CN106330608B - The uplink user Throughput fairness optimization method in number energy integrated communication network - Google Patents

The uplink user Throughput fairness optimization method in number energy integrated communication network Download PDF

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CN106330608B
CN106330608B CN201610728778.3A CN201610728778A CN106330608B CN 106330608 B CN106330608 B CN 106330608B CN 201610728778 A CN201610728778 A CN 201610728778A CN 106330608 B CN106330608 B CN 106330608B
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user
energy
downlink
uplink
power
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CN106330608A (en
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于秦
吕柯思
胡杰
杨鲲
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University of Electronic Science and Technology of China
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/08Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876Network utilisation, e.g. volume of load or congestion level
    • H04L43/0888Throughput
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B17/00Monitoring; Testing
    • H04B17/30Monitoring; Testing of propagation channels
    • H04B17/391Modelling the propagation channel

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Environmental & Geological Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses one kind number can uplink user Throughput fairness optimization method in integrated communication networks, specifically include: establishing the uplink and downlink network model in number energy integrated network;Determine base station transmitting power, noise power and energy transformation ratio;User's downlink business demand is defined, goal expression and its constraint are obtained;Calculate the expression formula for the energy that each user's downlink is gathered in;And then obtain the expression formula of user uplink data amount;The optimization of user uplink Throughput fairness is completed by the upstream and downstream time slot and power splitting factor of combined optimization user, obtains transmission strategy.Method of the invention is modeled by the physics scene to a kind of several energy integrated networks, and according to convex optimum theory to model solution, it solves in number energy integrated network, user's communication energy derives from the radiofrequency signal that base station is sent, and in the case that user has downlink data amount demand, the problem of strict guarantee user uplink transmits fairness, maximizes user uplink data amount.

