CN110913413B - Layered multiple access method for environment backscattering network - Google Patents

Layered multiple access method for environment backscattering network Download PDF

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CN110913413B
CN110913413B CN201911292414.5A CN201911292414A CN110913413B CN 110913413 B CN110913413 B CN 110913413B CN 201911292414 A CN201911292414 A CN 201911292414A CN 110913413 B CN110913413 B CN 110913413B
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李兰花
黄晓霞
汪漪
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Shenzhen Institute of Advanced Technology of CAS
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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
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—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 simultaneous transmission
    • H04B7/0615—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 simultaneous transmission of weighted versions of same signal
    • H04B7/0617—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 simultaneous transmission of weighted versions of same signal for beam forming
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    • 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
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Abstract

The invention provides a layered multiple access method for an environmental backscatter network. The method comprises the following steps: the access point constructs a layered multiple access model of a combined beam shaping layer and a non-orthogonal multiple access layer; designing an optimization problem of maximizing minimum group throughput aiming at the layered multiple access model, and obtaining a grouping strategy of the beam shaping layer and optimizing and controlling the reflection power of a backscattering node by solving the optimization problem; the beamforming layer divides signals from a plurality of backscatter nodes into a plurality of groups based on the grouping strategy; the non-orthogonal multiple access layer decodes the signals in each group by using a continuous interference cancellation mechanism. The method of the invention can obtain better grouping and backscattering coefficients, thereby improving the throughput of the whole network and reducing the network delay.

Description

Layered multiple access method for environment backscattering network
Technical Field
The invention relates to the technical field of communication, in particular to a layered multiple access method for an environmental backscatter network.
Background
Internet of things (IoT) has been widely deployed in various applications such as logistics, industrial control, healthcare, smart home or city, and environmental monitoring. Most wireless devices are powered by recharging or battery replacement, which requires a significant amount of manpower and high expenditure. Thus, energy supply and sustainability have been recognized as key issues for further applications of the internet of things. In recent years, backscatter communication has been introduced into power-limited wireless networks as a very promising technology due to extremely low power consumption. Unlike conventional radios that need to communicate on their own generated carrier signal, backscatter devices communicate information by reflecting a radio frequency signal and typically consume only a few microwatts of power. In view of the energy advantages of backscatter communications, it is of great interest to develop wireless networks with backscatter communications capabilities.
However, environmental backscatter communications also present new challenges to utilizing environmental signals as carriers. Because there is no persistent and stable carrier, the transmission of a backscatter communication device is very unstable and depends on the strength of the ambient signal. Many backscatter communication devices may immediately initiate data transmission to catch up with valuable transmission opportunities once a strong ambient signal is present, causing serious collisions and wasted communication resources. And frequent collisions may result in unpredictable delays, and poor energy efficiency and throughput performance. The traditional multiple access modes, such as FDMA (frequency division multiple access), CDMA (code division multiple access) and TDMA (time division multiple access), have the problems of high power consumption, high protocol complexity, strict synchronization requirements between nodes and the like. Therefore, these schemes are not suitable for low cost backscatter communications devices, even with increased power consumption without performance guarantees. Therefore, it is highly desirable to design an efficient multiple access method for environmental backscatter wireless networks.
In the prior art, for an environmental backscatter network, there are technical solutions: access control of multiple groups of signals is achieved using beamforming between groups, while non-orthogonal multiple access (NOMA) using successive interference cancellation mechanisms within each group. Although the prior art scheme considers the maximum and minimum group throughput optimization problem, the maximum and minimum group throughput optimization problem is not solved directly, but solved according to a self-defined grouping criterion and conventional beam forming, so that the expected optimization target cannot be achieved.
Disclosure of Invention
The present invention aims to overcome the above-mentioned drawbacks of the prior art, to design an efficient hierarchical multiple access scheme for an ambient backscatter communication radio network, and to obtain optimal packet and power control by solving a redefined maximum-minimum group throughput optimization problem.
