CN114024589A - MISO communication system design method and device - Google Patents

MISO communication system design method and device Download PDF

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CN114024589A
CN114024589A CN202111344857.1A CN202111344857A CN114024589A CN 114024589 A CN114024589 A CN 114024589A CN 202111344857 A CN202111344857 A CN 202111344857A CN 114024589 A CN114024589 A CN 114024589A
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antenna
subset
communication system
noise ratio
signal
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CN114024589B (en
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张沛昌
夏商
黄磊
赵博
钱恭斌
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Shenzhen University
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Shenzhen University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0602—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using antenna switching
    • H04B7/0608—Antenna selection according to transmission parameters

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Abstract

The invention provides a method and a device for designing a MISO communication system, wherein the MISO communication system comprises a transmitting terminal AP, an intelligent reflecting surface IRS and a receiving terminal user UE, the method for designing the MISO communication system comprises the steps of selecting a surface antenna of the transmitting terminal AP through a discrete cuckoo antenna selection algorithm, and selecting N with the maximum direct path signal-to-noise ratio corresponding to the transmitting terminal AP to the end user UESA root antenna; according to the selected NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side. The invention has the beneficial effects that: the whole MISO communication system improves the performance, and simultaneously does not need to increase the number of radio frequency chains so as to reduce the cost and the energy consumption of hardware.

Description

MISO communication system design method and device
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for designing a MISO communication system.
Background
With the rapid development of 5G wireless networks, the number of devices accessed in the wireless network is greatly increased. However, the increase in hardware cost and energy consumption in wireless networks remains an unresolved key issue. As an emerging technology proposed in recent years, an Intelligent Reflecting Surface (IRS) is formed by a large number of low-cost passive Reflecting elements, each of which can independently generate amplitude and/or phase changes for an incident signal, thereby cooperatively realizing three-dimensional reflection. Meanwhile, the intelligent reflecting surface does not need to transmit a radio frequency chain, so that the hardware cost and the energy consumption can be reduced. However, the number of rf chains at the transmitting end of the system cannot be reduced by using the intelligent reflecting surface. Therefore, in order to improve the performance of the system without increasing the number of radio frequency links, a MISO communication system design method combining an antenna selection technology and an IRS is proposed.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: a method for designing MISO communication system is provided to improve the receiving S/N ratio of user.
In order to solve the technical problems, the invention adopts the technical scheme that: a MISO communication system design method, the MISO communication system includes the transmitting terminal AP, the intelligent reflection surface IRS and the receiving terminal user UE, the MISO communication system design method includes the steps,
s10, selecting the surface antenna of the transmitting terminal AP through a discrete cuckoo antenna selection algorithm, and selecting N with the maximum direct path signal-to-noise ratio corresponding to the transmitting terminal AP to the receiving terminal user UESA root antenna;
s20, according to the selected NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
Further, step S10 specifically includes:
s11, randomly generating NSA subset of possible antennas
Figure BDA0003349171480000011
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure BDA0003349171480000021
Wherein
Figure BDA0003349171480000022
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure BDA0003349171480000023
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
s12, updating the antenna subset to
Figure BDA0003349171480000024
The global search strategy is expressed as
Figure BDA0003349171480000025
Where a is the step-size factor and,
Figure BDA0003349171480000026
is a point product operation, e is a random step size according with the Lewy distribution,
Figure BDA0003349171480000027
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure BDA0003349171480000028
S13, COMPARATIVE FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
S14, updating the antenna subset to
Figure BDA0003349171480000029
The local search strategy is expressed as
Figure BDA00033491714800000210
Wherein
Figure BDA00033491714800000211
Is a solution in the subset T, gamma, epsilon are random numbers subject to uniform distributionH (p-epsilon) is the jump function, p is the probability of discarding the existing solution,
Figure BDA00033491714800000212
is in the subset T except
Figure BDA00033491714800000213
A certain set of (2);
s15, COMPARATIVE FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with Tn；
S16, finally passing through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
Further, step S12 includes rounding down the values of the antenna subsets updated by the global search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
Further, step S14 includes rounding down the values of the antenna subsets updated by the local search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
Further, in step S20, the receiving snr of the receiving end user UE is calculated as follows:
Figure BDA00033491714800000214
s.t.wHw＜Pt
|Vm|＝1，m＝1，...，M
using a maximum transmission scheme
Figure BDA00033491714800000215
And finally, obtaining the final receiving signal-to-noise ratio of the receiving end user UE by adopting an SDR algorithm, wherein the transmitting end AP to the intelligent reflection surface IRS, the intelligent reflection surface IRS to the receiving end user UE and the transmitting end AP to the receiving endThe channels between the receiving end users UE are respectively represented as: G. h isr、hd(ii) a M is the number of reflective elements of the Intelligent reflective surface IRS, PtIs the transmit power.
