CN107592650A - A kind of resource allocation methods of the outdoor high energy efficiency into indoor communication system - Google Patents
A kind of resource allocation methods of the outdoor high energy efficiency into indoor communication system Download PDFInfo
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- CN107592650A CN107592650A CN201610528257.3A CN201610528257A CN107592650A CN 107592650 A CN107592650 A CN 107592650A CN 201610528257 A CN201610528257 A CN 201610528257A CN 107592650 A CN107592650 A CN 107592650A
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Abstract
The present invention implements to be related to outdoor in mobile communication and arrives indoor communications field, based on user side multiple antennas low-power wireless access node (Small Cell) network architecture, devises a kind of resource allocation methods of asymptotic optimization.This method is to maximize system descending energy efficiency as target, and in the case where meeting the multiple constraintss of system, by solving optimization problem, iteration obtains the asymptotic optimization solution of energy efficiency；In each iterative process, based on current energy efficiency more new transmission powers allocation matrix and subcarrier allocation strategy.Next, being improved to obtain second-rate optimization method to the above method, this method can guarantee that the convergence of locally optimal solution under any snr value.Using the present invention, by multiple-input and multiple-output (MIMO) system can be made to obtain great performance boost in terms of energy efficiency, throughput of system and spectrum efficiency in the case where user equipment is single antenna.
Description
Technical field
Present document relates to moving communicating field, and especially, the present invention is to be used to the movement of the 5th generation (5th-Generation) lead to
The method of outdoor a kind of resource allocation to indoor communications in letter system.
Background technology
Nowadays 4G mobile networks have been enter into the quick stage of popularization, at the same time 5G skills are all energetically being studied in countries in the world
Art, fall over each other the standard of this country to push to internationalize, 5G standards also begin to show up prominently gradually.Take the lead in utilizing cognitive radio skill
Art, the frequency range of offer is automatically determined by network, it is a 5G distinguishing feature to realize multi-internet integration.The 5G work in China has also taken
Obtain preliminary achievement.High data rate, energy-efficient and wide coverage are the basic demands of 5G wireless communication systems.Resource point
The high-freedom degree matched somebody with somebody causes extensive multiple-input and multiple-output (MIMO) to become a strong candidate scheme of 5G communication systems.
But state-of-the-art personal device is commonly provided with a small amount of reception antenna, provided which has limited MIMO to personal user device
Spatial multiplex gains.How to solve this contradiction and bring new opportunities and challenges of knowing clearly to 5G network designs and optimization.
It is terrible because in traditional GSM, most mobile data flow is all to use indoors
To the multimedia service such as more preferable communication quality and the voice of high quality, image, video, people start to consider utilizing optical fiber
The small base station of high-speed home is laid, but too high implementation cost causes this scheme not gear to actual circumstances.On the other hand, millimeter wave frequency
Band has huge bandwidth available, and still, millimetre wavelength is shorter, and loss is very big when passing through building wall, which limits
The feasibility of millimeter wave base station.It is a kind of new feasible in order to adapt to the new demand of network Development, new situations, meet that 5G communicates
The outdoor of system QOS demands urgently proposes to home communication network framework.
In order to realize energy-efficient, the high data rate required by 5G communication systems, it is proposed that a kind of more days of user side
Line low-power wireless access node (Small Cell) network architecture.The network architecture is used for assisting orthogonal frequency in 5G mobile communication
Divide the transmission of multiple access (OFDMA).In order to lift the spatial multiplex gains of single-antenna subscriber devices, the Small Cell are equipped with two groups
Antenna, one group uses in authorized frequency bands, works in outdoor base station to the small base station link of indoor family, another group in unauthorized frequency
Used in band, work in the small base station of indoor family to user equipment link.
The content of the invention
Present invention is generally directed to outside 5G rooms to indoor high data rate, energy-efficient communication in resource allocation problem,
Propose a kind of resource allocation methods based on home base station network framework and asymptotic optimization iteration.This method is single-antenna subscriber
Equipment provides multiple parallel data flow, and great performance boost is obtained in terms of system energy efficiency and spectrum efficiency.