The invention provides a layered multiple access method for an environment backscattering network, wherein an access point constructs a layered multiple access model of a combined beam shaping layer and a non-orthogonal multiple access layer; designing an optimization problem of maximizing minimum group throughput aiming at the layered multiple access model, and obtaining a grouping strategy of the beam shaping layer and optimizing and controlling the reflection power of a backscattering node by solving the optimization problem; the beamforming layer divides signals from a plurality of backscatter nodes into a plurality of groups based on the grouping strategy; the non-orthogonal multiple access layer decodes the signals in each group by using a continuous interference cancellation mechanism.
Compared with the prior art, the invention has the advantages that: a layered multiple access method is designed, the problem of optimizing the throughput of the minimum group to the maximum is provided according to the characteristics of an environment backscattering wireless network, and a branch-and-bound algorithm based on a Reconstruction Linearization Technique (RLT) is provided to solve the optimization problem, so that better grouping and backscattering coefficients (namely power control) are obtained, the throughput of the whole network is improved, and the network delay is reduced.
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The invention is illustrated and described only by way of example and not by way of limitation in the scope of the invention as set forth in the following drawings, in which:
FIG. 1 is a process diagram of a hierarchical multiple access method for an ambient backscatter network according to one embodiment of the invention;
FIG. 2 is a schematic diagram of a layered multiple access system model based on an ambient backscatter wireless network, according to one embodiment of the invention;
fig. 3 is a flow diagram of a hierarchical multiple access method for an ambient backscatter network, according to one embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions, design methods, and advantages of the present invention more apparent, the present invention will be further described in detail by specific embodiments with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
The invention provides a layered multiple access method based on an environment backscattering wireless network. Briefly, referring to fig. 1, the method comprises: step S110, designing a layered multiple access model combining a non-orthogonal multiple access layer and a beam shaping layer at an access point; step S120, controlling a grouping strategy of the beam shaping layer and controlling the reflection power of the backscattering node by designing an optimization problem of maximizing the minimum group throughput, wherein the grouping strategy considers the total throughput of the system and the transmission fairness of each backscattering node, and the reflection power control of the backscattering node reduces the interference when the non-orthogonal multiple access layer is decoded; step S130, solving the proposed optimization problem of maximizing the minimum group throughput by using a branch-and-bound method based on a reconfiguration linearization technology; step S140, the beamforming layer groups the received signals based on the grouping strategy, and the non-orthogonal multiple access layer decodes the signals in each group by using a continuous interference cancellation mechanism.
Specifically, referring to fig. 2, in the layered multiple access model provided in the embodiment of the present invention, N backscatter nodes simultaneously transmit reflected signals to an access point, and then the access point completes decoding of the signals by using the layered access control model, i.e., the beamforming layer and the NOMA layer. The hierarchical multiple access model, the maximum minimum set throughput (or simply maximum minimum set throughput) optimization problem, and the RLT-based branch definition method will be described separately below.
1) Hierarchical multiple access model
In the embodiment of the invention, a layered multiple access model consists of a beam shaping layer and a NOMA layer, wherein the beam shaping layer carries out grouping control on received signals; then, the successive interference cancellation mechanism is adopted to decode each group of signals in sequence at the NOMA layer.
Referring to fig. 2, an ambient backscatter wireless network consists of an access point with L antennas and N single-antenna backscatter nodes. Let alphai、si、biRespectively representing the backscattering coefficient of a backscattering node i, the received ambient radio frequency signal and the transmitted information bit, and the backscattering signal vector is represented as
Figure BDA0002319473790000031
And is
Figure BDA0002319473790000032
The beamforming matrix is represented as
Figure BDA0002319473790000033
The channel response matrix is
Figure BDA0002319473790000034
All nodes influence factor v according to signal strengthi＝hisiIn ascending order, i.e. II v1‖≤‖v2‖≤…‖vn‖。
1a) Relating to the beam forming layer
At the access point, the received signals are divided into C (C ≦ L) groups by the beamforming layer, and a signal vector r [ r ] is output1,r2,…,rc]TExpressed as:
r＝WHX+WN0 (1)
wherein N is0Is the signal noise vector.
