CN105792367A - Network resource allocation method for use under two-layer non-uniform topological structure heterogeneous network - Google Patents

Network resource allocation method for use under two-layer non-uniform topological structure heterogeneous network Download PDF

Info

Publication number
CN105792367A
CN105792367A CN201610102147.0A CN201610102147A CN105792367A CN 105792367 A CN105792367 A CN 105792367A CN 201610102147 A CN201610102147 A CN 201610102147A CN 105792367 A CN105792367 A CN 105792367A
Authority
CN
China
Prior art keywords
user
base station
abs
topological structure
heterogeneous network
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201610102147.0A
Other languages
Chinese (zh)
Other versions
CN105792367B (en
Inventor
刘楠
邹尚璋
潘志文
尤肖虎
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
White Box Shanghai Microelectronics Technology Co ltd
Original Assignee
Southeast University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN201610102147.0A priority Critical patent/CN105792367B/en
Publication of CN105792367A publication Critical patent/CN105792367A/en
Application granted granted Critical
Publication of CN105792367B publication Critical patent/CN105792367B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention provides a network resource allocation method for use under a two-layer non-uniform topological structure heterogeneous network. The network resource allocation method comprises the following steps: 1, constructing a target model as a logarithmic cumulative sum of all user rates, and splitting a problem to be solved of the target model into three sub-problems to be solved in sequence; and 2, solving the three sub-problems in sequence: (1) initializing other parameters, and solving a user connection and frequency resource allocation under a current situation; (2) solving current optimal ABS (Almost Blank Sub-frame) rate configuration after user connection and frequency resource allocation situations are determined; (3) solving emitting power of Macro base stations at an ABS time slot; and (4) setting a termination condition, circularly executing steps I to III, and stopping circulation when the terminal condition is satisfied. Through adoption of the method, a total use rate of a system can be increased, and fairness among users is ensured.