In order to solve the above problems, present invention firstly provides a kind of optimization Resource Allocation Formula of high energy efficiency, the party
Case is divided into two parts, and Part I renewal energy efficiency, Part II under conditions of giving instant energy efficiency in the case where updating
Uplink transmission power and subcarrier indicator of distribution.
The method and step of Part I renewal energy efficiency is as follows：
Step 1：Initialize maximum iteration HmaxWith convergence tolerance limit v.
Step 2：Iteration index h=0, initialization energy efficiency η are setEE。
Step 3：For given ηEE, Part II ([0017]) is transferred to, obtains optimal power contribution strategy and subcarrier
Allocation strategy
Step 4：JudgeWhether set up.In formula K ∈ { 1 ..., K } be subcarrier set, i ∈ 1 ...,
I } be user equipment (UE) set, m ∈ { 1 ..., M } be space channel set, PCFor circuit system total power consumption, other are related to
And variable will be explained below.
Step 5:If set up, sexual satisfaction is restrained, returns to optimal energy efficiencyJourney
Sequence terminates.
Step 6：If invalid, according toUpdate ηEE, and make h=h+1.
Step 7：Judge whether iterations reaches maximum Hmax。
Step 8：If reached, terminate program；Step 3 ([0010]) is transferred to if being not reaching to, is carried out next time
The iterative process of energy efficiency.
Part II updates downlink transmitted power and the method and step of subcarrier indicator of distribution is as follows：
Step 1：Initialize maximum iteration LmaxWith convergence tolerance limit Δ.
Step 2：Iteration index l=0 is set, initializes downlink transmitted powerWith subcarrier point
With tactful τk,i(l), l=l+1.
Step 3：For what is givenAnd τk,i(l), willSubstitute into the public affairs obtained by convergence constraints
Formula tries to achieve instant resource allocation policy
Step 4：For what is obtainedAnd τk,i(l), willAnother formula obtained by convergence constraints is substituted into ask
Obtain instant resource allocation policy
Step 5：According to what is obtainedAnd τk,i(l) and correlation formula is updated, and is obtained immediately descending
Subcarrier allocation strategy τk,i'(l)。
JudgeWhether set up.
Step 7:If set up, sexual satisfaction is restrained, is returnedObtain optimal power contribution strategy and
Subcarrier allocation strategy, iterative process terminate, and result is sent to the step 4 of Part I.
Step 8：If invalid, according toRenewal
τk,i(l), and l=l+1 is made.
Step 9：Judge whether iterations reaches maximum Lmax。
Step 10：If reached, iterative process terminates, and returnsObtain optimal power contribution plan
Slightly and subcarrier allocation strategy, and result is sent to the step 4 of Part I；Step 3 is transferred to if being not reaching to, is carried out down
The iterative process of first resource distribution.
In the step 1 of Part I and Part II, maximum iteration and convergence tolerance limit will rationally be set, and maximum changes
It is too small that generation number sets excessive or convergence tolerance limit to set, then program operation is slow；It is on the contrary then be possible to that optimal solution can not be obtained.
In the step 2 of Part I and Part II, ηEE, downlink transmitted powerAlso
Initial value is rationally set, and subcarrier allocation strategy is discrete 0-α matrixes.
In the step 3 of Part II, askCalculation formula：
Wherein,
In formula, x+=max { x, 0 },MBS-to-Small Cell links are represented in m-th of space channel, subcarrier k
On equivalent channels noise ratio (CNR),Small Cell-to-UE links are represented on m-th of space channel, subcarrier k
The equivalent channels noise ratio (CNR) of i-th of user.ρ is that the Lagrange relevant with MBS maximum transmission power constraintss multiplies
Son, βi>=0 is the Lagrange multiplier vector related to the minimum downlink data rate needed for latency sensitive user equipment,
σ is the constant related to the efficiency of power amplifier,For the efficiency of energy collection at Small Cell ends,For MBS-to-
The channel gain of Small Cell links.
In the step 4 of Part II, askCalculation formula：
Wherein,
In formula, λ is the Lagrange multiplier relevant with Small Cell maximum transmission power constraintss, μkFor with difference
The Lagrange multiplier relevant with layer interference constraints vector between Small Cell, σ are related to the efficiency of power amplifier
Constant,For the efficiency of energy collection at UE ends,It is Small Cell-to-UE links in m-th of space channel, subcarrier k
Upper user i channel gain.All Lagrange multipliers are updated with Subgradient Algorithm in each iteration.
