CN112532289A - Multi-antenna multicast transmission method of symbiotic communication system based on intelligent reflection surface - Google Patents
Multi-antenna multicast transmission method of symbiotic communication system based on intelligent reflection surface Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- 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
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/0848—Joint weighting
- H04B7/0857—Joint weighting using maximum ratio combining techniques, e.g. signal-to- interference ratio [SIR], received signal strenght indication [RSS]
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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
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
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- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
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- H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
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Abstract
The invention belongs to the technical field of wireless communication, and relates to a multi-antenna multicast transmission method of a symbiotic communication system based on an intelligent reflection surface. The invention provides a multi-antenna multicast transmission method of a symbiotic communication system based on an intelligent reflection surface. The invention also provides a method for jointly optimizing the active beamforming W at the base station end and the passive beamforming phi at the intelligent surface end, and the minimum transmitting power of the base station is realized under the condition of meeting the signal-to-noise ratio requirements of a main receiver and an IoT receiver. Through simulation verification, the invention greatly saves the transmitting power and energy of the base station without influencing the normal communication of the main system, and does not additionally increase the frequency spectrum and the cost.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a multi-antenna multicast transmission method of a symbiotic communication system based on an intelligent reflection surface.
Background
Symbiotic Radio (SR) is a wireless communication technology with extremely high energy efficiency, high spectral efficiency and extremely low cost, which is proposed based on environmental backscatter communication, and has important application prospects in the field of Internet of Things (IoT) in large-scale vertical industries. Specifically, the passive backscatter devices can modulate their own information onto a received communication signal of the main system for transmission of the internet of things, and in return, the reflective links can provide additional multipaths to enhance communication of the main system, thereby achieving reciprocity of co-existing radio.
The reflective link has limited performance enhancement for the communication performance of the host system due to severe fading. The channel condition is improved, the coverage is increased and the reliability is improved by introducing Intelligent Reflecting Surface (IRS) (hereinafter referred to as Intelligent Surface) to assist the symbiotic communication. The IRS consists of a large number of passive reflection units, and each reflection unit can passively adjust the amplitude and the phase of an incident signal and reflect the incident signal, so that the IRS is a high-efficiency, energy-saving and low-cost technology. Therefore, by reasonably designing the reflection coefficient (amplitude and phase shift) of each reflection unit, the wireless propagation environment can be intelligently reconstructed, so as to achieve the aims of useful signal enhancement, interference suppression, safe transmission and the like.
On the other hand, multicast services have important application scenes in 5G and above systems, especially in the multimedia field, such as online live broadcast, remote education, video conference and the like. In the multi-antenna multicast transmission of the symbiotic communication system based on the intelligent surface, a Base Station (BS) sends independent information to each group of Primary Receivers (PR) in a multicast mode with the assistance of the intelligent surface, meanwhile, the intelligent surface is used as equipment of the Internet of things, and transmits the information to an IoT Receiver through a multicast signal of a Primary system so as to achieve the purpose of simultaneously enhancing the communication of the Primary system and supporting the Internet of things transmission.
Disclosure of Invention
The invention provides a multi-antenna multicast transmission method of a symbiotic communication system based on an intelligent surface, and relates to a system composition structure, a working principle and an active and passive combined beam forming design method.
The technical scheme adopted by the invention is the multi-antenna multicast transmission of the symbiotic communication system based on the intelligent surface: the system structure is shown in fig. 1, and comprises a base station configured with M antennas and a base station configured with Q antennasThe system comprises an IoT receiver of a wire, an intelligent surface comprising N passive reflection units, an IRS controller connected with the intelligent surface, and K single-antenna main receivers. Wherein the K main receivers are divided into G groups according to different information requirements,
the primary receivers in the same group request the same information at the same time and each primary receiver can only belong to one group, i.e. primary receivers
M is more than or equal to 1, Q is more than or equal to 1, K is more than or equal to 1, and G is more than or equal to 1 and less than or equal to K.
