformed into a formula (4) according to an averaging algorithm;
Figure FDA0003127173070000027
obtaining the channel expression h of each receiving antenna according to the formula (4)iAnd aiThe following conditions are satisfied:
Figure FDA0003127173070000028
Figure FDA0003127173070000029
b is a constant.
5. The channel estimation method of the SIMO system as claimed in claim 4, wherein the optimizing step comprises: and optimizing the channel proportional relation and the data signal corresponding to the training sequence received by the receiving end according to a set optimization criterion, solving the optimal solution of b under the condition of meeting the optimization criterion, and then obtaining the channel estimation of each receiving antenna according to the optimal solution of b and a formula (5).
6. The channel estimation method of an SIMO system as claimed in claim 5, wherein the data received by each receiving antenna of the receiving end corresponding to said training sequence is set as data mark
Figure FDA0003127173070000031
Wherein the content of the first and second substances,
Figure FDA0003127173070000032
represents the kth data corresponding to the training sequence received by the ith receiving antenna of the receiving end, and k belongs to [1, N ]t]；NtRepresents the data length of the training sequence;
receiving a data signal Y corresponding to the training sequence received by a receiving end under the condition that a channel in one frame of data is kept unchangedpExpressed as:
Yp＝hpT+Zp＝bapT+Zp；
Figure FDA0003127173070000033
the data signal corresponding to the training sequence is received by a receiving end;
Figure FDA0003127173070000034
is a channel vector;
Figure FDA0003127173070000035
for the transposition of the training sequence vector, T represents the transposition;
Figure FDA0003127173070000036
is a vector of coefficients of the channel scale relationship in equation (4); zpFor the noise matrix:
Figure FDA0003127173070000037
7. the channel estimation method of the SIMO system as claimed in claim 6, wherein the optimization criterion includes least square method and least mean square error method.
8. The channel estimation method of an SIMO system as claimed in claim 7, wherein when the optimization criterion is the least square method, the objective function is set to s (b) Yp-bapT||；
When S (b) is minimum, optimal solution of b
Figure FDA0003127173070000038
Comprises the following steps:
Figure FDA0003127173070000041
wherein H is a conjugate transpose;
the channel estimate is derived from equation (5) and equation (8) as:
Figure FDA0003127173070000042
9. a channel estimation apparatus for a SIMO system, comprising a memory and a processor, the memory having stored thereon a channel estimation program operable on the processor, the channel estimation program being a computer program, characterized in that: the processor, when executing the channel estimation procedure, performs the steps of a method of channel estimation for a SIMO system as claimed in any of claims 1-8.
10. A storage medium which is a computer-readable storage medium having a channel estimation program stored thereon, the channel estimation program being a computer program characterized in that: the channel estimation program when executed by a processor implements the steps of a channel estimation method of a SIMO system as claimed in any one of claims 1-8.
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Publication number Priority date Publication date Assignee Title
US20080101495A1 (en) * 2006-10-30 2008-05-01 Broadcom Corporation, A California Corporation MIMO channel estimation in presence of sampling frequency offset
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