The correlation formula of subcarrier allocation strategy is updated in step 5：
τk,i=0others
In formula, α is descending time slot,It is m-th of space channel, subcarrier k
Upper user i Signal to Interference plus Noise Ratio.
From technical method, this method is to maximize system descending energy transfer efficiency (bits/Joule) as mesh
Mark, has considered the limitation of system components maximum transmission power, latency sensitive user minimum data rate demand, transmission link
In interference and noise suppressed, network in same layer interference constraints between different Small Cell and Small Cell with using
The collection of energy of family equipment end, using asymptotic optimization resource allocation alternative manner renewal from outdoor multi-antenna base station (MBS) to
The transimission power of Small Cell links, Small Cell to user equipment transimission power, and subcarrier indicator of distribution.
Small Cell use authorized frequency bands and unlicensed frequency band simultaneously using two groups of antennas, by the sky of the authorized frequency bands performed by base station
Between multiplexing be converted into the channeling of unlicensed frequency band, to allow single-antenna subscriber devices to decode more spatial datas.
Technical scheme is further elaborated below by the drawings and specific embodiments.
Brief description of the drawings
For the elaboration implementation of the invention become apparent from and existing technical scheme, below by technical scheme
The explanation accompanying drawing for illustrating to use in accompanying drawing and description of the prior art does simple introduction, it is clear that, do not paying creativeness
On the premise of work, those of ordinary skill in the art can obtain other accompanying drawings by this accompanying drawing.
Fig. 1 is shown in the embodiment of the present invention comprising multiple antennas Macrocell Base Station and multiple antennas Small
Cell system architecture diagram；
Fig. 2 show the flow chart of system power and subcarrier distribution alternative manner in the embodiment of the present invention；
Embodiment
Main idea is that by being modeled to communication system, establish and optimize principal function and constraints,
And maximum iteration is initialized, tolerance limit, iteration index, downlink transmitted power and subcarrier allocation strategy are restrained, is passed through
The asymptotic optimality resource allocation alternative manner of it is proposed seeks optimal transmission power allocation matrix and subcarrier allocation strategy, to obtain
The globally optimal solution for the system of obtaining, i.e. maximum power efficiency.However, it is proposed optimal method be only applicable to the very big feelings of signal to noise ratio
Condition, optimal solution may be unable to reach when signal to noise ratio is limited.
Next, we illustrating second-rate optimization method, the general structure of this method is identical with optimal method, simply step
3 and step 4 in transimission power more new formula change respectively it is as follows：
The more new formula of subcarrier allocation strategy is constant, remains as the formula used in step 5, this method is in any noise
The convergence of locally optimal solution is can guarantee that under ratio, thus it is more practical.As long as rationally setting maximum iteration, convergence is held
The initial value of limit, iteration index, downlink transmitted power and subcarrier allocation strategy, the method proposed can ensure to receive
Reach the optimal solution of energy efficiency in the case of holding back property, any to-noise ratio and high number of subcarriers.
Fig. 1 is shown while the system architecture including Small Cell Yu multiple antennas Macrocell Base Station
Figure, it includes multiple antennas Macrocell Base Station, multiple multiple antennas Small Cell and its user equipment.
Fig. 2 is proposed resource allocation alternative manner flow chart, and flow is as follows：
Step 101：Initialize maximum iteration HmaxWith convergence tolerance limit v.
Step 102：Iteration index h=0, initialization energy efficiency η are setEE。
Step 103：For given ηEE, it is transferred to step 109.
Step 104：JudgeWhether set up.If into
It is vertical, sexual satisfaction is restrained, is transferred to step 105；If invalid, step 106 is transferred to.
Step 105:Return to optimal energy efficiencyPart I iterative process terminates,
It is transferred to step 108.
Step 106：According toUpdate ηEE, and make h=h+1.
Step 107：Judge whether iterations reaches maximum HmaxIf reached, step 108 is transferred to；If do not reach
Arrive, be transferred to step 103, carry out the iterative process of energy efficiency next time.
