CN101800623A - Throughput-maximized cognitive radio system - Google Patents

Abstract

The invention belongs to the radio communication field, and relates to a throughput-maximized cognitive radio system which aims at enabling secondary users to maximize the radio frequency spectrum not made full use by major users and simultaneously effectively controlling the interference on the major users by the secondary users. The invention uses the collision probability as the measure gauge and control target of the interference on the major users by the secondary users. The system comprises a radio transceiver, a detector, a dispatcher, a transmission controller and a data terminal. By optimally dispatching the secondary-user transmission probability on each transmission sub-time slot in each frequency spectrum idle area, the system maximizes the secondary-user throughput on a single channel and simultaneously limits the collision probability of the major-user data packets within the range of a preset threshold. The system acquires the major-user channel occupying characteristic in a prediction mode, and simultaneously, the performance of the system can be optimized for any secondary-user time slot length.

Description

A kind of throughput-maximized cognitive radio system

Technical field

The invention belongs to wireless communication field, relate to cognitive radio system (CognitiveRadio System) wherein, particularly insert (Opportunistic SpectrumAccess, cognitive radio system OSA) based on chance formula frequency spectrum.

Background technology

In recent years, (Dynamic Spectrum Access, DSA) technology had been subjected to the extensive concern of countries in the world scientific research institutions as a kind of potential emerging wireless communication technology that significantly promotes frequency spectrum resource utilization rate in the dynamic spectrum access.Q.Zhao and B.M.Sadler is seen in the introduction of existing DSA technology and classification, " A survey of dynamic spectrum access, " IEEE Signal ProcessingMagazine, vol.24, no.3, pp.79-89, May 2007.Therein, a kind of opportunistic spectrum that adopts the layer-specific access structure inserts that (Opportunistic Spectrum Access, OSA) technology is emphasized.In the cognitive radio system based on OSA, the owner that main users (Primary User) is defined as certain section authorized frequency bands enjoys the preferential right of freely using this frequency band; Secondary Users (SecondaryUser) can find the frequency spectrum cavity-pocket (Spectrum Hole) on the authorized frequency bands and are used by frequency spectrum perception (Spectrum Sensing).Frequency spectrum perception comprises that specifically energy measuring (EnergyDetector Based Sensing), matched filtering detect (Matched-filtering Detection) or cyclostationary characteristic detects (Cyclostationarity Feature Detection), see T.Yucek and H.Arslan for details, " A survey of spectrum sensing algorithms for cognitive radioapplications, " IEEE Communications Surveys﹠amp; Tutorials, vol.11,2009.Frequency spectrum cavity-pocket is defined in the special time period and the authorized frequency bands that is not used by main users in the specific geographical area.In order to use these frequency spectrum cavity-pockets that dynamically occurs, simultaneously the main users of working is produced limited interference on identical frequency band, Secondary Users need carry out strict interference constraints.For the main users based on packet (Packet-based), Secondary Users are protected main users by restriction main users packet by collision probability.The common cognitive radio system based on OSA is divided into two kinds: multichannel cognitive radio system and single channel cognitive radio system.In these two kinds of cognitive radio systems, Secondary Users adopt the data transfer mode of listem-before-talk (Listen-before-talk) usually, referring to Z.Qing, R.Wei, and A.Swami, " Spectrum Opportunity Detection:HowGood Is Listen-before-Talk?, " in Asilomar Conference on Signals, Systems andComputers.pp.767-771,2007).This data transfer mode is divided into isometric time slot to the time, and a time slot comprises that one is detected sub-slots and a transmission sub-slots.Detecting sub-slots is the beginning part of each time slot, and rest parts is a transmission sub-slots afterwards.Generally speaking, the length of transmission sub-slots is much larger than the length that detects sub-slots, and for example, the length of transmission sub-slots surpasses 50 times that detect sub-slots length, referring to S.Geirhofer, L.Tong, and B.M.Sadler, " Cognitivemedium access:Constraining interference based on experimental models; " IEEEJournal on Selected Areas in Communications, vol.26, pp.95-105,2008.In different classes of cognitive radio system, the multiple throughput-maximized cut-in method of Secondary Users that can make is suggested.