When indicating variable gijNode i belongs to jth group when 1 is equal, otherwise node i does not belong to jth group, grouping matrix
Figure BDA0002319473790000041
Wherein
Figure BDA0002319473790000042
The maximum ratio filtering is adopted to carry out wave beam forming on each group of signals, namely
W＝(Hg)H (2)
Substituting the formula (2) into the formula (1) and expanding, the k group signal is:
Figure BDA0002319473790000043
wherein n is0Is additive Gaussian noise and assumes that it is an independent Gaussian random variable with a mean of 0 and a variance of σ2。
1b) About NOMA layer
For the NOMA layer, using a successive interference cancellation mechanism within each group, the signal is obtained as follows:
Figure BDA0002319473790000044
order to
Figure BDA0002319473790000045
And
Figure BDA0002319473790000046
wherein
Figure BDA0002319473790000047
The expected value is expressed, and as can be seen from the above equation (4), the power of the node m is:
Figure BDA0002319473790000048
2) maximum minimum group throughput optimization problem
In order to obtain an optimal packet g and power control, i.e. backscatter coefficient α, at the access point1,α2,…αn]To achieve maximum minimum group throughput, the problem is described as:
Figure BDA0002319473790000049
Figure BDA00023194737900000410
Figure BDA0002319473790000051
Figure BDA0002319473790000052
wherein R iskRepresents the total throughput of the kth group, and the constraint (6b) represents the energy consumption of the node
Figure BDA0002319473790000053
Node-limited energy storage EiThe constraint (6c) ensures that each node only belongs to a certain group.
The total throughput of the kth group is defined as follows:
Figure BDA0002319473790000054
where B denotes a channel bandwidth.
In addition, the backscattering node can simultaneously perform backscattering transmission and energy acquisition by adjusting a backscattering coefficient, and then the acquired energy is removed, and the net energy consumption of the node is as follows:
Pi c＝Pc-η0(1-αi)Pi (8)
wherein, PcRepresenting the total system energy consumption of the node during data transmission, the latter term on the right hand side of the equation is the energy acquired, η0Represents the power conversion efficiency, PiIs the ambient signal power received by node i.
3) RLT-based branch-and-bound method
The nonlinear term g in the optimization problem can be converted by using RLTikαiAnd (3) converting into linear constraint, thereby converting the optimization problem (6) from a mixed integer nonlinear optimization problem into a mixed integer linear optimization problem, and then solving the problem by using a branch-and-bound method.
First, according to the limiting range of the variable 0 ≦ gikAlpha is not less than 1 and not more than 0iThe following constraints are obtained at ≦ 1:
Figure BDA0002319473790000055
then, using the new variable gammaikSubstitution of g in equation (9)ikαiThereby obtaining gammaikThe linear constraint of (c) is:
Figure BDA0002319473790000061
the optimization problem (6) is then transformed using the above transformation into:
Figure BDA0002319473790000062
s.t.
Figure BDA0002319473790000063
Figure BDA0002319473790000064
Figure BDA0002319473790000065
γiklinear constraints (10), (11e)
And finally, solving the above formula by adopting a branch-and-bound method.
To further understand the present invention, the procedure of the hierarchical multiple access method according to the embodiment of the present invention will be described in detail below.
Still referring to fig. 2, in the system model, N backscatter nodes simultaneously transmit reflected signals to the access point, and then the access point completes the decoding of the signals using the layered access control model, i.e., the beamforming layer and the NOMA layer. After passing through the beamforming layer, the signals are divided into C groups, i.e., equations (1), (2), and (3), and then the NOMA layer decodes the signals in each group using the successive interference cancellation mechanism, i.e., equation (4). The successive interference cancellation scheme is to decode the strongest signal to the weakest signal in the group, first decode the strongest signal, while the other signals are considered as interference, then extract the decoded signal from the group of signals, then decode the second strongest signal, and so on to complete the decoding of the entire group of signals.
