CN103023592B - Fairness based cognitive radio-frequency spectrum resource management algorithm - Google Patents
Fairness based cognitive radio-frequency spectrum resource management algorithm Download PDFInfo
- Publication number
- CN103023592B CN103023592B CN201310004775.1A CN201310004775A CN103023592B CN 103023592 B CN103023592 B CN 103023592B CN 201310004775 A CN201310004775 A CN 201310004775A CN 103023592 B CN103023592 B CN 103023592B
- Authority
- CN
- China
- Prior art keywords
- channel
- base station
- spectrum resource
- frequency spectrum
- fairness
- 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.)
- Expired - Fee Related
Links
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses a fairness based cognitive radio-frequency spectrum resource management algorithm. The fairness based cognitive radio-frequency spectrum resource management algorithm includes the steps of (1) subjecting underutilized or undistributed spectrum resource to channel division according to different network type; (2) describing parameters of the underutilized or undistributed spectrum resource; (3) introducing three variable parameters a, b and c, increasing the a to increase influence of channel width wt which can be obtained currently, obtaining larger total system revenue and reducing distribution fairness at the same time, and increasing the b and the c to improve the distribution fairness and reduce the total system revenue at the same time, wherein total bandwidth w, the channel width wt of the network type t and the channel quantity Mt of the network type t meet the Formula Mt=floor(w/wt), and the Formula is floor operation.
Description
Technical field
The invention belongs to wireless communication field, specifically a kind of cognitive radio intermediate frequency spectrum Resource Management Algorithm based on fairness.In obtaining optimizer system income, ensure the reliable communication of frequency spectrum resource distributional equity and node.
Background technology
Radio spectrum resources is fixed division by radio spectrum management department always, gives certain business, certain wireless traffic operator (or group, department etc.) by certain frequency range fixed allocation.Frequency range after division can only be used by the user under this operator, and other unauthorized users can not use this frequency range, even the in the situation that of the authorized user free time.But, more and more studies have shown that this method of salary distribution is that utilance is low-down, and can not meet the growing demand to radio spectrum resources of user.
Based on this, JosephMitola in 1999 have proposed the concept of cognitive radio (CR, Cognitive Radio).Although CR is assigned with some, untapped frequency spectrum and some are used but the frequency spectrum that is not fully utilized is looked for out, and again distribute and use, thereby reach higher spectrum utilization efficiency, alleviated to a certain extent the contradiction of current frequency spectrum anxiety and business development.Be accompanied by the rise of cognitive radio technology, Dynamic Spectrum Management problem is rich in challenging problem as one in cognitive radio and is also more and more paid close attention to by more people.
Dynamic Spectrum Management is in all feasible channel allocation, to select optimum channel allocation set U*, reaches the optimization of target function with this.In more than ten years in the past, a lot of researchers have proposed the effective Dynamic Spectrum Management algorithm based on different network environments, different target function.What for example, in the article " Collaboration and fairness in opportunistic spectrum access " of Haitao Zheng and Chunyi Peng, propose has designed three kinds of different algorithms based on three kinds of different target functions.This locality by graph theory for example proposing in the article " List-coloring based channel allocation for open-spectrum wireless networks " of Wei Wangand Xin Liu again problem (LCP, local-coloring problem) of tinting is applied to the algorithm of Dynamic Spectrum Management.But much the research based on graph theory, by introducing the concept of " neighbours ", connects spectrum allocation may problem with neighbours' spectrum allocation may, has simplified between node and has disturbed, and ignored the cumulative interference of non-neighbor user.As at L.Yang, L.Cao, in the article " Physical interference driven dynamic spectrum management " of and H. Zheng, point out, when multiple link, operation can cause enough large cumulative interference, thereby cause bust this, even can not impact transmission when these links move alone.Thereby a kind of system framework PLAN(physical conflict graph generator proposed in this section of article), this framework improves the allocation performance of algorithm by considering the suffered cumulative interference of node.Subsequently, at SooyeolIm, Yunseok Kang, Wonsop Kim, Seunghee Kim, in the article " Dynamic spectrum allocation with efficient SINR-based interference management " of Jinup Kim and HyuckjaeLee, propose the heterogeneous network based on center type, proposed a kind of effective spectrum management algorithm, but this algorithm has been ignored distributional equity problem.
Based on the heterogeneous network of center type, this paper combines equitable proportion algorithm (PF, proportional fairness) and physical disturbance model, has ensured the reliable communication of distributional equity and node in obtaining optimizer system income.