Another technical solution of the present invention is a MISO communication system design apparatus, the MISO communication system includes a transmitting end AP, an intelligent reflective surface IRS, and a receiving end user UE, the MISO communication system design apparatus includes,
an antenna selection module, configured to select a surface antenna of the transmitting end AP through a discrete cuckoo antenna selection algorithm, and select N where a direct path signal-to-noise ratio from the transmitting end AP to the receiving end user UE is the largestSA root antenna;
a signal-to-noise ratio calculation module for selecting NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
Further, the antenna selection module specifically includes:
an antenna subset generation unit for randomly generating NSA subset of possible antennas
Figure BDA0003349171480000031
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure BDA0003349171480000032
Wherein
Figure BDA0003349171480000033
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure BDA0003349171480000034
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
a global search unit for updating the antenna subset to
Figure BDA0003349171480000035
The global search strategy is expressed as
Figure BDA0003349171480000036
Where a is the step-size factor and,
Figure BDA0003349171480000037
is a point product operation, e is a random step size according with the Lewy distribution,
Figure BDA0003349171480000038
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure BDA0003349171480000039
A first comparison unit for comparing FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
A local search unit for updating the antenna subset to
Figure BDA00033491714800000310
The local search strategy is expressed as
Figure BDA00033491714800000311
Wherein
Figure BDA00033491714800000312
Is a solution in the subset T, gamma, epsilon are random numbers obeying uniform distribution, h (p-epsilon) is the hopping function, p is the probability of discarding the existing solution,
Figure BDA00033491714800000313
is in the subset T except
Figure BDA00033491714800000314
A certain set of (2);
a second comparison unit for comparing FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with F ″)n；
An iteration unit for the final pass through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
Further, the global search unit further performs rounding-down on the values of the antenna subsets updated by the global search strategy to replace the decimal, and performs re-random value selection on the antenna indexes in the same subset to remove the repeated antenna indexes.
Further, the local search unit further performs rounding-down on values of the antenna subsets updated by the local search strategy to replace the decimal, and performs re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
Further, in the snr calculation module, a calculation formula of the received snr of the receiving end user UE is as follows:
Figure BDA0003349171480000041
s.t.wHw＜Pt
|Vm|＝1，m＝1，...，M
using a maximum transmission scheme
Figure BDA0003349171480000042
And finally, obtaining a final receiving signal-to-noise ratio of the receiving end user UE by adopting an SDR algorithm, wherein channels from the transmitting end AP to the intelligent reflection surface IRS, from the intelligent reflection surface IRS to the receiving end user UE and from the transmitting end AP to the receiving end user UE are respectively expressed as follows: G. h isr、hd(ii) a M is the number of reflective elements of the Intelligent reflective surface IRS, PtIs the transmit power.
The invention has the beneficial effects that: the number of radio frequency chains at a transmitting end can be reduced by using an antenna selection technology, and meanwhile, the receiving signal-to-noise ratio of a system is increased; the intelligent reflecting surface technology is used for enhancing the receiving signal-to-noise ratio of the whole system, and simultaneously, as the intelligent reflecting surface technology is formed by passive elements, a radio frequency chain is not needed. Therefore, the whole MISO communication system improves the performance, and reduces the number of radio frequency chains so as to reduce the cost and the energy consumption of hardware.
Drawings
The following detailed description of the invention refers to the accompanying drawings.
FIG. 1 is a block diagram of a MISO communication system in accordance with an embodiment of the present invention;
FIG. 2 is a simulation diagram of the SNR for user reception according to an embodiment of the present invention;
FIG. 3 is a flow chart of a MISO communication system design method in accordance with an embodiment of the present invention;
FIG. 4 is a block diagram of a MISO communication system design apparatus in accordance with an embodiment of the present invention;
FIG. 5 is a schematic block diagram of a computer device in accordance with a specific embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As shown in fig. 3, the first embodiment of the present invention is: a MISO communication system design method, as shown in FIG. 1, the MISO communication system includes a transmitting end AP, an intelligent reflective surface IRS and a receiving end user UE, the MISO communication system design method includes steps,
s10, selecting the surface antenna of the transmitting terminal AP through a discrete cuckoo antenna selection algorithm, and selecting N with the maximum direct path signal-to-noise ratio corresponding to the transmitting terminal AP to the receiving terminal user UESA root antenna;
s20, according to the selected NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
In the scheme, N antennas are arranged at the AP position of the transmitting end, and the selected number of the transmitting antennas is NS(NS< N), wherein NSThat is, the number of radio frequencies, the intelligent reflective surface IRS has M reflective units, and the receiving-end user UE has one antenna. And (3) performing direct path antenna selection and beam forming design at the transmitting end AP, and performing phase shift angle optimization on the intelligent reflecting surface.