The basic working principle of the multi-antenna multicast transmission method of the symbiotic communication system based on the intelligent surface is as follows: the base station multicasts independent signals to each group of main receivers through active beam forming, and due to the shielding of obstacles, the channel response between the base station and the main receivers is weak, and the main link communication between the base station and the main receivers can be enhanced by controlling a reflection unit on an intelligent surface; on the other hand, the smart surface modulates its own information on a multicast signal using Binary Phase Shift Keying (BPSK) and transmits the modulated information to the IoT receiver. Thus, both the primary receiver and the IoT receiver receive two parts of the signal: a direct link signal from a base station and a reflected signal from a smart surface.
According to the above description, the signal received by the kth master receiver of the g-th group is represented as
Wherein s isg(l) And
respectively representing information symbols and active beam forming vectors sent by a base station to a g-th group of main receivers, and x represents intelligentThe transmission rate of the Internet of things is far less than the main transmission rate, so that one symbol period of x comprises L (L > 1) sg(l) The symbol period of (a) is,
a phase-shift matrix representing the smart surface,
a vector of phase shifts is represented that is,
and
respectively representing the base station to kth primary receiver channel, the smart surface to kth primary receiver channel and the base station to smart surface channel, zk(l) Indicating a power of
Zero mean additive white gaussian noise.
The signal received by the IoT receiver is denoted as
Wherein the content of the first and second substances,
and
respectively representing base station to IoT receiver channels and smart surface to IoT receiver channels,
indicating a power of
Zero mean additivity ofA gaussian white noise vector.
The invention provides an active and passive combined beam forming design method for multi-antenna multicast transmission of a symbiotic communication system based on an intelligent surface, which meets the requirement of ensuring the signal-to-interference-and-noise ratio of a main receiver in a main system
And IoT receiver signal-to-noise ratio requirement in communication of Internet of things
Under the premise of (1), the aim of minimizing the transmitting power of the base station is to jointly optimize the transmitting (active) beam forming of the base station end
And an intelligent surface-side phase-shift matrix (passive beamforming) Φ. The specific optimization problem is represented as follows:
the first constraint is the main receiver signal-to-interference-and-noise ratio requirement, the second constraint is to ensure that the IoT receiver can successfully demodulate the main signal, the third constraint is the IoT receiver signal-to-noise ratio requirement, and the fourth constraint is the phase shift constraint of the intelligent surface.
The constraints of the above problem include coupled variables and a plurality of components, which is a non-Convex Optimization problem, and consider the comprehensive utilization of alternate Optimization (Optimization) technology "Stephen Boyd and Lieven Vandenberghe, convergent Optimization, Cambridge unite v.press, 2004.", Quadratic transformation (Quadratic Transform) method "kaimng Shen and Wei Yu," sectional programming for communication systems — part I: power control and beamforming ". IEEE trans. Signal Processing, vol.66, No.10, pp.2616-2630, May, 2018", Semi-positive Relaxation (Semi-positive Relaxation) method "Zhi-Quan Luo, Wing-Kin Ma, equation Man-Cho So, YINyu Ye, and Shuzhong Zhang," Semidefinite Relaxation of quadrature optimization schemes, "IEEE Signal Processing Mag., vol.27, No.3, pp.20-34,2010", and designing an efficient iterative algorithm optimization solving problem (P1) to obtain a joint optimization design method of base station side transmit beamforming W and intelligent surface side phase shift matrix phi.
The invention has the beneficial effects that: a multi-antenna multicast transmission scheme of a symbiotic communication system based on an intelligent surface and a joint optimization design method of base station end active beam forming W and intelligent surface end passive beam forming phi are provided. The intelligent surface transmits its own internet of things information symbols through the multicast signal of the master system, the downlink multicast transmission from the base station to the master receiver can be enhanced through the intelligent surface, and the master receiver and the IoT receiver both receive the direct link signal from the base station and the reflected signal from the intelligent surface. The invention designs an efficient iterative algorithm to jointly optimize the active beamforming W at the base station end and the passive beamforming phi at the intelligent surface end, and realizes the minimum of the transmitting power of the base station under the condition of meeting the requirements of the signal-to-noise ratio of a main receiver and the signal-to-noise ratio of an IoT receiver. Through simulation verification, the invention greatly saves the transmitting power and energy of the base station without influencing the normal communication of the main system, does not additionally increase the frequency spectrum and the cost expenditure, and has strong application value and development potential.