Step 108：Terminate program.
Step 109：Initialize maximum iteration LmaxWith convergence tolerance limit Δ.
Step 110：Iteration index l=0 is set, initializes downlink transmitted powerAnd subcarrier
Allocation strategy τk,i(l), l=l+1.
Step 111：For what is givenAnd τk,i(l), willSubstitute into what is obtained by convergence constraints
Formula tries to achieve instant resource allocation policy
Step 112：For what is obtainedAnd τk,i(l), willSubstitute into another formula obtained by convergence constraints
Try to achieve instant resource allocation policy
Step 113：According to what is obtainedAnd τk,i(l) and correlation formula is updated, and is obtained i.e. at present
Row subcarrier allocation strategy τk,i'(l)。
Step 114：Judge
Whether set up.If set up, receive
Sexual satisfaction is held back, is transferred to step 115；If invalid, step 116 is transferred to.
Step 115：ReturnOptimal power contribution strategy and subcarrier allocation strategy are obtained, is transferred to
104。
Step 116：According toRenewalτk,i(l), and
Make l=l+1.
Step 117：Judge whether iterations reaches maximum Lmax, step 111 is transferred to if being not reaching to, is carried out
The iterative process of resource allocation next time；If reached, step 115 is transferred to.
Claims (5)
1. a kind of resource allocation methods of the outdoor high energy efficiency into indoor communication system, are divided into two parts, it is characterised in that bag
Containing following steps：
Part I：
Step 1：Initialize maximum iteration HmaxWith convergence tolerance limit ν.
Step 2：Iteration index h=0, initialization energy efficiency η are setEE。
Step 3：For given ηEE, Part II is transferred to, and obtain optimal power contribution strategy and subcarrier allocation strategy
Step 4：JudgeWhether set up.
In formulaFor system overall channel capacity,For total system power consumption.
Step 5:If set up, sexual satisfaction is restrained, returns to optimal energy efficiencyProgram determination.
Step 6：If invalid, according toUpdate ηEE, and make h=h+1.
Step 7：Judge whether iterations reaches maximum Hmax。
Step 8：If reached, terminate program；Be transferred to step 3 if being not reaching to, carry out energy efficiency next time repeatedly
For process.
Part II：
Step 1：Initialize maximum iteration LmaxWith convergence tolerance limit Δ.
Step 2：Iteration index l=0 is set, initializes downlink transmitted powerPlan is distributed with subcarrier
Slightly τk,i(l), l=l+1.
Step 3：For what is givenAnd τk,i(l), willThe formula obtained by convergence constraints is substituted into ask
Obtain instant resource allocation policy
Step 4：For what is obtainedAnd τk,i(l), willAnother formula obtained by convergence constraints is substituted into try to achieve i.e.
When resource allocation policy
Step 5：According to what is obtainedAnd τk,i(l) and correlation formula is updated, and obtains instant downlink sub-carrier
Allocation strategy τk,i'(l)。
Step 6：JudgeWhether set up.
Step 7:If set up, sexual satisfaction is restrained, is returnedObtain optimal power contribution strategy and son carries
Ripple allocation strategy, and result is sent to the step 4 of Part I.
Step 8：If invalid, according toRenewal τk,i
(l), and l=l+1 is made.
Step 9：Judge whether iterations reaches maximum Lmax。
Step 10：If reached, iterative process terminates, and returnsObtain optimal power contribution strategy and
Subcarrier allocation strategy, and result is sent to the step 4 of Part I；Step 3 is transferred to if being not reaching to, is carried out next time
The iterative process of resource allocation.
2. the outdoor alternative manner for arriving indoor communication system high energy efficiency resource allocation according to claim 1, its feature exist
In：
System model has considered the maximum transmission power limitation of macro base station (MBS) and Small Cell, latency sensitive user
Spread at random in interference and noise suppressed, network in minimum data rate demand, transmission link between Small Cell a little
With layer interference constraints and Small Cell and the collection of energy at user equipment end, to maximize system descending energy transmission effect
Rate (bits/Joule) is target, using asymptotic optimization resource allocation alternative manner renewal from outdoor multi-antenna base station (MBS) to
The transimission power of Small Cell links, Small Cell to user equipment transimission power, and subcarrier indicator of distribution.