(1) multichannel cognitive radio system.In this system, Secondary Users select the target that reaches throughput-maximized by carry out optimized channel on a plurality of main users channels.The cut-in method that has been suggested is for example observed the optimal detection and the cut-in method of Markovian decision process (POMDP) based on part, see Q.Zhao, L.Tong, A.Swami, and Y.Chen, " Decentralizedcognitive MAC for opportunistic spectrum access in ad hoc networks:APOMDP framework; " IEEE Journal on Selected Areas in Communications, vol.25, no.3, pp.589-600, Apr.2007.This method does not limit Secondary Users' Channel Detection order, constructs POMDP and finds the solution detection, the cut-in method that makes Secondary Users throughput-maximized.Owing to ask the optimal solution amount of calculation excessive,, finally under certain computation complexity restriction, try to achieve suboptimal solution along with the increase of channel quantity is exponential increase.

(2) single channel cognitive radio system.In this system, Secondary Users are operated on the authorization channel, by selecting optimum access way, reach throughput-maximized target.The cut-in method that has been suggested has:

(2.1) optimized detection time method, see Y.Liang, Y.Zeng, E.Peh, and A.Hoang, " Sensing-throughput tradeoff for cognitive radio networks; " IEEETransactions on Wireless Communications, vol.7, no.4, pp.1326-1337, Apr.2008.This method supposition length detection time is fixing, but can find the solution optimized detection time of length by the constitution optimization equation, so that Secondary Users reach maximized throughput.

(2.2) method of optimization transfer of data length, see S.Huang, X.Liu, and Z.Ding, " Optimal Transmission Strategies for Dynamic Spectrum Access in CognitiveRadio Networks, " IEEE Transactions on Mobile Computing, vol.8, no.12, pp.1636-1648, Dec.2009.This method proposes a kind of method of calculating the optimal data transmission length of Secondary Users when channel idle, can make the throughput-maximized of Secondary Users, simultaneously the collision probability of restriction and main users packet.Just can reach optimum but this method only levels off at Secondary Users' slot length zero the time, and not provide the method that Secondary Users obtain main users channel occupancy feature.

Acquisition methods about main users channel occupancy feature, document I.A.Akbar and W.H.Tranter, " Dynamic spectrum allocation in cognitive radio using hidden Markovmodels:Poisson distributed case; " IEEE Southeast Conference, pp.196-201,2007 have proposed based on HMM (Hidden Markov Model, Forecasting Methodology HMM).Related definition and algorithm about HMM, referring to L.R.Rabiner, " A tutorial on hiddenMarkov models and selected application in speech recognition; " Proceedings ofthe IEEE, vol.77, no.2, pp.257-286,1989 and W.Turin, Digital TransmissionSystems:Performance Analysis and Modeling.McGraw-Hill, 1998.

Summary of the invention

The object of the present invention is to provide a kind of throughput-maximized cognitive radio system, this system can make that Secondary Users' is throughput-maximized, can control simultaneously that Secondary Users make within the threshold range that is limited in presetting by collision probability of main users packet the interference of main users in the cognition radio communication process.