Wherein, step S10 specifically includes:
s11, randomly generating NSA subset of possible antennas
Figure BDA0003349171480000051
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure BDA0003349171480000061
Wherein
Figure BDA0003349171480000062
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure BDA0003349171480000063
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
s12, updating the antenna subset to
Figure BDA0003349171480000064
The global search strategy is expressed as
Figure BDA0003349171480000065
Where a is the step-size factor and,
Figure BDA0003349171480000066
is a point product operation, e is a random step size according with the Lewy distribution,
Figure BDA0003349171480000067
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure BDA0003349171480000068
S13, COMPARATIVE FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
S14, updating the antenna subset to
Figure BDA0003349171480000069
The local search strategy is expressed as
Figure BDA00033491714800000610
Wherein
Figure BDA00033491714800000611
Is a solution in the subset T, gamma, epsilon are random numbers obeying uniform distribution, h (p-epsilon) is the hopping function, p is the probability of discarding the existing solution,
Figure BDA00033491714800000612
is in the subset T except
Figure BDA00033491714800000613
A certain set of (2);
s15, COMPARATIVE FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with Tn；
S16, finally passing through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
In step S12, the method further includes rounding down the values of the antenna subsets updated by the global search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
In step S14, the method further includes rounding down the values of the antenna subsets updated by the local search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
In step S20, the calculation formula of the received snr of the receiving end user UE is as follows:
Figure BDA00033491714800000614
s.t.wHw＜Pt
|Vm|＝1，m＝1，...，M
using a maximum transmission scheme
Figure BDA00033491714800000615
And finally, obtaining a final receiving signal-to-noise ratio of the receiving end user UE by adopting an SDR algorithm, wherein channels from the transmitting end AP to the intelligent reflection surface IRS, from the intelligent reflection surface IRS to the receiving end user UE and from the transmitting end AP to the receiving end user UE are respectively expressed as follows: G. h isr、hd(ii) a M is intelligent reflectometerNumber of reflecting elements of surface IRS, PtIs the transmit power.
In the embodiment, the number of radio frequency chains at the transmitting end can be reduced by using an antenna selection technology, and meanwhile, the receiving signal-to-noise ratio of the system is increased; the intelligent reflecting surface technology is used for enhancing the receiving signal-to-noise ratio of the whole system, and simultaneously, as the intelligent reflecting surface technology is formed by passive elements, a radio frequency chain is not needed. Therefore, the whole MISO communication system improves the performance, and reduces the number of radio frequency chains so as to reduce the cost and the energy consumption of hardware. The final simulation results are shown in fig. 2, and it can be seen that the MISO system combining direct path antenna selection and intelligent reflector performs better than the one without combining the two technologies.
As shown in fig. 4, another embodiment of the present invention is a MISO communication system design apparatus, as shown in fig. 1, the MISO communication system includes a transmitting side AP, an intelligent reflective surface IRS, and a receiving side user UE, the MISO communication system design apparatus includes,
an antenna selection module 10, configured to select a surface antenna of the transmitting end AP through a discrete cuckoo antenna selection algorithm, and select N with the largest direct path signal-to-noise ratio from the transmitting end AP to the receiving end user UESA root antenna;
a signal-to-noise ratio calculating module 20 for calculating N according to the selected NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
The antenna selection module 10 specifically includes:
an antenna subset generation unit for randomly generating NSA subset of possible antennas
Figure BDA0003349171480000071
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure BDA0003349171480000072
Wherein
Figure BDA0003349171480000073
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure BDA0003349171480000074
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
a global search unit for updating the antenna subset to
Figure BDA0003349171480000075
The global search strategy is expressed as
Figure BDA0003349171480000076
Where a is the step-size factor and,
Figure BDA0003349171480000077
is a point product operation, e is a random step size according with the Lewy distribution,
Figure BDA0003349171480000078
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure BDA0003349171480000079
A first comparison unit for comparing FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
A local search unit for updating the antenna subset to
Figure BDA0003349171480000081
The local search strategy is expressed as
Figure BDA0003349171480000082
Wherein
Figure BDA0003349171480000083
Is aA certain solution in the set T, gamma and epsilon are random numbers obeying uniform distribution, h (p-epsilon) is a hopping function, p is the probability of discarding the existing solution,
Figure BDA0003349171480000084
is in the subset T except
Figure BDA0003349171480000085
A certain set of (2);
a second comparison unit for comparing FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with Tn；
An iteration unit for the final pass through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
The global search unit further performs rounding-down on the values of the antenna subsets updated by the global search strategy to replace the decimal, and performs random value selection again on the antenna indexes in the same subset to remove the repeated antenna indexes.