Description

The uplink user Throughput fairness optimization method in number energy integrated communication network
Technical field
The invention belongs to technical field of communication network, and in particular to a kind of uplink user in number energy integrated communication network Throughput fairness optimization method.
Background technique
The energy of existing wireless communication system mostlys come from power grid power supply and battery power supply.Power grid is powered so that system It is sustainable to obtain reliable energy, but deployment electric power networks are required, to keep systematic difference range limited;Battery power so that Systematic difference is more portable, but the storage capacity of monocell is severely restricted the power of system and energy, To constrain the service performance and life cycle of system, and the charge capacity of current battery has become the bottleneck of technology development. Number energy integrated communication technology is on the basis of existing wireless power technology, by the technological means in a variety of forward positions, wireless Information is transmitted while being realized collection of energy (Energy Harvesting, EH), thus realizing the same of high efficient and reliable information communication When make full use of valuable energy resource, provide possibility to solve information and synchronous energy transmission in wireless communication, Become an important directions of future communications development.
Research has been considered that the optimized throughput in number energy integrated communication network transmission, including uplink total throughout The optimization of optimization and upstream data amount fairness, but it is all based on the physical field of time slot switching (Time Swiching, TS) technology Scape is realized the simultaneous interpretation of number energy, is optimized to upstream data amount.Wherein also having research is to divide (Power based on power Splitting, PS) technology realizes the optimization of uplink total throughout, but since number can be double " remote-close " in integration Effect, channel quality is poor or the energy that gathers in apart from base station user farther out's downlink is small, and the power that uplink needs Greatly, therefore user uplink data amount is difficult to be guaranteed.
Summary of the invention
It is an object of the invention to overcome in the prior art to gulp down multi-purpose amount energy integrated communication network transmission optimization The defect that user uplink data amount fairness is not accounted for when the amount of spitting is proposed and a kind of is used under the scene of lower line number energy simultaneous interpretation The transmission strategy that family uplink throughput fairness is optimal.
The purpose of the present invention is achieved through the following technical solutions: a kind of uplink in number energy integrated communication network User throughput fairness optimization method, comprising the following steps:
S1, it determines network model, establishes the uplink and downlink network model in number energy integrated network;
S2, base station transmitting power, noise power and energy transformation ratio are determined;
S3, define user's downlink business demand, obtain about the goal expression of user's downlink business demand and its about Beam;
S4, the expression formula for calculating the energy that each user's downlink is gathered in;
S5, the energy that user's downlink is collected into according to obtained in S4 expression formula obtain the expression of user uplink data amount Formula;
S6, user uplink throughput fairness is completed by the upstream and downstream time slot and power splitting factor of combined optimization user Property optimization, and obtain transmission strategy.
Further, step S1 establishes uplink and downlink network model and specifically includes following sub-step:
S11, the integrated cellular network of number energy based on TDMA for considering single cell, base station and user are single antenna, base The BS that stands sends the integrated signal of number energy with the forms of broadcasting to M user (U by down channel timesharing1,U2,U3,...,UM), it uses Family sends information to base station with then passing through up channel timesharing;The communication of downlink is completed with constant power in base station;If base station with Channel between user remains unchanged in a duty cycle T,WithIt is expressed as the down channel and uplink of user j The channel power of channel declines, if channel is awgn channel, and channel noise power is Pn
S12,Period in, base station is with power PBSIt is communicated in the form of broadcast with user j, at this point, user j By power cutting techniques with splitting factor μjBy downlink reception to signal energy be divided into two parts, a part is used as energy It collects, another part received signal energy is decoded acquisition corresponding information, and other users are then complete by the signal received Portion is acquired as energy.
Beneficial effects of the present invention: method of the invention is counted by the physics scene to a kind of several energy integrated networks Modeling is learned, and according to convex optimum theory to model solution, solved in number energy integrated network, user's communication energy derives from The radiofrequency signal that base station is sent, and in the case that user has downlink data amount demand, strict guarantee user uplink transmits fairness, The problem of maximizing user uplink data amount.
Detailed description of the invention
Fig. 1 is dynamic resource optimal method flow chart of the invention;
Fig. 2 is the network model schematic diagram of number energy integrated communication network of the invention;
Fig. 3 is to carry out the method schematic diagram that power divides energy after user of the invention receives signal;
Fig. 4 is network model time slot allocation figure of the invention.
Specific embodiment
Technical solution of the present invention is further illustrated in the following with reference to the drawings and specific embodiments.