Description

A kind of network resource allocation method under the non-homogeneous topological structure heterogeneous network of two-layer
Technical field
The present invention relates to moving communicating field, especially the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer, the method is in the non-homogeneous topological structure heterogeneous network Access Layer of two-layer, the total throughout of system, the power of completion system and resource distribution is maximized when ensureing user fairness.
Background technology
Nowadays Mobile Communication Development is rapid, and the extensive use of the universal and various real-time media business of mobile intelligent terminal, in broadband wireless network, the traffic increases with exponential rate, and the demand hence for more high coverage rate, faster data rate services is also higher.Owing to frequency spectrum resource is limited, it is improve the availability of frequency spectrum in an efficient way, LTE-Advanced proposes the base station that some are smaller, the general power ratio in this base station is relatively low, and it is arranged in the user density relatively larger hot spot region distance for furthering between user and base station, thus improving user throughput.This in macrocellular network the network architecture of superposition low power nodes be referred to as heterogeneous network (HeterogneousNetworks, HetNets).The application of low power base station brings new opportunity, equally also brings a new difficult problem.The deployment of low power base station can cause minizone overlapping region to increase, owing in order to maximize availability of frequency spectrum employing identical networking mode, region overlaps the interference aggravation meaning minizone.In order to tackle the interference of minizone, interference coordination (enhancedInter-CellInterferenceCoordination between enhancement type district, eICIC) it is a kind of interference coordination technique introduced in LTE-A, distributed by the resource in time domain, coordinate user's interconnection technique, can be diverted on small station by certain customers to improve resource distribution, and improve the channel condition of small station user, thus improving the overall performance of system.Time-domain resource distribution and Macro base station are at some ABS (AlmostBlankSubframe) subframe low power communication, and therefore lower powered base station can use the ABS subframe communication that interference is less, has reached the purpose of interference coordination.
Therefore, at LTE-A as under the main research background of next generation mobile communication system, how coordinates interference power and resource distribution improve overall system throughput, have significantly high researching value and meaning.
Summary of the invention
Goal of the invention: for solving above-mentioned technical problem, the present invention proposes the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer, total user rate that the method can improve system and the fairness that ensure that between user.
Technical scheme: for realizing above-mentioned technique effect, the technical solution used in the present invention is:
A kind of network resource allocation method under the non-homogeneous topological structure heterogeneous network of two-layer, including:
Step 1: to ensure premised on user rate fairness, set up the total speed maximization problems model of system user, target problem is converted to and is split as three subproblems, respectively P1: user connects and frequency spectrum resource distribution, P2: time-domain resource is distributed, and P3:Macro base station is arranged in the transmit power of ABS time slot；
Step 2: successively three subproblems being solved, solution procedure includes:
(1) power at ABS time slot of the Macro base station in non-homogeneous for two-layer topological structure heterogeneous network and ABS ratio are initialized as constant parameter；And obtain under the power and the initialized situation of ABS ratio of ABS time slot, the connection status of user and the distribution of base station frequency domain resource in the non-homogeneous topological structure heterogeneous network of two-layer；
(2) after user connects and base station frequency domain resource distribution condition is determined, ABS ratio arrangement optimum in current network is solved；
(3) when ABS ratio is determined, all Macro base stations transmitting power at ABS time slot is calculated；
(4) circulation performs step (1) to (3), and arranges end condition according to user's request, stops circulation when meeting end condition.
Concrete, the solution procedure of subproblem P1 is included by described step (1):
The Macro base station in non-homogeneous for the two-layer topological structure heterogeneous network power at ABS time slot and ABS ratio are initialized as 0 by 2-1；
Each Macro base station in non-homogeneous for two-layer topological structure heterogeneous network and Pico base station are equivalent to two independent virtual base stations by 2-2 respectively；Definition BABSAnd BnABSRepresent the base station of ABS timeslot scheduling and the base station of non-ABS timeslot scheduling respectively；Define the ratio of total user's number in the user's number and the non-homogeneous topological structure heterogeneous network of two-layer that ABS ratio is the base station connecting ABS timeslot scheduling；The frequency domain resource that in two-layer non-homogeneous topological structure heterogeneous network, each user obtains is allocated as follows:
Wherein, yubRepresent the user u normalization bandwidth obtained when connecting base station b, KbRepresent the total user's number under the b of base station, b ∈ B under current connection strategynABS, BABSRepresenting the base station of non-ABS and ABS timeslot scheduling, β represents ABS ratio；
2-3 set user u connect base station b time obtain transfer rate as:
Rub=yubBlog(1+SINRub)(2)
Wherein, B represents the total bandwidth of the non-homogeneous topological structure heterogeneous network system of two-layer, SINRubRepresent signal to noise ratio during user u connection base station b.
2-4 defined variable xubRepresent user's connectivity problem, work as xubRepresent when=1 that user u connects base station b, work as xubRepresent there is no access base station b when=0；Adopting distributed algorithm to solve user's connectivity problem, algorithm performs at user side and base station end respectively, including step:
1) K is calculatedb, and by KbIt is broadcast to all base stations in two-layer non-homogeneous topological structure heterogeneous network；
2) the transfer rate R returned according to userubAnd Kb, calculate xub:
Above step is repeated, as user link variable set { x at user side and base station endubNo longer change time stop iteration.
Concrete, the solution procedure of subproblem P2 is included by described step (2): after user connects and base station frequency domain resource distribution condition is determined, calculating ABS ratio β is:
Wherein, N represents total number of users of system, and namely ABS ratio represents the ratio of user's number and the total user's number of system connecting ABS base station.
Concrete, the solution procedure of subproblem P3 is included by described step (3): by solve all Macro base stations transmit power at ABS time slot be converted into the logarithm solving the transfer rate that user obtains under the non-homogeneous topological structure heterogeneous network of two-layer and:
Wherein, P represents that required Macro base station is vectorial in the transmit power of ABS time slot, 0 < Pb< PMRepresent the transmit power restriction of Macro base station b, RubIt is the equation about P, uses the gradient descent method in convex optimization that expression formula (4) is solved, obtain the optimum results of subproblem P3.
Concrete, the end condition in described step (4) is set to:
5-1 sets the longest iteration cycle number of times according to channel characteristics, the finishing iteration process when finding iterations more than the threshold value set；Or
5-2 by the front logarithm of user's transfer rate and with current logarithmic and subtract each other and obtain user's transfer rate logarithm and difference, according to user's transfer rate logarithm and difference, threshold interval [l is set1, l2], when user's transfer rate logarithm and difference fall into threshold interval [l1, l2] time, terminate iterative process；l1Represent threshold interval lower limit, l2Represent the threshold interval upper limit.
Beneficial effect: compared with prior art, the invention have the advantages that