Drawings
FIG. 1: the system of the invention is composed of a schematic diagram;
FIG. 2: simulating a three-dimensional coordinate system schematic diagram;
FIG. 3: a relation graph of base station transmitting power, main receiver signal-to-noise ratio and quantization bit number;
FIG. 4: and (3) a relation graph of base station transmitting power, the number of the intelligent surface reflection units and the signal-to-noise ratio of the IoT receiver.
Detailed Description
The invention is described in detail below with reference to the figures and simulation examples.
The invention provides a multi-antenna multicast transmission method of a symbiotic communication system based on an intelligent surface, which comprises the following steps: the system composition structure is as shown in fig. 1, and comprises a base station configured with M antennas, an IoT receiver configured with Q antennas, an intelligent surface including N passive reflection units and an IRS controller connected thereto, and K single-antenna main receivers. Wherein the K main receivers are divided into G groups according to different information requirements,
the primary receivers in the same group request the same information at the same time and each primary receiver can only belong to one group, i.e. primary receivers
M is more than or equal to 1, Q is more than or equal to 1, K is more than or equal to 1, and G is more than or equal to 1 and less than or equal to K.
The basic working principle of the multi-antenna multicast transmission method of the symbiotic communication system based on the intelligent surface is as follows: the base station multicasts independent signals to each group of main receivers through active beam forming, and due to the shielding of obstacles, the channel response between the base station and the main receivers is weak, and the main link communication between the base station and the main receivers can be enhanced by controlling a reflection unit on an intelligent surface; on the other hand, the smart surface modulates its own information on a multicast signal using Binary Phase Shift Keying (BPSK) and transmits the modulated information to the IoT receiver. Thus, both the primary receiver and the IoT receiver receive two parts of the signal: a direct link signal from a base station and a reflected signal from a smart surface.
According to the above description, the signal received by the kth master receiver of the g-th group is represented as
Wherein s isg(l) And
respectively representing information symbols and active beam forming vectors sent to a g group of main receivers by a base station, wherein x represents information symbols sent by an intelligent surface, and because the transmission rate of the Internet of things is far less than the main transmission rate, one symbol period of x contains L (L > 1) sg(l) The symbol period of (a) is,
a phase-shift matrix representing the smart surface,
a vector of phase shifts is represented that is,
and
respectively representing the base station to kth primary receiver channel, the smart surface to kth primary receiver channel and the base station to smart surface channel, zk(l) Indicating a power of
Zero mean additive white gaussian noise.
The signal received by the IoT receiver is denoted as
Wherein the content of the first and second substances,
and
respectively representing base station to IoT receiver channels and smart surface to IoT receiver channels,
indicating a power of
Zero mean additive gaussian white noise vector.
Typically, the base station multicasts an independent gaussian data symbol to each group of primary receivers, and
in demodulating the main link signal sg(l) In time, the period of the information sent by the intelligent surface is far longer than that of the main link signal sg(l) And thus the reflected signal is considered as a multipath component of the main link signal. And the modulation mode of the information symbol of the intelligent surface is BPSK, namely x belongs to {1, -1}, so that after x is expected, the signal-to-interference-and-noise ratio of the kth main receiver of the g group is
Wherein the content of the first and second substances,
in the present invention, the IoT receiver receives information transmitted by the smart surface through Successive Interference Cancellation (SIC) and Maximum Ratio Combining (MRC) methods. First, the IoT receiver decodes the primary link multicast signal sg(l) Then removed from the received signal by SIC and finally recoveredAnd outputting the Internet of things information symbol x sent by the intelligent surface. Thus, the IoT receiver decodes the primary link signal sg(l) Respectively expressed as the signal-to-interference-and-noise ratio of the decoded self information symbol x
Wherein the content of the first and second substances,
and is
Then, in order to minimize the base station transmit power, an optimization problem is established by jointly optimizing the base station side transmit (active) beamforming
And an intelligent surface end phase shift matrix (passive beamforming) phi, minimizing the base station transmission power.
The first constraint is the main receiver signal-to-interference-and-noise ratio requirement, the second constraint is to ensure that the IoT receiver can successfully demodulate the main signal, the third constraint is the IoT receiver signal-to-noise ratio requirement, and the fourth constraint is the phase shift constraint of the intelligent surface.