The local search unit further performs rounding-down on the values of the antenna subsets updated by the local search strategy to replace the decimal, and performs random value selection again on the antenna indexes in the same subset to remove the repeated antenna indexes.
In the snr calculation module, a calculation formula of the received snr of the receiving end user UE is as follows:
Figure BDA0003349171480000086
s.t.wHw＜Pt
|Vm|＝1，m＝1，...，M
using a maximum transmission scheme
Figure BDA0003349171480000087
Finally, SDR algorithm is adopted to obtain the final receiving signal-to-noise ratio of receiving end user UEAnd the channels from the transmitting end AP to the intelligent reflection surface IRS, from the intelligent reflection surface IRS to the receiving end user UE and from the transmitting end AP to the receiving end user UE are respectively expressed as follows: G. h isr、hd(ii) a M is the number of reflective elements of the Intelligent reflective surface IRS, PtIs the transmit power.
It should be noted that, as can be clearly understood by those skilled in the art, the specific implementation process of the MISO communication system design apparatus and each unit may refer to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, no further description is provided herein.
The MISO communication system designing apparatus described above may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 5.
Referring to fig. 5, fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a terminal or a server, where the terminal may be an electronic device with a communication function, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, and a wearable device. The server may be an independent server or a server cluster composed of a plurality of servers.
Referring to fig. 5, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer programs 5032 comprise program instructions that, when executed, cause the processor 502 to perform a MISO communication system design method.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the execution of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 may be caused to execute a MISO communication system design method.
The network interface 505 is used for network communication with other devices. Those skilled in the art will appreciate that the configuration shown in fig. 5 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation of the computer device 500 to which the present application may be applied, and that a particular computer device 500 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to run the computer program 5032 stored in the memory to implement the MISO communication system design method as described above.
It should be understood that in the embodiment of the present Application, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing associated hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program comprises program instructions. The program instructions, when executed by the processor, cause the processor to perform the MISO communication system design method as described above.
The storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, which can store various computer readable storage media.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A MISO communication system design method, characterized by: the MISO communication system comprises a transmitting terminal AP, an intelligent reflecting surface IRS and a receiving terminal user UE, the design method of the MISO communication system comprises the steps,
s10, selecting the surface antenna of the transmitting terminal AP through a discrete cuckoo antenna selection algorithm, and selecting N with the maximum direct path signal-to-noise ratio corresponding to the transmitting terminal AP to the end user UESA root antenna;
s20, according to the selected NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
2. The MISO communication system design method of claim 1, wherein: step S10 specifically includes:
s11, randomly generating NSA subset of possible antennas
Figure FDA0003349171470000011
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure FDA0003349171470000012
Wherein
Figure FDA0003349171470000013
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure FDA0003349171470000014
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
s12, updating the antenna subset to
Figure FDA0003349171470000015
The global search strategy is expressed as
Figure FDA0003349171470000016
Where a is the step-size factor and,
Figure FDA0003349171470000017
is a point product operation, e is a random step size according with the Lewy distribution,
Figure FDA0003349171470000018
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure FDA0003349171470000019
S13, COMPARATIVE FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
S14, updating the antenna subset to
Figure FDA00033491714700000110
The local search strategy is expressed as
Figure FDA00033491714700000111
Wherein
Figure FDA00033491714700000112
Is a solution in the subset T, gamma, epsilon are random numbers obeying uniform distribution, h (p-epsilon) is the hopping function, p is the probability of discarding the existing solution,
Figure FDA00033491714700000113
is in the subset T except
Figure FDA00033491714700000114
A certain set of (2);
s15, COMPARATIVE FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with Tn；
S16, finally passing through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
3. The MISO communication system design method of claim 2, wherein: in step S12, the method further includes rounding down the values of the antenna subsets updated by the global search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
4. The MISO communication system design method of claim 3, wherein: in step S14, the method further includes rounding down the values of the antenna subsets updated by the local search strategy to replace the decimal, and performing re-random value selection on the antenna indexes in the same subset to remove duplicate antenna indexes.