1 present invention is based on the two-layer heterogeneous network model of non-uniform Distribution, and allows different Macro base stations to use different transmitting powers at ABS time slot, so can more adapt to base station distribution heterogeneous.
2 present invention adopt combined optimization power and the algorithm of resource distribution, eliminate Macro base station to a certain extent to the interference of user under Pico base station, improve overall system throughput and ensure that the fairness between user.
Accompanying drawing explanation
Fig. 1 is the principle flow chart of one embodiment of the present of invention；
Fig. 2 is the isomerism network structure schematic diagram in the embodiment of the present invention, and * represents eNB, × represent Pico base station, ● represent user.
Fig. 3 is the connection strategy of ZP-ABS connection strategy, LP-ABS connection strategy, no-eICIC connection strategy and present invention proposition user rate CDF figure under identical network layout；
Fig. 4 is base station edge customer speed and user's mean speed comparison diagram under different connection strategy.
Detailed description of the invention
In order to make those skilled in the art be more fully understood that the technical scheme that the present invention proposes, below in conjunction with embodiment, the technical scheme in the present invention is carried out clear, complete description, obviously, described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.
Embodiment: the present embodiment is for the non-homogeneous heterogeneous network of two-layer, this two-layer isomerism network structure schematic diagram is as shown in Figure 2: have 21 Macro base stations in non-homogeneous heterogeneous network, represent by numbering 1 to 21 respectively, wherein being respectively arranged with 5 Pico base station random distributions in 7 Macro base stations, remaining 14 Macro base stations then do not comprise Pico base station.Each base station arranges 10 user's random distributions.Macro base station and Pico base station operation in 2GHz carrier wave and have 10MHz bandwidth, transmit power respectively 46dBm and the 30dBm of Macro base station and Pico base station.In the present embodiment, receive model and only consider that path loss and shadow fading are left out rapid fading.
Introducing Pico base station is the overlapped coverage in order to tap certain customers, present Macro base station and Pico base station for Macro base station, so management calculates the connectivity problem of user, is connect Macro base station or Pico base station.Again since it is desired that alleviate Macro base station to the interference of user under Pico base station, thus Macro base station within a period of time (ABS time slot) with low power communication, and different Macro base stations can adopt different power.Using the ABS ratio of how many ratios is also our one of work.Finally, due to Macro base station at the power of ABS time slot with low power communication, then how many power communication should be adopted then to need to calculate.
Owing to maximizing system user total speed when needing to ensure user rate fairness, so object module is configured to the logarithm cumulative sum of all user rates.Problem to be solved for object module is split as three subproblems solve successively:
First, initialize other parameter, solve the user under present case and connect and frequency resource allocation；Second, after user connects and frequency resource allocation situation is determined, solve currently most ABS ratio arrangement；Finally, each Macro base station transmitting power at ABS time slot is solved.Owing to object function is convex function relative to above variable, circulation three above step eventually converges on an optimum power and resource allocation strategy.
It is illustrated in figure 1 the principle flow chart of embodiment, comprises the following steps:
Step 1: at ABS time slot power, all Macro base stations are initialized as 0, namely represents that Macro does not communicate at ABS time slot.ABS ratio is also initialized as 0 and namely represents and do not adopt interference coordination.
Step 2: user connects and frequency spectrum resource allocation strategy is as follows:
Because there are ABS slotted communication and a non-ABS slotted communication two states in each base station, and each user can only connect a base station, and user or only at ABS time slot or non-ABS slotted communication.So herein each Macro base station and Pico base station being equivalent to two virtual base stations, wherein BABS(BnABS) represent ABS (non-ABS) base station communicated respectively.So the frequency domain resource that user obtains is as follows:
Wherein, yubRepresent the user u normalization bandwidth obtained when connecting base station b, KbRepresent the total user's number under the b of base station, b ∈ B under current connection strategynABS, BABSRepresenting the base station of non-ABS and ABS timeslot scheduling, β represents ABS ratio.Owing to Macro base station becoming two base stations with Pico base station equivalence, and user can only individually at ABS time slot or non-ABS slotted communication.It is R that user u obtains speed when connecting base station bubAs follows:
Rub=yubBlog(1+SINRub)(2)
Wherein, B represents the total bandwidth of base station.SINRubRepresent signal to noise ratio during user u connection base station b, note connecting BABSWhat adopt is the Macro base station transmit power at ABS time slot.
Use variable xubRepresent user's connectivity problem, i.e. xub=1 expression user u connection base station b, and xub=0 expression does not have access base station b.Adopting distributed algorithm to solve user's connectivity problem, algorithm performs at user side and base station end respectively, and all users perform the following step:
1) according to formula (2), transfer rate R when connecting each base station is calculated for all usersub。
All base stations perform the following step:
2) K is calculatedb, and value is broadcast to all base stations.
3) the transfer rate R returned according to userubAnd Kb, calculate x further according to following equationub:
Above step is repeated at user side and base station end, until user link variable set { xubNo longer change stopping iteration.
Step 3: calculating ABS ratio is:
Wherein, N represents total number of users of system, and namely ABS ratio represents the ratio of user's number and the total user's number of system connecting ABS base station.
Step 4: be equivalent to the optimization problem asking expression formula (4) by solving all Macro base stations transmit power at ABS time slot,
Wherein, P represents required vector power, 0 < Pb< PMRepresent the transmit power restriction of Macro base station, RubIt is the equation about P, uses the gradient descent method in convex optimization that expression formula (4) is solved.
Step 5: arrange end condition, repeats step 2 to step 4, until reaching end condition.Namely we need for required power and resource allocation proposal.
Described end condition includes:
1, can according to channel characteristics set the longest iteration cycle number of times, when find the cycle more than set threshold value time finishing iteration process；Or
2, finishing iteration process when network user's logarithm speed and when tending towards stability, the logarithm of the speed namely obtained for user under non-homogeneous topological structure heterogeneous network and arrange constant interval, when the logarithm of user rate with fall into this interval, finishing iteration process.Such as: by a front logarithm of user's transfer rate and with current logarithmic and subtract each other and obtain user's transfer rate logarithm and difference, according to user's transfer rate logarithm and difference, threshold interval [l is set1, l2], when user's transfer rate logarithm and difference fall into threshold interval [l1, l2] time, terminate iterative process；l1Represent threshold interval lower limit, l2Represent the threshold interval upper limit.
Fig. 3 is the connection strategy of ZP-ABS connection strategy, LP-ABS connection strategy, no-eICIC connection strategy and the present embodiment proposition user rate CDF figure under identical network layout；Fig. 4 is base station edge customer speed and user's mean speed comparison diagram under different connection strategy.As seen from the figure, the present invention eliminates Macro base station to a certain extent to the interference of user under Pico base station, improves overall system throughput and ensure that the fairness between user.
The above is only the preferred embodiment of the present invention; it is noted that, for those skilled in the art; under the premise without departing from the principles of the invention, it is also possible to make some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention.