Small Cell use authorized frequency bands and unlicensed frequency band simultaneously using two groups of antennas, by the sky of the authorized frequency bands performed by base station
Between multiplexing be converted into the channeling of unlicensed frequency band, to allow single-antenna subscriber devices to decode more spatial datas.
3. the outdoor alternative manner for arriving indoor communication system high energy efficiency resource allocation according to claim 1, its feature exist
In：
In the step 3 of Part II, step 4, if using optimizing resource allocation methods, the public affairs obtained by convergence constraints
Formula refers to：
Wherein
Wherein
In formula, x+=max { x, 0 },MBS-to-Small Cell links are represented on m-th of space channel, subcarrier k
Equivalent channels noise ratio (CNR),Small Cell-to-UE links are represented i-th on m-th of space channel, subcarrier k
The equivalent channels noise ratio (CNR) of individual user.ρ is the Lagrange multiplier relevant with MBS maximum transmission power constraintss, βi
>=0 is related to the minimum downlink data rate needed for latency sensitive user equipment Lagrange multiplier vector, λ be with
The relevant Lagrange multiplier of Small Cell maximum transmission power constraintss, μkFor the same layer between different Small Cell
The relevant Lagrange multiplier vector of interference constraints, σ is the constant related to the efficiency of power amplifier,For Small Cell
The efficiency of energy collection at end,For the channel gain of MBS-to-Small Cell links,Imitated for the collection of energy at UE ends
Rate,For Small Cell-to-UE links user i on m-th of space channel, subcarrier k channel gain.
4. the outdoor alternative manner for arriving indoor communication system high energy efficiency resource allocation according to claim 1, its feature exist
In：
In the step 3 of Part II, step 4, if using suboptimization resource allocation methods, the public affairs obtained by convergence constraints
Formula refers to：
In formula, each variable meaning is same as above.
5. the outdoor alternative manner for arriving indoor communication system high energy efficiency resource allocation according to claim 1, its feature exist
In：
In the step 4 of Part I,Hold for system instant channel
Amount,
For the instant total power consumption of system.Wherein PCFor circuit system total power consumption,It is empty m-th
Between channel, on subcarrier k user i Signal to Interference plus Noise Ratio,WithRespectively Small
Cell and the collection of energy at user equipment end.
Pass through calculatingWhether set up, judge main optimization problem
Convergence, if convergence sexual satisfaction, returns to optimal energy efficiencyProgram determination.If not into
It is vertical, then according toUpdate ηEE, and make iteration index h=h+1.
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| CN109756270A (en) * | 2019-02-26 | 2019-05-14 | 重庆邮电大学 | A kind of indoor visible light communication system downlink disturbance restraining method |
| CN110831036A (en) * | 2019-10-10 | 2020-02-21 | 广西师范大学 | Energy efficiency optimization method and system for multi-user EH distributed base station |
| CN116775303A (en) * | 2023-07-03 | 2023-09-19 | 乘乘智数科技(深圳)有限公司 | Method, device and equipment for distributing system computing resources aiming at multilink concurrency |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108738121A (en) * | 2018-03-07 | 2018-11-02 | 北京科技大学 | A kind of wireless network resource distribution method based on software defined network |
| CN109661034A (en) * | 2018-12-11 | 2019-04-19 | 南京邮电大学 | Day line options and resource allocation methods in a kind of wireless energy supply communication network |
| CN109756270A (en) * | 2019-02-26 | 2019-05-14 | 重庆邮电大学 | A kind of indoor visible light communication system downlink disturbance restraining method |
| CN109756270B (en) * | 2019-02-26 | 2021-11-09 | 重庆邮电大学 | Downlink interference suppression method for indoor visible light communication system |
| CN110831036A (en) * | 2019-10-10 | 2020-02-21 | 广西师范大学 | Energy efficiency optimization method and system for multi-user EH distributed base station |
| CN116775303A (en) * | 2023-07-03 | 2023-09-19 | 乘乘智数科技(深圳)有限公司 | Method, device and equipment for distributing system computing resources aiming at multilink concurrency |
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