Summary of the invention
The present invention proposes a kind of cognitive radio frequency spectrum Resource Management Algorithm based on fairness that has ensured the reliable communication of distributional equity and node in obtaining optimizer system income.A cognitive radio frequency spectrum Resource Management Algorithm based on fairness, is characterized in that: it comprises the following steps:
The first step: the frequency spectrum resource of underusing or not being assigned with is carried out to channel distribution according to different network type;
Second step: describe the parameter of the frequency spectrum resource of underusing or not being assigned with, the channel quantity of the total bandwidth W of the frequency spectrum resource of wherein underusing or not being assigned with, the channel width Wt of network type t and network type t
wherein
it is rounding operation;
The 3rd step: introduce three variable element a, b, c, increase a and increase current obtainable channel width w
timpact, and obtain larger system total revenue, reduce fairness in distribution simultaneously, increase b and c and improve fairness in distribution, reduce system total revenue simultaneously.
On the basis of technique scheme, described the 3rd step also comprises, each base station is selected an available network model voluntarily, then the channel of map network type is carried out to competitive bidding, and base station 1 is to channel m
t(m
t=1 ..., M
t) carry out competitive bidding, the target function design in its i time circulation is as follows:
Wherein J
i-1until the BTS channel pair that the i-1 time circulation distributed after finishing
b
i-1j
i-1in all base stations,
that base station l is to channel m
tbidding price, w
tthe channel width of network type t, a
n,j(j=1 ..., M
t), (n, j) ∈ J
i-1i-1 the circulation allocation matrix of network type t afterwards, and a
n, jbe defined as:
On the basis of technique scheme, further consider the cumulative interference between base station, as follows based on physical disturbance model optimization:
Constraints design is as follows:
Be constrained in
For all (k, m
k) ∈ J
i'
Wherein J
i'=J
i-1∪ (l, m
t), B
i'to belong to J
i'all base stations, i.e. B
i'=B
i-1∪ l, P
kthe through-put power of base station k, P
nnoise power, d
kthe distance between base station k and its terminal use, d
n,kit is the distance between base station n and any user of base station k; Wherein
represent that the current base station-channel that will distribute is to (l, m
t) be subject to likely disturb summation, simultaneously
be defined as:
When
be 1 and show channel m
nwith channel m
kidentical or overlapping,
be 0 o'clock channel m
nwith channel m
kbetween noiseless mutually.
Can provide service more flexibly with respect to prior art the present invention, we can obtain the allocation result of high fairness, low system benefit, also can obtain the high yield allocation result of relatively high fairness simultaneously, by utilizing physical disturbance model, effectively suppress the cumulative interference between base station, thereby ensured terminal use's reliable communication.
Brief description of the drawings
Fig. 1 the present invention carries out channel distribution according to different network type to CAB frequency spectrum resource;
Fig. 2 network insertion type of the present invention and bidding price;
Fig. 3 system total revenue contrast of the present invention;
Fig. 4 fairness in distribution contrast of the present invention;
Fig. 5 SINR cumulative distribution function contrast of the present invention (SINR thresholding β=5dB);
Fig. 6 SINR cumulative distribution function contrast of the present invention (SINR thresholding β=10dB).
Embodiment
Please refer to Fig. 1 and Fig. 2, a kind of cognitive radio frequency spectrum Resource Management Algorithm based on fairness of the present invention comprises the following steps,
The first step: the frequency spectrum resource of underusing or not being assigned with is carried out to channel distribution according to different network type;
Second step: describe the parameter of the frequency spectrum resource of underusing or not being assigned with, the channel quantity of the total bandwidth W of the frequency spectrum resource of wherein underusing or not being assigned with, the channel width Wt of network type t and network type t
wherein
it is rounding operation;
The 3rd step: introduce three variable element a, b, c, increase a and increase current obtainable channel width w
timpact, and obtain larger system total revenue, reduce fairness in distribution simultaneously, increase b and c and improve fairness in distribution, reduce system total revenue simultaneously.