A kind of throughput-maximized cognitive radio system provided by the invention, it is characterized in that: this system comprises wireless set, detector, scheduler, transmission control unit (TCU) and data terminal;

Wireless set uses the channel C identical with main users, wireless set adopts the data transfer mode of listem-before-talk, each time slot is divided into detection sub-slots and transmission sub-slots, detecting sub-slots, radio signal on the wireless set receive channel C, and the signal that receives is input to detector, at the transmission sub-slots, wireless set sends packet in the buffering area sending data terminal under the control of transmission control unit (TCU) on channel C;

Detector is used for wireless set is handled in the radio signal that the detection sub-slots receives, judged whether that main users sends data on channel C, the operating state of promptly judging current main users is busy or not busy, and judged result is input to scheduler;

Scheduler calculates the transfer of data probability that each transmission sub-slots wireless set should adopt after the current detection sub-slots according to the judged result of detector output;

Transmission control unit (TCU) determines at random according to the transfer of data probability of current transmission sub-slots whether wireless set sends data terminal at current transmission sub-slots and send packet in the buffering area;

Data terminal becomes packet to be input in the inner transmission buffering area formation data processing to be sent, treats that wireless set takes out packet and transmits at channel C from this formation.

The present invention proposes a kind of single channel cognitive radio system.Than other single channel cognitive radio systems, native system is by optimized scheduling Secondary Users transmission probability on each transmission sub-slots in each frequency spectrum clear area, realized less important user throughput maximization on the single channel, simultaneously within the threshold range that is limited in presetting by collision probability of main users packet.Native system obtains the channel occupancy feature of main users by the mode of prediction; Simultaneously, for Secondary Users' slot length of any setting, systematic function can both reach optimization.The present invention can be applied to radio area network (Wireless Region Area Network, WRAN) in, effectively utilize vacant wireless videocast frequency range (54-842MHz, VHF/UHF), wide application.

Description of drawings

Fig. 1 is the system block diagram of cognitive radio system provided by the invention;

Fig. 2 is based on the multistep system block diagram of the scheduler of Forecasting Methodology forward.

Embodiment

Below by by embodiment the present invention being described in further detail, but following examples only are illustrative, and protection scope of the present invention is not subjected to the restriction of these embodiment.

As shown in Figure 1, system of the present invention comprises wireless set 1, detector 2, scheduler 3, transmission control unit (TCU) 4 and data terminal 5.

Wireless set 1 uses the channel/band identical with main users, is labeled as channel C, can send on channel C and receive radio signals.Wireless set 1 adopts the data transfer mode of listem-before-talk.At the detection sub-slots of a time slot, the radio signal on the wireless set 1 receive channel C, and the signal that receives is input to detector 2.At the transmission sub-slots of a time slot, wireless set 1 is sending the packet that data terminal 5 sends in the buffering area on channel C under the control of transmission control unit (TCU) 4.

2 pairs of wireless sets 1 of detector are handled detecting the radio signal that sub-slots receives, and have judged whether that main users sends data on channel C, judge promptly that the operating state of current main users is " doing " or " spare time ".The state representation of " hurrying " main users sends data on channel C, " spare time " state representation main users does not send data on channel C.Detector 2 is input to scheduler 3 with judged result.The radio signal that detector 2 receives according to wireless set 1 judges that the method for main users operating state is a frequency spectrum perception.

Scheduler 3 calculates the transfer of data probability that each transmission sub-slots wireless set 1 should adopt after the current detection sub-slots according to the testing result of detector 2 outputs.For example, when the transfer of data probability was 0.8, wireless set 1 had 80% probability that the packet that data terminal 5 sends in the buffering areas is transmitted in current transmission sub-slots by channel C.The cardinal principle of institute's foundation is in the calculated data transmission probability process: under the condition that makes within the threshold range that is limited in presetting by collision probability of main users packet, make that Secondary Users' is throughput-maximized.In the present invention, the main users packet be defined in one long enough period by collision probability, for example in one hour, number of times that Secondary Users and main users packet bump and main users send the ratio of packet number; Secondary Users' throughput is defined in one long enough period, for example in one hour, transmission sub-slots number and all time periods that do not taken of channel C that Secondary Users' packet does not bump with the main users packet by main users, the ratio of the transmission sub-slots number that promptly can be used in the clear area.

Transmission control unit (TCU) 4 determines at random according to the transfer of data probability of current transmission sub-slots whether wireless set 1 sends the packet that data terminal 5 sends in the buffering area at current transmission sub-slots.