On the basis of the model of fig. 2, the invention provides a maximum and minimum group throughput optimization problem to realize the maximization of the system throughput and ensure the fairness of node transmission. Next, a process of solving the optimization problem is described, and referring to fig. 3, specific implementation steps are described as follows:
step S310: and the access point acquires the channel response information H and the energy storage state E of each node through the pilot signal as initialization parameters in the optimization problem (11).
Step S320: setting the algorithm precision E and the maximum iteration number MkAnd adding the problem (11) obtained by RLT conversion of the original optimization problem (6) into the problem list Q as an initial problem. The optimization problem (11) is a mixed integer linear optimization problem, let's be a binary variable gijIn [0,1 ]]The inner real number yields the linear relaxation of the problem (11). An objective function value can be obtained as an upper bound UB by solving the optimization problem of linear relaxation, and then a feasible solution of the optimization problem can be obtained by fixing the value of the binary variable (taking 0 or 1), and the objective function value is taken as a lower bound LB at this time. Let the iteration number variable k be 0 and the current lower bound LB ∞.
Step S330: selecting the value UB with the largest objective function from the question list QqSub-problem q of (1), let the upper bound UB of the optimization problem be UBq。
Step S340: the optimal solution under linear relaxation of the known problem q is the maximum g of the node i in the group CikValue of 1, i.e. gik＝max1≤j≤cgijOther g is known from the constraint (11c) as 1ijThe value being 0, i.e.
Figure BDA0002319473790000072
Then at a given g′Solving the problem q to obtain the backscattering parameter alpha′To obtain a feasible solution (g ', alpha') to the problem q and the objective function value LBqIf LB isqLarger than the current LB, and making LB equal to LBq。
Step S350: and updating an iteration time variable k to k +1, and then judging whether the optimization precision and the maximum iteration time are reached.
If the lower bound of the problem satisfies the inequality LB ≧ (1-epsilon UB or the number of iterations reaches k ≧ MkThe loop terminates and outputs the current feasible solution (g ', α'), i.e., the final solution of the algorithm, from which the node groupings and backscatter coefficients are configured (i.e., step S390).
Step S360: if the loop termination condition is not met, the variable g closest to 1 is selectedijDividing the question q into two sub-questions q1(gij0) and q2(gij＝1)。
Step S370: solving problem q1And q is2Solving under linear relaxation and obtaining the upper bound UB of the problemq1And UBq2。
Step S380: judging whether the upper bound of the subproblem is larger than the precision range of the current lower bound, namely whether LB < (1-epsilon) UB is satisfiedq1And LB < (1-e) UBq2If the condition is satisfied, add the sub-problem to Q, while removing the problem Q. Check the upper bound of other questions Q' in Q if LB ≧ 1-epsilon UBq′The problem does not provide a better solution to remove it out of Q. After the update of the list Q, the process returns to step S330.
To further verify the effect of the present invention, simulation experiments can be performed, and the simulation parameters used are shown in table 1. The codes are written in MATLAB according to the implementation steps, the process in the invention can be well realized, so that the final optimization result is obtained, and the statistical measurement of the network performance can verify that the invention is superior to the prior art in the aspects of average signal-to-interference ratio, total throughput, average time delay and the like.
Table 1 simulation parameter settings
Figure BDA0002319473790000071
Figure BDA0002319473790000081
In summary, the present invention provides a hierarchical multiple access model for an environmental backscatter wireless network; the method comprises the steps that in order to obtain optimal throughput and guarantee fairness of transmission of each node, the optimal grouping and power control are obtained by solving the redefined maximum and minimum group throughput optimization problem, wherein the power control is realized by optimizing backscattering coefficients of the nodes; further, a branch-and-bound algorithm based on a Reconstruction Linearization Technique (RLT) is proposed for solving the optimization problem.
It should be noted that, although the steps are described in a specific order, the steps are not necessarily performed in the specific order, and in fact, some of the steps may be performed concurrently or even in a changed order as long as the required functions are achieved.