As shown in Figure 1, a kind of dynamic resource optimal method of several energy integrated communication networks, comprising the following steps:
S1, it determines network model, establishes the uplink and downlink network model in number energy integrated network;Concrete model such as Fig. 2 institute Show, including following sub-step:
S11, the integrated cellular network of number energy based on TDMA for considering single cell, base station and user are single antenna, base The BS that stands sends the integrated signal of number energy with the forms of broadcasting to M user (U by down channel timesharing1,U2,U3,...,UM), it uses Family sends information to base station with then passing through up channel timesharing;The communication of downlink is completed with constant power in base station;If base station with Channel between user remains unchanged in a duty cycle T,WithIt is expressed as the down channel and uplink of user j The channel power of channel declines, if channel is awgn channel;
S12,Period in, base station is with power PBSIt is communicated in the form of broadcast with user j.At this point, user j By power cutting techniques with splitting factor μjBy downlink reception to signal energy be divided into two parts, a part is used as energy It collects, another part received signal energy is decoded acquisition corresponding information, and other users are then complete by the signal received Portion is acquired as energy;
S2, base station transmitting power, noise power and energy transformation ratio are determined;Specifically include following sub-step:
S21, base station transmitting power P is determined according to actual hardware and base station ambient environmental conditionsBS
S22, according to actual scene situation, determine user's j upstream and downstream channel noise powerUser's j equipment Energy conversion efficiency is βj
S3, define user's downlink business demand, obtain about the goal expression of user's downlink business demand and its about Beam;Its concrete methods of realizing are as follows: according to the demand of practical application scene, determine the Minimum requirements D of user's j downlink data amountj (bit/Hz);Two parts are partitioned into according to the signal power that power segmentation principle as shown in Figure 3 will receive, wherein for believing Ceasing decoded power isThe data volume expression formula that user's j downlink reception arrives are as follows:
Available downlink data amount constraint are as follows:
Wherein, j=1,2,3...M.
S4, the expression formula for calculating the energy that each user's downlink is gathered in;Here with specific reference to the original of power cutting techniques Reason obtains.
Concrete methods of realizing are as follows: according to the available collected energy of user j of the illustraton of model 2 and Fig. 4 that are proposed in S1 Expression formula are as follows:
S5, the energy that user's downlink is collected into according to obtained in S4 expression formula obtain the expression of user uplink data amount Formula;Specifically include following sub-step: according to the available user j upstream data of network model Fig. 2 and Fig. 4 proposed in S1 Measure expression formula are as follows:
That is,
S6, user uplink throughput fairness is completed by the upstream and downstream time slot and power splitting factor of combined optimization user Property optimization, and obtain transmission strategy;Specifically include following sub-step:
S61, meet downlink business demand consumption while, be expected that by under the uplink for reasonably distributing each user The power splitting factor of row transmission time slot and each user, so that user uplink data amount fairness is optimal, then it is corresponding Mathematical model can be such that
0≤uj≤1
J=1,2 ..., M
S62, the problem are not a convex optimization problem, need to carry out it variable replacement, are enabledThen obtain New optimization problem is as follows:
J=1,2 ..., M
New optimization problem is that the proof of convex problem is as follows:
Objective functionIt is functionPerspective Function it is easy to show that by the basic conception of convex optimum theory (affine function, logarithmic function and min function)It is one Stringent concave function.Since perspective function and original function keep identical convexity, so objective function is a stringent concave function. And remaining constraint condition can prove convexity by seeking Hessian matrix, therefore the problem after variable replacement is one convex asks Topic.
S63, have been proven that Solve problems are a convex optimization problems due to S62, it is possible to right by Lagrange Even method obtains optimal solution.Due to the particularity of Solve problems, if solved to problem direct iteration, complexity is too high, then to S62 The problems in converted to obtain new problem it is as follows:
J=1,2 ..., M
Wherein R is the variable newly introduced.
S64, setting RmaxFor a biggish value, R is setminIt is 0;It takesPass through Lagrange duality Method solves the problems in S63;If optimum results are greater than T, R is takenmax=R, on the contrary take Rmin=R, then be brought into S63 and ask Solution, until Rmax-Rmin< ε (ε is preset error margin), finally obtains optimal solution.
S65, the solving result obtained according to S64 determine transmission strategy.
Method of the invention carries out mathematical modeling by the physics scene to a kind of several energy integrated networks, and according to convex excellent Change theory to model solution, solves in number energy integrated network, the radio frequency letter that user's communication energy is sent from base station Number, and in the case that user has downlink data amount demand, strict guarantee user uplink transmits fairness, maximizes user uplink number The problem of according to amount.
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair Bright principle, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.This field Those of ordinary skill disclosed the technical disclosures can make according to the present invention and various not depart from the other each of essence of the invention The specific variations and combinations of kind, these variations and combinations are still within the scope of the present invention.