Data terminal 5 becomes packet to be input in the inner transmission buffering area formation data processing to be sent, treats that wireless set 1 takes out packet and transmits at channel C from this formation.

Figure 2 shows that a kind of (Hidden Markov model, the HMM) scheduler 3 of Forecasting Methodology comprises control module 31, prediction module 32, transmission probability computing module 33 and output module 34 based on HMM.

Scheduler 3 adopts discrete time HMM usually.One has the discrete time HMM of N implicit state and M output symbol is a kind of doubly stochastic process, can use parameter sets λ={ A, B, π } to represent HMM.Wherein, A is N * N state-transition matrix, characterize the hidden layer random process that can not be observed among the HMM, B is N * M output symbol probability matrix, characterize the top layer random process that can produce outside may observe sequence, π is that length is the initial condition probability vector of N, has comprised system and has been in the different probability that imply under the states at initial time.

Control module 31 is adjusted the operating state of scheduler 3 according to the current detection sub-slots main users operating state of detector 2 outputs.Detect the channel status that sub-slots is judged with X (k) expression detector at k, then

K is a positive integer, and expression detects the sequence number of sub-slots, replaces mutually owing to transmit sub-slots and detect sub-slots, and the two quantity equates, so k also represents to transmit the sequence number of sub-slots.

Suppose current k=3000, promptly system is current is in the 3000th and detects sub-slots, and the adjustment criterion of control module 31 is as follows:

If X (3000)=1, control module 31 stores the current detection result, sends signal " NULL " to output module 34, and promptly controlling output module 34 outputs is 0 at the transfer of data probability of current transmission sub-slots, does not promptly send data;

If X (3000)=0, and X (2999)=1 illustrate that current channel C goes up the main users state and changes " spare time " into by " doing ", control module 31 stores the current detection result.If the main users state composition vector Z (3000) of detection sub-slots judgement from initial time 1 to current time k=3000=[X (1), X (2) ..., X (3000)].Control module 31 sends Z (3000) to prediction module 32, simultaneously internal counter value j is changed to 0.Vectorial Q who forms by one group of transfer of data probability of probability calculation module 33 outputs to be transmitted ₃₀₀₀=[Q ₃₀₀₀(0), Q ₃₀₀₀(1) ..., Q ₃₀₀₀And deposit in the output module 34 (S-1)].Q ₃₀₀₀Expression is counted backward S vector that transmits transfer of data probability composition on the sub-slots altogether from the 3000th transmission sub-slots, and S is the multi-step prediction step number, and S is integer and 2≤S≤100.Control module 31 sends signal " j=0 " to output module 34, promptly controls output module 34 and take out transmission probability Q from internal memory ₃₀₀₀(0) also output.

If X (3000)=0, and X (2999)=0, the state that the current channel C of X (2998)=1 explanation goes up main users still is " spare time ", and control module 31 stores the current detection result.The main users state changes " spare time " into by " doing " on the 2999th detection sub-slots channel C as can be known, so there has been Q in the output module ₂₉₉₉Control module 31 internal counter value j send signal " j=1 " from adding 1 to output module 34, promptly control output module 34 output transmission probability Q ₂₉₉₉(1).

Prediction module 32 is based on discrete time HMM.In the present invention, the output symbol of HMM 0, the testing result on the 1} representation signal C, output symbol number M=2.Wherein the operating state of output symbol " 1 " expression main users is " hurrying ", and the operating state of output symbol " 0 " expression main users is " spare time ".Flow process based on the HMM Forecasting Methodology is as follows:

Suppose current k=3000, X (3000)=0, and X (2999)=1, then control module 31 delivery channel state history Z (3000) are to prediction module 32.Prediction module 32 adopts Bao Mu-Wei Erqi algorithm, and (Baum-Welch Algorithm BWA) trains optimum HMM, obtains optimum HMM parameter sets λ.