On the basis of technique scheme, described the 3rd step also comprises, each base station is selected an available network model voluntarily, then the channel of map network type is carried out to competitive bidding, and base station 1 is to channel m
t(m
t=1 ..., M
t) carry out competitive bidding, the target function design in its i time circulation is as follows:
Wherein J
i-1until the BTS channel pair that the i-1 time circulation distributed after finishing
b
i-1j
i-1in all base stations,
that base station l is to channel m
tbidding price, w
tthe channel width of network type t, a
n,j(j=1 ..., M
t), (n, j) ∈ J
i-1i-1 the circulation allocation matrix of network type t afterwards, and a
n, jbe defined as:
On the basis of technique scheme, further consider the cumulative interference between base station, as follows based on physical disturbance model optimization:
Constraints design is as follows:
Be constrained in
For all (k, m
k) ∈ J
i,
Wherein J
i'=J
i-1∪ (l, m
t), B
i'to belong to J
i'all base stations, i.e. B
i'=B
i-1∪ l, P
kthe through-put power of base station k, P
nnoise power, d
kthe distance between base station k and its terminal use, d
n,kit is the distance between base station n and any user of base station k; Wherein
represent that the current base station-channel that will distribute is to (l, m
t) be subject to likely disturb summation, simultaneously
be defined as:
When
be 1 and show channel m
nwith channel m
kidentical or overlapping,
be 0 o'clock channel m
nwith channel m
kbetween noiseless mutually.
Next explanation is introduced about the parameter declaration relating in simulation process of the present invention:
Base station number: N
Square region size: 1000 × 1000units:
The through-put power of each base station: P=100mW
The communication distance of each base station: r=50units,
A path loss factor: mistake! Do not find Reference source.
Noise power: P
n=-100dBm
SINR thresholding: 5dB and 10dB.
Can use CAB resource spectral bandwidth: 100MHZ as base station
Then carry out channel distribution according to the network type in Fig. 2.Each base station is being chosen after the network type that oneself will access, and carries out competitive bidding according to the competitive bidding scope of Fig. 2.
Next introduce the correlated performance index of simulation result:
System total revenue can be expressed as
The cumulative distribution function of the SINR of end user location in management area (CDF, cumulative distribution function) is selected ten terminal uses that are positioned at the communication zone boundaries of base station at random, measures its SINR, and draws cumulative distribution function figure.
Fairness in distribution
Definition fairness criteria is:
F
a=1 mean distribute finish after, all base stations have obtained the frequency spectrum resource of same amount of bandwidth.
Wherein Q
tbe the average bandwidth that base station obtains, and be defined as
R
tafter distribution finishes, the channel multiplexing total degree of network type t, N
tit is the number of base stations of selecting network type t.
Can provide service more flexibly with respect to prior art the present invention, we can obtain the allocation result of high fairness, low system benefit, also can obtain the high yield allocation result of relatively high fairness simultaneously, by utilizing physical disturbance model, effectively suppress the cumulative interference between base station, thereby ensured terminal use's reliable communication.
Claims (2)
1. a method for the cognitive radio frequency spectrum resource management based on fairness, is characterized in that: it comprises the following steps:
The first step: the frequency spectrum resource of underusing or not being assigned with is carried out to channel distribution according to different network type;
Second step: describe the parameter of the frequency spectrum resource of underusing or not being assigned with, the channel quantity of the total bandwidth W of the frequency spectrum resource of wherein underusing or not being assigned with, the channel width Wt of network type t and network type t
wherein
it is rounding operation;
The 3rd step: introduce three variable element a, b, c, increase the impact that a increases current obtainable channel width wt, and the larger system total revenue of acquisition, reduce fairness in distribution simultaneously, increase b and c and improve fairness in distribution, reduce system total revenue simultaneously, described the 3rd step also comprises, each base station is selected an available network model voluntarily, then the channel of map network type is carried out to competitive bidding, and base station 1 is to channel m
t(m
t=1 ..., M
t) carry out competitive bidding, the target function design in its i time circulation is as follows:
Wherein J
i-1until the BTS channel pair that the i-1 time circulation distributed after finishing
b
i-1j
i-1in all base stations,
that base station l is to channel m
tbidding price, w
tthe channel width of network type t, a
n,j(j=1 ..., M
t), (n, j) ∈ J
i-1i-1 the circulation allocation matrix of network type t afterwards, and a
n, jbe defined as:
2. the method for a kind of cognitive radio frequency spectrum resource management based on fairness as claimed in claim 1, is characterized in that: further consider the cumulative interference between base station, as follows based on physical disturbance model optimization:
Constraints design is as follows:
Be constrained in
For all (k, m
k) ∈ J
i'
Wherein J
i'=J
i-1∪ (l, m
t), B
i'to belong to J
i'all base stations, i.e. B
i'=B
i-1∪ l, P
kthe through-put power of base station k, P
nnoise power, d
kthe distance between base station k and its terminal use, d
n,kit is the distance between base station n and any user of base station k; Wherein
represent that the current base station-channel that will distribute is to (l, m
t) be subject to likely disturb summation, simultaneously
be defined as:
When
be 1 and show channel m
nwith channel m
kidentical or overlapping,
be 0 o'clock channel m
nwith channel m
kbetween noiseless mutually.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310004775.1A CN103023592B (en) | 2013-01-07 | 2013-01-07 | Fairness based cognitive radio-frequency spectrum resource management algorithm |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310004775.1A CN103023592B (en) | 2013-01-07 | 2013-01-07 | Fairness based cognitive radio-frequency spectrum resource management algorithm |
Publications (2)
Publication Number | Publication Date |
---|---|
CN103023592A CN103023592A (en) | 2013-04-03 |
CN103023592B true CN103023592B (en) | 2014-11-26 |
Family
ID=47971764
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201310004775.1A Expired - Fee Related CN103023592B (en) | 2013-01-07 | 2013-01-07 | Fairness based cognitive radio-frequency spectrum resource management algorithm |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN103023592B (en) |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101026445B (en) * | 2006-02-21 | 2010-11-03 | 华为技术有限公司 | Wireless regional area network uplink resource distributing method and device using orthogonal frequency division multi access |
CN101626604A (en) * | 2008-07-08 | 2010-01-13 | 电子科技大学 | Fairness-based power and channel joint allocation method for cognitive radio system |
US8553652B2 (en) * | 2009-03-10 | 2013-10-08 | Stmicroelectronics, Inc. | Frame based, on-demand spectrum contention methodology |
-
2013
- 2013-01-07 CN CN201310004775.1A patent/CN103023592B/en not_active Expired - Fee Related
Also Published As
Publication number | Publication date |
---|---|
CN103023592A (en) | 2013-04-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhang et al. | Joint computation offloading and resource allocation optimization in heterogeneous networks with mobile edge computing | |
Zhou et al. | Green cell planning and deployment for small cell networks in smart cities | |
CN106341186B (en) | The method of VLC-WiFi converged network parallel transmission and load balancing | |
CN102665282B (en) | Distribution method of multi-user parallel transmission resource in wireless heterogeneous network | |
CN107466099A (en) | A kind of interference management self-organization method based on non-orthogonal multiple access | |
CN105916198B (en) | Resource allocation and Poewr control method based on efficiency justice in a kind of heterogeneous network | |
CN103281786B (en) | The method for optimizing resources of a kind of Home eNodeB double-layer network based on energy efficiency | |
CN105898851A (en) | High energy efficiency power control method which takes energy harvest into consideration in ultra-dense network | |
CN103269487A (en) | Femtocell network down link dynamic interference management method based on game theory | |
Ghasemi et al. | Channel assignment based on bee algorithms in multi‐hop cognitive radio networks | |
CN102448070B (en) | Frequency-power united allocation method based on multi-agent reinforcement learning in dynamic frequency spectrum environment | |
CN103402265A (en) | Spectrum allocation method based on fuzzy logic and communication priority | |
Zhang et al. | Spectrum sharing in cognitive radio using game theory--A survey | |
CN104010288A (en) | Optimal power control method based on pricing in cognitive network | |
CN111343721B (en) | D2D distributed resource allocation method for maximizing generalized energy efficiency of system | |
CN103052078B (en) | The pricing method of revenue of primary user is maximized in cognition network | |
CN103023592B (en) | Fairness based cognitive radio-frequency spectrum resource management algorithm | |
Tian et al. | QoS-aware dynamic spectrum access for cognitive radio networks | |
Wei et al. | Dynamic system level frequency spectrum allocation scheme based on cognitive radio technology | |
Wechtaisong et al. | Multi-objective planning and optimization for base station placement in WiMAX network | |
Bu et al. | Dynamic energy-efficient resource allocation in cognitive heterogeneous wireless networks with the smart grid | |
CN102547725B (en) | Based on the network terminal probability access control method of cognitive radio | |
CN108540246A (en) | A kind of resource allocation methods of the secondary IoT equipment of IoT sensor networks based on cognitive radio under imperfect channel | |
Shnaiwer et al. | Cost-efficient secondary users grouping for two-tier cognitive radio networks | |
Zhou et al. | Virtualized resource sharing in cloud radio access networks: An auction approach |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20141126 Termination date: 20220107 |
|
CF01 | Termination of patent right due to non-payment of annual fee |