The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may include, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (5)

1. A hierarchical multiple access method for an ambient backscatter network, comprising the steps of:
the access point constructs a layered multiple access model of a combined beam shaping layer and a non-orthogonal multiple access layer;
designing an optimization problem of maximizing minimum group throughput aiming at the layered multiple access model, and obtaining a grouping strategy of the beam shaping layer and optimizing and controlling the reflection power of a backscattering node by solving the optimization problem;
the beamforming layer divides signals from a plurality of backscatter nodes into a plurality of groups based on the grouping strategy;
the non-orthogonal multiple access layer decodes signals in each group by using a continuous interference cancellation mechanism;
wherein the optimization problem that maximizes the minimum group throughput is set as:
Figure FDA0002962243220000011
Figure FDA0002962243220000012
Figure FDA0002962243220000013
Figure FDA0002962243220000014
wherein R iskDenotes the total throughput, P, of the k-th groupi cRepresenting the energy consumption of the backscatter node i, EiRepresenting the energy storage of the backscatter node i, C representing the number of packets, N representing the number of backscatter nodes, gijIs an indicator variable, α, for indicating whether a backscatter node i belongs to the jth packetiRepresenting the backscattering coefficient of the backscattering node i;
wherein the optimization problem that maximizes the minimum group throughput is solved according to the following sub-steps:
converting the optimization problem of maximizing the minimum group throughput into:
Figure FDA0002962243220000015
Figure FDA0002962243220000016
Figure FDA0002962243220000021
Figure FDA0002962243220000022
γikis subject to a linear constraint of
Figure FDA0002962243220000023
Wherein, PcRepresenting the total system energy consumption, η, of the backscatter node during data transmission0Represents the power conversion efficiency, hiIs the channel response, P, of the backscatter node iiIs that the backscatter node i receives the ambient signal power and B denotes the channel bandWidth;
and solving the transformed optimization problem of maximizing the minimum group throughput by adopting a branch-and-bound method to obtain the grouping strategy of the beam shaping layer and the backscattering coefficient of the backscattering node.
2. The hierarchical multiple access method for an ambient backscatter network of claim 1, wherein the employing branch-and-bound to solve the transformed optimization problem that maximizes the minimum set of throughputs comprises the sub-steps of:
adding the converted optimization problem which maximizes the minimum group throughput as an initial problem into a problem list Q;
selecting the value UB with the largest objective function from the question list QqSub-problem q of (1), let the upper bound UB of the optimization problem be UBq；
The optimal solution under linear relaxation of the known problem q is the maximum g of the node i in the group CikThe value is 1, then the problem q is solved under the given g 'to obtain the backscattering parameter alpha', the feasible solution (g ', alpha') of the problem q and the objective function value LB are obtainedqIf LB isqGreater than the current objective function LB, making LB equal to LBq；
Judging whether to terminate the loop according to the optimization precision and the set maximum iteration number, if so, outputting the current feasible solution (g ', alpha'), and configuring the grouping and backscattering coefficients of each backscattering node according to the feasible solution (g ', alpha');
if it is determined not to terminate the loop, the question q is divided into two sub-questions q1And q is2；
Solving problem q1And q is2Solving under linear relaxation and obtaining an upper bound for each subproblem
Figure FDA0002962243220000024
And
Figure FDA0002962243220000025
and judging whether the upper bound of each subproblem is larger than the precision range of the current lower bound, if so, adding the subproblems into Q, simultaneously removing the problem Q, checking the upper bound of other problems Q 'in Q, and if not, removing the problems Q' out so as to further solve the updated Q.
3. The hierarchical multiple access method for an ambient backscatter network of claim 1, wherein the backscatter nodes backscatter transmit and harvest energy by adjusting a backscatter coefficient, and wherein a net energy consumption of the backscatter nodes i is expressed as:
Pi c＝Pc-η0(1-αi)Pi
wherein, PcRepresenting the total system energy consumption, η, of the backscatter node i during data transmission0Representing power conversion efficiency, αiRepresenting the backscattering coefficient, P, of the backscattering node iiIs the ambient signal power received by the backscatter node i.
4. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 3.
5. An electronic device comprising a memory and a processor, on which a computer program is stored which is executable on the processor, characterized in that the steps of the method of any of claims 1 to 3 are implemented when the processor executes the program.
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