After having obtained optimum HMM parameter sets λ, adopt forward-backward algorithm (forward-backward procedure) calculating probability U ₃₀₀₀(i) and V ₃₀₀₀(i).Wherein, i is prediction step number sequence number, and multi-step prediction step number S=20 is established in 0≤i≤19.U ₃₀₀₀(i) the expression main users is used the probability of channel C in 3000+i transmission sub-slots; V ₃₀₀₀(i) expression channel C detects sub-slots until 3000+i detection sub-slots all keeps idle probability from the 3000th.U ₃₀₀₀(i) and V ₃₀₀₀(i) computing formula is as follows:

$U_{3000}\left(i\right)=$

$\left\{\begin{array}{c}\frac{\mathrm{Pr}(X(3001+i)=1,Z\left(3000\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(3000\right)\right|\mathrm{\&lambda;})},i=0\\ \frac{\mathrm{Pr}(X\left(3001\right)=0,...,X(3000+i)=0,X(3000+i+1)=1,Z\left(3000\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(3000\right)\right|\mathrm{\&lambda;})},\\ 0<i\&le;19\end{array}\right.$

$V_{3000}\left(i\right)=$

$\left\{\begin{array}{c}\frac{\mathrm{Pr}(X(3001+i)=0,Z\left(3000\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(3000\right)\right|\mathrm{\&lambda;})},i=0\\ \frac{\mathrm{Pr}(X\left(3001\right)=0,...,X(3000+i)=0,X(3000+i+1)=0,Z\left(3000\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(3000\right)\right|\mathrm{\&lambda;})},\\ 0<i\&le;19\end{array}\right.$

Wherein, Pr (|) is illustrated in the conditional probability that certain incident takes place under the specified conditions.After calculating finishes with U ₃₀₀₀(i) and V ₃₀₀₀(i) value is input to transmission probability computing module 33.

Transmission probability computing module 33 calculates the transfer of data probability of following transmission sub-slots.If multi-step prediction step number S=20, for make main users next time packet by collision probability D ₃₀₀₀Within the threshold range that is limited in presetting, establish R=0.2,0≤R≤1 makes Secondary Users transmit sub-slots respectively according to probability Q the 3000th to 3019 ₃₀₀₀(0), Q ₃₀₀₀(1) ..., Q ₃₀₀₀(19) carry out transfer of data, then must satisfy following constraint:

$D_{3000}=\underset{i=0}{\overset{19}{\mathrm{\&Sigma;}}}{U}_{3000}\left(i\right)\&CenterDot;Q_{3000}\left(i\right)\&le;0.2$

If each packet of main users by collision probability all less than thresholding 0.2, then the main users packet by collision probability less than thresholding 0.2.

Secondary Users are at the desired value T of the normalization throughput of current clear area ₃₀₀₀Can be expressed as:

$T_{3000}=\frac{\underset{i=0}{\overset{19}{\mathrm{\&Sigma;}}}{V}_{3000}\left(i\right)\&CenterDot;Q_{3000}\left(i\right)}{\underset{i=0}{\overset{19}{\mathrm{\&Sigma;}}}{V}_{3000}\left(i\right)}$

If the throughput desired value maximization of Secondary Users on each clear area, then Secondary Users' is throughput-maximized.

Linear programming problem is a kind of common optimization problem (referring to A.Schrijver, Theory ofLinear and Integer Programming.John Wiley and Sons, 1998).In order to make T ₃₀₀₀Maximization, the present invention finds the solution Q by the method for linear programming ₃₀₀₀(i).Can list the canonical form of linear programming, as follows:

Max?T ₃₀₀₀

s.t.D ₃₀₀₀≤0.2

0≤Q ₃₀₀₀(i)≤1，i＝0，1，...，19

Can dope based on discrete time HMM:

U ₃₀₀₀(0)～U ₃₀₀₀(19) value is respectively 0.0372,0.0702,0.0657,0.1290,0.1063,0.0913,0.0738,0.0626,0.0533,0.0457,0.0390,0.0333,0.0284,0.0242,0.0206,0.0176,0.0150,0.0128,0.0109,0.0632;

V ₃₀₀₀(0)～V ₃₀₀₀(19) value is respectively 0.9628,0.8926,0.8269,0.6979,0.5916,0.5003,0.4265,0.3639,0.3105,0.2649,0.2259,0.1926,0.1643,0.1401,0.1195,0.1019,0.0869,0.0741,0.0632,0.0539.