Claims (5)

1. the network resource allocation method under the non-homogeneous topological structure heterogeneous network of two-layer, it is adaptable to two-layer heterogeneous network, it is characterised in that including:
Step 1: to ensure premised on user rate fairness, set up the total speed maximization problems model of system user, target problem is converted to and is split as three subproblems, respectively P1: user connects and frequency spectrum resource distribution, P2: time-domain resource is distributed, and P3:Macro base station is arranged in the transmit power of ABS time slot；
Step 2: successively three subproblems being solved, solution procedure includes:
(1) power at ABS time slot of the Macro base station in non-homogeneous for two-layer topological structure heterogeneous network and ABS ratio are initialized as constant parameter；And obtain under the power and the initialized situation of ABS ratio of ABS time slot, the connection status of user and the distribution of base station frequency domain resource in the non-homogeneous topological structure heterogeneous network of two-layer；
(2) after user connects and base station frequency domain resource distribution condition is determined, ABS ratio arrangement optimum in current network is solved；
(3) when ABS ratio is determined, all Macro base stations transmitting power at ABS time slot is calculated；
(4) circulation performs step (1) to (3), and arranges end condition according to user's request, stops circulation when meeting end condition.
2. the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer according to claim 1, it is characterised in that in described step (1), the solution procedure of subproblem P1 is included:
The Macro base station in non-homogeneous for the two-layer topological structure heterogeneous network power at ABS time slot and ABS ratio are initialized as 0 by 2-1；
Each Macro base station in non-homogeneous for two-layer topological structure heterogeneous network and Pico base station are equivalent to two independent virtual base stations by 2-2 respectively；Definition BABsAnd BnABsRepresent the base station of ABS timeslot scheduling and the base station of non-ABS timeslot scheduling respectively；Define the ratio of total user's number in the user's number and the non-homogeneous topological structure heterogeneous network of two-layer that ABS ratio is the base station connecting ABS timeslot scheduling；The frequency domain resource that in two-layer non-homogeneous topological structure heterogeneous network, each user obtains is allocated as follows:
Wherein, yubRepresent the user u normalization bandwidth obtained when connecting base station b, KbRepresent the total user's number under the b of base station, b ∈ B under current connection strategynABS, BABSRepresenting the base station of non-ABS and ABS timeslot scheduling, β represents ABS ratio；
2-3 set user u connect base station b time obtain transfer rate as:
Rub=yubBlog(1+SINRub)(2)
Wherein, B represents the total bandwidth of the non-homogeneous topological structure heterogeneous network system of two-layer, SINRubRepresent signal to noise ratio during user u connection base station b.
2-4 defined variable xubRepresent user's connectivity problem, work as xubRepresent when=1 that user u connects base station b, work as xubRepresent there is no access base station b when=0；Adopting distributed algorithm to solve user's connectivity problem, algorithm performs at user side and base station end respectively, including step:
1) K is calculatedb, and by KbIt is broadcast to all base stations in two-layer non-homogeneous topological structure heterogeneous network；
2) the transfer rate R returned according to userubAnd Kb, calculate xub:
Above step is repeated, as user link variable set { x at user side and base station endubNo longer change time stop iteration.
3. the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer according to claim 1, it is characterized in that, in described step (2), the solution procedure of subproblem P2 being included: after user connects and base station frequency domain resource distribution condition is determined, calculating ABS ratio β is:
Wherein, N represents total number of users of system, and namely ABS ratio represents the ratio of user's number and the total user's number of system connecting ABS base station.
4. the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer according to claim 1, it is characterized in that, the solution procedure of subproblem P3 is included by described step (3): by solve all Macro base stations transmit power at ABS time slot be converted into the logarithm solving the transfer rate that user under the non-homogeneous topological structure heterogeneous network of two-layer obtains and:
Wherein, P represents that required Macro base station is vectorial in the transmit power of ABS time slot, 0 < Pb< PMRepresent the transmit power restriction of Macro base station b, RubIt is the equation about P, uses the gradient descent method in convex optimization that expression formula (4) is solved, obtain the optimum results of subproblem P3.
5. the network resource allocation method under the non-homogeneous topological structure heterogeneous network of a kind of two-layer according to claim 1, it is characterised in that the end condition in described step (4) is set to:
5-1 sets the longest iteration cycle number of times according to channel characteristics, the finishing iteration process when finding iterations more than the threshold value set；Or
5-2 by the front logarithm of user's transfer rate and with current logarithmic and subtract each other and obtain user's transfer rate logarithm and difference, according to user's transfer rate logarithm and difference, threshold interval [l is set1, l2], when user's transfer rate logarithm and difference fall into threshold interval [l1, l2] time, terminate iterative process；l1Represent threshold interval lower limit, l2Represent the threshold interval upper limit.
CN201610102147.0A 2016-02-24 2016-02-24 Network resource allocation method under two-layer heterogeneous topological structure heterogeneous network Active CN105792367B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610102147.0A CN105792367B (en) 2016-02-24 2016-02-24 Network resource allocation method under two-layer heterogeneous topological structure heterogeneous network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610102147.0A CN105792367B (en) 2016-02-24 2016-02-24 Network resource allocation method under two-layer heterogeneous topological structure heterogeneous network