5. The MISO communication system design method of claim 4, wherein: in step S20, the calculation formula of the received snr of the receiving end user UE is as follows:
Figure FDA0003349171470000021
s.t.wHw＜Pt
|Vm|＝1，m＝1，...，M
using a maximum transmission scheme
Figure FDA0003349171470000022
And finally, obtaining a final receiving signal-to-noise ratio of the receiving end user UE by adopting an SDR algorithm, wherein channels from the transmitting end AP to the intelligent reflection surface IRS, from the intelligent reflection surface IRS to the receiving end user UE and from the transmitting end AP to the receiving end user UE are respectively expressed as follows: G. h isr、hd(ii) a M is the number of reflective elements of the Intelligent reflective surface IRS, PtIs the transmit power.
6. A MISO communication system designing apparatus characterized by: the MISO communication system comprises a transmitting terminal AP, an intelligent reflecting surface IRS and a receiving terminal user UE, the MISO communication system design device comprises,
an antenna selection module for selecting the surface antenna of the transmitting terminal AP through a discrete cuckoo antenna selection algorithm, and selecting the N with the maximum signal-to-noise ratio of the direct path corresponding to the transmitting terminal AP to the end user UESA root antenna;
a signal-to-noise ratio calculation module for selecting NSAnd transmitting signals by the AP of the transmitting end through the intelligent reflecting surface and the direct path by the root antenna to obtain the receiving signal-to-noise ratio of the UE of the user side.
7. The MISO communication system design apparatus of claim 6, wherein: the antenna selection module specifically includes:
an antenna subset generation unit for randomly generating NSA subset of possible antennas
Figure FDA0003349171470000023
Wherein T isnRepresenting one possible antenna subset, and calculating user signal-to-noise ratio corresponding to the possible antenna subsets
Figure FDA0003349171470000024
Wherein
Figure FDA0003349171470000025
w is a beamforming vector, employing a maximum ratio transmission scheme
Figure FDA0003349171470000026
PtIs the transmit power, σ2Is the noise power, hdIs a channel from the transmitting end AP to the receiving end user UE;
a global search unit for updating the antenna subset to
Figure FDA0003349171470000031
The global search strategy is expressed as
Figure FDA0003349171470000032
Where a is the step-size factor and,
Figure FDA0003349171470000033
is a point product operation, e is a random step size according with the Lewy distribution,
Figure FDA0003349171470000034
is a set in the subset T, and calculates the user signal-to-noise ratio corresponding to the updated T
Figure FDA0003349171470000035
A first comparison unit for comparing FnAnd F'nIf F isn＜F′nThen T will benIs replaced by T'n；
A local search unit for updating the antenna subset to
Figure FDA0003349171470000036
The local search strategy is expressed as
Figure FDA0003349171470000037
Wherein
Figure FDA0003349171470000038
Is a solution in the subset T, gamma, epsilon are random numbers obeying uniform distribution, h (p-epsilon) is the hopping function, p is the probability of discarding the existing solution,
Figure FDA0003349171470000039
is in the subset T except
Figure FDA00033491714700000310
A certain set of (2);
a second comparison unit for comparing FnAnd F ″)nIf F isn＜F″nThen T will benReplacement is with Tn；
An iteration unit for the final pass through NSAfter the iteration, selecting T with the maximum corresponding signal-to-noise ratio in TnAs a final result.
8. The MISO communication system designing apparatus according to claim 7, wherein: the global search unit further performs rounding-down on the values of the antenna subsets updated by the global search strategy to replace the decimal, and performs random value selection again on the antenna indexes in the same subset to remove the repeated antenna indexes.
9. The MISO communication system design apparatus of claim 8, wherein: the local search unit further performs rounding-down on the values of the antenna subsets updated by the local search strategy to replace the decimal, and performs random value selection again on the antenna indexes in the same subset to remove the repeated antenna indexes.
10. The MISO communication system design apparatus of claim 9, wherein: in the snr calculation module, the receiving snr of the receiving end user UE is calculated as follows:
Figure FDA00033491714700000311
s.t.wHw＜Pt
|Vm|＝1，m＝1，…，M
using a maximum transmission scheme
Figure FDA00033491714700000312
And finally, obtaining a final receiving signal-to-noise ratio of the receiving end user UE by adopting an SDR algorithm, wherein channels from the transmitting end AP to the intelligent reflection surface IRS, from the intelligent reflection surface IRS to the receiving end user UE and from the transmitting end AP to the receiving end user UE are respectively expressed as follows: G. h isr、hd(ii) a M is the number of reflective elements of the Intelligent reflective surface IRS, PtIs the transmit power.
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