By the method for linear programming, can access and make T ₃₀₀₀Maximized one group of Secondary Users' transfer of data probability Q ₃₀₀₀(0)～Q ₃₀₀₀(19) value is respectively 1,1,1,0,0,0,0,0,0.5054,0,0,0,0,0,0,0,0,0,0,0, T ₃₀₀₀Maximum is 0.4022.If the length of this clear area is greater than multi-step prediction step number 20, Q so ₃₀₀₀(19) Secondary Users' transfer of data probability afterwards all is used as 0 processing.

Output module 34 is used for the transmission probability vector Q with 33 outputs of transmission probability computing module ₃₀₀₀Store, and export the transmission probability of current transmission sub-slots under the control of control module 31, situation is as follows:

If control module 31 output signals " NULL ", then the transmission probability of the current transmission sub-slots of output module 34 outputs is 0;

If control module 31 output signals are " j=1 " for example, 0≤j≤S-1, then the transmission probability of the current transmission sub-slots of output module 34 outputs is Q ₃₀₀₀(1);

If control module 31 output signal j＞S-1, then the transmission probability of the current transmission sub-slots of output module 34 outputs is 0.

The present invention not only is confined to above-mentioned embodiment; persons skilled in the art are according to content disclosed by the invention; can adopt other multiple embodiment to implement the present invention; therefore; every employing project organization of the present invention and thinking; do some simple designs that change or change, all fall into the scope of protection of the invention.

Claims (5)

1. throughput-maximized cognitive radio system, it is characterized in that: this system comprises wireless set, detector, scheduler, transmission control unit (TCU) and data terminal;

Wireless set uses the channel C identical with main users, wireless set adopts the data transfer mode of listem-before-talk, each time slot is divided into detection sub-slots and transmission sub-slots, detecting sub-slots, radio signal on the wireless set receive channel C, and the signal that receives is input to detector, at the transmission sub-slots, wireless set sends packet in the buffering area sending data terminal under the control of transmission control unit (TCU) on channel C;

Detector is used for wireless set is handled in the radio signal that the detection sub-slots receives, judged whether that main users sends data on channel C, the operating state of promptly judging current main users is busy or not busy, and judged result is input to scheduler;

Scheduler calculates the transfer of data probability that each transmission sub-slots wireless set should adopt after the current detection sub-slots according to the judged result of detector output;

Transmission control unit (TCU) determines at random according to the transfer of data probability of current transmission sub-slots whether wireless set sends data terminal at current transmission sub-slots and send packet in the buffering area;

Data terminal becomes packet to be input in the inner transmission buffering area formation data processing to be sent, treats that wireless set takes out packet and transmits at channel C from this formation.

2. throughput-maximized cognitive radio system according to claim 1 is characterized in that: scheduler comprises control module, prediction module, transmission probability computing module and output module;

Control module is adjusted the operating state of scheduler according to the current detection sub-slots main users operating state of detector output: if current detection sub-slots upper signal channel C is taken by main users, then scheduler exports that the transfer of data probability is 0 on the current transmission sub-slots; If current detection sub-slots upper signal channel C is not taken by main users, and last detection sub-slots upper signal channel C is taken by main users, then scheduler calculates the transfer of data probability on the transmission sub-slots in one group of future by prediction module and transmission probability computing module, and exports the transfer of data probability on the current transmission sub-slots; If current detection sub-slots upper signal channel C is not taken by main users, and last detection sub-slots upper signal channel C is not also taken by main users, and then scheduler is exported transfer of data probability on the current transmission sub-slots;