Publications (2)

Publication Number Publication Date
CN105792367A true CN105792367A (en) 2016-07-20
CN105792367B CN105792367B (en) 2020-06-05

Family

ID=56402754

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610102147.0A Active CN105792367B (en) 2016-02-24 2016-02-24 Network resource allocation method under two-layer heterogeneous topological structure heterogeneous network

Country Status (1)

Country Link
CN (1) CN105792367B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111628912A (en) * 2020-05-28 2020-09-04 深圳华锐金融技术股份有限公司 Resource-related data processing method and device, computer equipment and storage medium

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103188808A (en) * 2013-04-12 2013-07-03 中国科学技术大学 Method for equally distributing resource of heterogeneous wireless network for users
CN104869646A (en) * 2015-05-05 2015-08-26 上海交通大学 Energy-efficient resource allocation method for use in heterogeneous wireless network
CN105188089A (en) * 2015-08-05 2015-12-23 东南大学 Load balancing method based on integral optimization of user connection and interference management in ultra-dense heterogeneous network

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103188808A (en) * 2013-04-12 2013-07-03 中国科学技术大学 Method for equally distributing resource of heterogeneous wireless network for users
CN104869646A (en) * 2015-05-05 2015-08-26 上海交通大学 Energy-efficient resource allocation method for use in heterogeneous wireless network
CN105188089A (en) * 2015-08-05 2015-12-23 东南大学 Load balancing method based on integral optimization of user connection and interference management in ultra-dense heterogeneous network