Claims (6)

1. a kind of uplink user Throughput fairness optimization method in number energy integrated communication network, comprising the following steps:
S1, it determines network model, establishes the uplink and downlink network model in number energy integrated network;
Specifically include following sub-step:
S11, the integrated cellular network of number energy based on TDMA for considering single cell, base station and user are single antenna, base station BS The integrated signal of number energy is sent to M user (U by down channel timesharing with the forms of broadcasting1,U2,U3,...,UM), user is then Base station is sent information to by up channel timesharing;The communication of downlink is completed with constant power in base station;If base station and user Between channel remained unchanged in a duty cycle T,WithIt is expressed as the down channel and up channel of user j Channel power decline, if channel is awgn channel, and channel noise power is Pn
S12,Period in, base station is with power PBSIt is communicated in the form of broadcast with user j, at this point, user j passes through Power cutting techniques are with splitting factor μjBy downlink reception to signal energy be divided into two parts, a part is received as energy Collection, another part received signal energy is decoded acquisition corresponding information, and other users are then by the signal received whole It is acquired as energy;
S2, base station transmitting power, noise power and energy transformation ratio are determined;
S3, user's downlink business demand is defined, obtained about the goal expression of user's downlink business demand and its constraint;
S4, the expression formula for calculating the energy that each user's downlink is gathered in;
S5, the energy that user's downlink is collected into according to obtained in S4 expression formula obtain the expression formula of user uplink data amount;
S6, to complete user uplink Throughput fairness by the upstream and downstream time slot and power splitting factor of combined optimization user excellent Change, and obtains transmission strategy.
2. the uplink user Throughput fairness optimization method according to claim 1 in number energy integrated communication network, It is characterized in that, step S2 specifically includes following sub-step:
S21, base station transmitting power P is determined according to actual hardware and base station ambient environmental conditionsBS
S22, according to actual scene situation, determine user's j upstream and downstream channel noise powerUser's j plant capacity Transfer efficiency is βj
3. the uplink user Throughput fairness optimization method according to claim 2 in number energy integrated communication network, It is characterized in that, step S3 concrete methods of realizing are as follows: according to the demand of practical application scene, determine user's j downlink data amount Minimum requirements Dj;Divide principle according to power to obtain, the data volume expression formula that user's j downlink reception arrives are as follows:
Available downlink data amount constraint are as follows:
Wherein, j=1,2,3...M.
4. the uplink user Throughput fairness optimization method according to claim 2 in number energy integrated communication network, It is characterized in that, step S4 calculates the expression formula for the energy that each user's downlink is gathered in;With specific reference to power cutting techniques Principle obtains the collected derivation of energy formula of user j are as follows:
5. the uplink user Throughput fairness optimization method according to claim 4 in number energy integrated communication network, It is characterized in that, step S5 obtains user's j upstream data amount expression formula specifically:
That is,
6. the uplink user Throughput fairness optimization method according to claim 5 in number energy integrated communication network, It is characterized in that, step S6 specifically includes following sub-step:
S61, meet downlink business demand consumption while, be expected that by reasonably distribute each user upstream and downstream pass The power splitting factor of defeated time slot and each user, so that user uplink data amount fairness is optimal, then corresponding mathematics Model can be such that
0≤uj≤1
J=1,2 ..., M
S62, variable replacement is carried out to it, enableIt is as follows then to obtain new optimization problem:
J=1,2 ..., M
New optimization problem is that the proof of convex problem is as follows:
Objective functionIt is functionPerspective function,It is a stringent concave function, Since perspective function and original function keep identical convexity to pass through Hessian matrix so objective function is a stringent concave function Orthotropicity prove functionIt is a stringent convex function, and it is remaining Constraint condition is all affine constraint, therefore the problem after variable replacement is a convex problem;
S63, have been proven that Solve problems are a convex optimization problems due to S62, it is possible to pass through Lagrange duality method Optimal solution is obtained, the problems in step S62 is converted to obtain new problem as follows:
J=1,2 ..., M
Wherein, R is the variable newly introduced;
S64, setting RmaxFor a biggish value, R is setminIt is 0;It takesPass through Lagrange duality method pair The problems in S63 is solved;If optimum results are greater than T, R is takenmax=R, on the contrary take Rmin=R, then be brought into S63 and solve, directly To Rmax-Rmin< ε (ε is preset error margin), finally obtains optimal solution;
S65, the solving result obtained according to S64 determine transmission strategy.
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CN110167106B (en) * 2019-05-30 2020-06-26 电子科技大学 Multi-user resource allocation method based on base station selection under fog architecture
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CN111246560B (en) * 2020-03-25 2022-08-12 中国电子科技集团公司第五十四研究所 Wireless energy-carrying communication time slot and power joint optimization method

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