Since the base station side transmit beamforming W and the smart surface side phase shift matrix Φ are coupled together in the first, second and third constraints, and the numerator and denominator in the first and second constraints both contain optimization variables, the problem (P1) is a non-convex optimization problem. The efficient surface-optimized emission matrix can be obtained by iterative Optimization of the surface-optimized Man-Cho, yin-yang, sh-oh, and "surface-optimized" emission matrix, and by using the "adaptive Optimization" technique "Stephen bed and Liven Vandeberghe, Convex Optimization, Cambridge Unit v.Press, 2004" ", Quadratic transformation (Quadratic transformation) method" kaimng bed and Wei Yu, "sectional planning for communication system-part I: Power control and beamforming". IEEE Trans.Signal Processing, vol.66, No.10, pp.2616-2630, May,2018. ", Semi-positive Relaxation (Semi-defined Relaxation) method" Zhou-query Luo, Wing-Kin Ma, analysis Man-Cho, yin, Shuzo and "reflection" Optimization "method" Zhi-Quan Luo, Wing-Kin Ma, analysis Man-Cho, Yinyu Yonye, exchanging phi, "and" reflection "surface-Optimization method" 3. P.853. the above-adaptive Optimization method "surface-mapping".
In order to illustrate the superiority of the scheme in power performance, another two schemes are introduced as comparison references, one scheme is traditional multicast transmission without intelligent surface assistance, the other scheme is intelligent surface-assisted multicast transmission (the intelligent surface does not send information and does not support transmission of the internet of things, namely symbiotic communication is not realized), and the base station transmitting power is minimized by jointly optimizing the base station end transmitting beam forming W and the intelligent surface end phase shift matrix phi.
The beneficial effects of the present invention are verified by simulation below. The simulation parameters are set as followsThe number of station antennas and IoT receiver antennas is 4 and the symbol period multiple is 60. The channels from the base station to the intelligent surface, from the intelligent surface to all the main receivers and from the intelligent surface to the IoT receiver are modeled into Rice channels, the Rice factor is 10, and the large-scale path loss is respectively set to be 10-3d-2、10-3d-2.8、10-3d-2.8(d is link distance in meters); the channels from the base station to all the main receivers and from the base station to the IoT receiver are modeled as Rayleigh channels, and the large-scale path loss is set to be 10-3d-4(ii) a The power of additive white gaussian noise is-114 dBm. Specifically, the position and distance relationship of each device can be seen from the three-dimensional coordinate system in fig. 2, the coordinates of the base station are (0, 0, 10), and the coordinates of the smart surface are (b), (c), (d), and (d)
10) IoT receiver coordinates of (
30, 10) are received, all primary receivers are randomly distributed in a circle with a (60, 60, 1.5) as the center and a radius of 10.
Fig. 3 shows the relationship between the base station transmit power and the primary receiver signal-to-noise ratio and the number of quantization bits. The number of the intelligent surface reflection units is set to be 64, and the minimum signal-to-noise ratio requirement of the IoT receiver is 8 dB. First, it is observed that as the signal to interference and noise ratio requirement of the primary receiver increases, the base station transmit power also increases. Compared with the traditional multicast transmission scheme without intelligent surface assistance, the multi-antenna multicast transmission scheme of the symbiotic communication system based on the intelligent surface saves more base station transmitting power, and the performance gap of the two schemes is increased along with the increase of the signal-to-interference-and-noise ratio requirement of the main receiver, which shows that when the signal-to-interference-and-noise ratio requirement of the main receiver is smaller, the scheme provided by the invention needs to consume more power to meet the transmission requirement of the internet of things, however, when the signal-to-interference-and-noise ratio requirement of the main receiver is larger, the scheme provided by the invention mainly meets the main transmission requirement, and the transmission requirement of the internet of things is easy to meet. In addition, compared to the smart surface assisted multicast transmission scheme, i.e. no symbiotic communication is implemented, the proposed scheme has a slight performance penalty, since additional power is required to support the networked transmission. In practical applications, the smart surface cannot adjust the continuous phase value, so the continuous phase value is usually quantized to a specific range according to a fixed quantization bit number B considering the case of discrete phase shift. It can be seen from fig. 3 that the discrete phase shift case has some performance loss, but the performance loss becomes further smaller as the number of quantization bits increases. Specifically, when the quantization bit numbers are 1, 2, and 3, respectively, the transmission power of the base station is increased by 7.1%, 2.6%, and 0.9% on average, compared with the continuous phase shift case proposed by the present invention.