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
BEATRIZ SORET，KLAUS I. PEDERSEN: "Macro Cell Muting Coordination for Non-Uniform Topologies in LTE-A HetNets", 《IEEE》 *
QIAOYANG YE, BEIYU RONG, YUDONG CHEN, MAZIN AL-SHALASH: "User Association for Load Balancing in Heterogeneous Cellular Networks", 《IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS》 *
WEIJUN TANG, RONGBIN ZHANG, YUAN LIU, AND SUILI FENG: "Joint Resource Allocation for eICIC in Heterogeneous Networks", 《GLOBECOM 2014 - NEXT GENERATION NETWORKING SYMPOSIUM》 *
YU CHEN, XUMING FANG, BO HUANG: "Joint ABS Power and Resource Allocations for eICIC in Heterogeneous Networks", 《PROCEEDINGS OF IWSDA’13》 *
张榕彬: "LTE-A 异构网络下的增强型小区间干扰协调关键技术研究", 《华南理工大学硕士学位论文》 *
黄德华: "LTE-A异构网络中的负载均衡与增强型小区间干扰协调技术研究", 《华南理工大学硕士学位论文》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111628912A (en) * 2020-05-28 2020-09-04 深圳华锐金融技术股份有限公司 Resource-related data processing method and device, computer equipment and storage medium
CN111628912B (en) * 2020-05-28 2021-08-03 深圳华锐金融技术股份有限公司 Resource-related data processing method and device, computer equipment and storage medium

Also Published As

Publication number Publication date
CN105792367B (en) 2020-06-05

Similar Documents

Publication Publication Date Title
Zhang et al. Incomplete CSI based resource optimization in SWIPT enabled heterogeneous networks: A non-cooperative game theoretic approach
Khan et al. Efficient power allocation in downlink multi‐cell multi‐user NOMA networks
Liang et al. A cluster-based energy-efficient resource management scheme for ultra-dense networks
Hasan et al. Distributed resource allocation in 5G cellular networks
Sekander et al. Decoupled uplink-downlink user association in multi-tier full-duplex cellular networks: A two-sided matching game
CN109729528A (en) A kind of D2D resource allocation methods based on the study of multiple agent deeply
CN107426773B (en) Energy efficiency-oriented distributed resource allocation method and device in wireless heterogeneous network
CN107613556B (en) Full-duplex D2D interference management method based on power control
Yang et al. DISCO: Interference-aware distributed cooperation with incentive mechanism for 5G heterogeneous ultra-dense networks
CN104796990A (en) Cellular heterogeneous network D2D resource allocation method based on power control
Yu et al. Dynamic resource allocation in TDD-based heterogeneous cloud radio access networks
Wang et al. User association in non-orthogonal multiple access networks
CN104770004A (en) Communication system and method
Liu et al. Distributed relay selection for heterogeneous UAV communication networks using a many-to-many matching game without substitutability
CN106788812A (en) Interference alignment schemes based on sub-clustering in a kind of two-tier network
CN107241799A (en) The resource allocation of Energy Efficient and interference alignment integrated processes in heterogeneous network
CN103582105A (en) Optimization method for system efficiency maximization in large-scale heterogeneous cellular network
CN105490794A (en) Packet-based resource distribution method for orthogonal frequency division multiple access (OFDMA) femtocell double-layer network
CN107454601A (en) The wireless dummy mapping method of inter-cell interference is considered under a kind of super-intensive environment
Kumar et al. A game theory based hybrid NOMA for efficient resource optimization in cognitive radio networks
Eliodorou et al. User association coalition games with zero-forcing beamforming and NOMA
Feng et al. Energy-efficient joint optimization of channel assignment, power allocation, and relay selection based on hypergraph for uplink mMTC networks
Yuan et al. A cascaded channel-power allocation for D2D underlaid cellular networks using matching theory
Li et al. Resource sharing for cellular-assisted D2D communications with imperfect CSI: a many-to-many strategy
CN111343721A (en) D2D distributed resource allocation method for maximizing generalized energy efficiency of system

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20210330

Address after: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai

Patentee after: Shanghai Hanxin Industrial Development Partnership (L.P.)

Address before: 211189 No. 2 Southeast University Road, Jiangning District, Nanjing, Jiangsu

Patentee before: SOUTHEAST University

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230925

Address after: 201615 room 301-6, building 6, no.1158, Jiuting Central Road, Jiuting Town, Songjiang District, Shanghai

Patentee after: White box (Shanghai) Microelectronics Technology Co.,Ltd.

Address before: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai

Patentee before: Shanghai Hanxin Industrial Development Partnership (L.P.)

TR01 Transfer of patent right