Fig. 4 shows the variation of the base station transmission power with the number of intelligent surface reflection units and the signal-to-noise ratio of the IoT receiver when the constraint value of the signal-to-interference-and-noise ratio of the main receiver is 20 dB. First, it can be seen that as the number of the reflection units of the smart surface increases, the base station transmission power required by the schemes based on the smart surface (i.e. the multicast transmission scheme assisted by the smart surface and the multi-antenna multicast transmission scheme of the symbiotic communication system based on the smart surface proposed by the present invention) decreases, while the base station transmission power required by the conventional multicast transmission scheme without the smart surface assistance remains unchanged at a larger value, which indicates that increasing the number of the reflection units brings about a significant performance improvement. In addition, when the signal-to-noise ratio requirement of the IoT receiver is increased from 2dB to 10dB, the transmission power of the base station is not significantly increased, because when the signal-to-noise ratio requirement of the main receiver is large, the scheme provided by the invention mainly meets the main transmission requirement, and the transmission requirement of the internet of things can be easily met. In this case, the smart surface can not only enhance the main transmission but also support the internetworking transmission without adding additional power consumption.
Claims (2)
1. The system consists of a base station configured with M antennas, an IoT receiver configured with Q antennas, an intelligent surface comprising N passive reflection units, an IRS controller connected with the intelligent surface, and K single-antenna main receivers; the multi-antenna multicast transmission method is characterized by comprising the following steps:
the K primary receivers are grouped into G groups,
the primary receivers in the same group request the same information at the same time and each primary receiver can only belong to one group, i.e. primary receivers
G is not equal to i, M is more than or equal to 1, Q is more than or equal to 1, K is more than or equal to 1, and G is more than or equal to 1 and less than or equal to K;
the base station multicasts independent signals to each group of main receivers through active beam forming and enhances the main link communication between the base station and the main receivers by controlling a reflection unit of an intelligent surface; the intelligent surface modulates self information on a multicast signal by using a binary phase shift keying mode and transmits the multicast signal to an IoT receiver; both the primary receiver and the IoT receiver receive two parts of the signal: a direct link signal from a base station and a reflected signal from a smart surface;
the signal received by the kth primary receiver of the g-th group is:
wherein s isg(l) And
respectively representing information symbols and active beam forming vectors sent to a g group of main receivers by a base station, wherein x represents information symbols sent by an intelligent surface and defines that the transmission rate of the Internet of things is far less than the main transmission rate, so that one symbol period of x contains L sg(l) The symbol period of (1), L > 1,
a phase-shift matrix representing the smart surface,
a vector of phase shifts is represented that is,
and
respectively representing the base station to kth primary receiver channel, the smart surface to kth primary receiver channel and the base station to smart surface channel, zk(l) Indicating a power of
Zero-mean additive white gaussian noise;
the signals received by the IoT receiver are:
wherein the content of the first and second substances,
and
respectively representing base station to IoT receiver channels and smart surface to IoT receiver channels,
indicating a power of
Zero mean additive gaussian white noise vector.
2. The intelligent reflective surface based multi-antenna multicast transmission method for symbiotic communication system according to claim 1 wherein the active beamforming vector is
The design method of the phase shift matrix phi of the intelligent surface comprises the following steps:
ensuring main receiver signal-to-interference-and-noise ratio requirements in a primary system
And IoT receiver signal-to-noise ratio requirement in communication of Internet of things
On the premise of (A) under the condition of (B),
aiming at minimizing the transmitting power of the base station, establishing an optimization problem:
the first constraint is the signal-to-interference-and-noise ratio requirement of a main receiver, the second constraint is to ensure that the IoT receiver can successfully demodulate a main signal, the third constraint is the signal-to-noise ratio requirement of the IoT receiver, the fourth constraint is the phase shift constraint of an intelligent surface, and the base station end transmitted beam forming W and the intelligent surface end phase shift matrix phi can be obtained by solving the optimization problem.
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