Prediction module is based on the discrete time HMM, according to predicting that from the channel status history of control module input main users transmit the probability that uses channel C in the sub-slots in future;

The transmission probability computing module is used to calculate the transfer of data probability of following transmission sub-slots; The transmission probability computing module is an optimization aim with less important user throughput, be constraints within the threshold range that is limited in presetting by collision probability with the main users packet, structure is also found the solution the linear optimization equation, obtain the transfer of data probability of one group of optimum, make Secondary Users throughput-maximized;

Output module is used to store one group of transmission probability of transmission probability computing module output, and exports the transmission probability of current transmission sub-slots under the control of control module.

3. throughput-maximized cognitive radio system according to claim 2 is characterized in that: control module is adjusted the operating state of scheduler according to following rule:

Detect the channel status that sub-slots is judged with X (k) expression detector at k, then

K is a positive integer, and expression detects the sequence number of sub-slots and transmission sub-slots, supposes that current system is in k and detects sub-slots;

If X (k)=1, control module stores the current detection result, sends signal " NULL " to output module, and promptly controlling output module output is 0 at the transfer of data probability of current transmission sub-slots, does not promptly send data;

If X (k)=0, and X (k-1)=1, k＞1 illustrates that current channel C goes up the main users state and changes " spare time " into by " doing ", and control module stores the current detection result; If the main users state composition vector Z (k) of detection sub-slots judgement from initial time 1 to current time k=[X (1), X (2) ..., X (k)]; Control module sends Z (k) to prediction module, simultaneously internal counter value j is changed to 0; Vectorial Q who forms by one group of transfer of data probability of probability calculation module output to be transmitted _k=[Q _k(0), Q _k(1) ..., Q _kAnd deposit in the output module (S-1)]; Q _kExpression is counted backward S vector that transmits transfer of data probability composition on the sub-slots altogether from k transmission sub-slots, and S is the multi-step prediction step number, and S is integer and 2≤S≤100; Control module sends signal " j=0 " to output module, promptly controls output module and take out transmission probability Q from internal memory _k(0) also output;

If X (k)=0, and X (k-1)=0, X (k-2)=1, k＞2 illustrate that the state of the last main users of current channel C still is " spare time ", control module stores the current detection result; The main users state changes " spare time " into by " doing " on k-1 detection sub-slots channel C, so there has been Q in the output module _K-1Control module internal counter value j sends signal " j=1 " from adding 1 to output module, promptly controls output module output transmission probability Q _K-1(1).

4. throughput-maximized cognitive radio system according to claim 3 is characterized in that: prediction module adopts the HMM HMM based on discrete time to predict that its flow process is:

Suppose that current system is in k and detects sub-slots, X (k)=0, and X (k-1)=1, then the historical Z of channel status (k) of control module output is to prediction module; Prediction module adopts Bao Mu-Wei Erqi algorithm, trains optimum HMM, obtains the parameter sets λ of optimum HMM;

If U _k(i) the expression main users is used the probability of channel C in k+i transmission sub-slots; V _k(i) expression channel C detects sub-slots until k+i detection sub-slots all keeps idle probability from k; Adopt forward-backward algorithm calculates U _k(i) and V _k(i):

$U_k\left(i\right)=$

$\left\{\begin{array}{c}\frac{\mathrm{Pr}(X(k+i+1)=1,Z\left(k\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(k\right)\right|\mathrm{\&lambda;})},i=0\\ \frac{\mathrm{Pr}(X(k+1)=0,...,X(k+i)=0,X(k+i+1)=1,Z\left(k\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(k\right)\right|\mathrm{\&lambda;})}\\ 0<i\&le;S-1\end{array}\right.,$

$V_k\left(i\right)=$

$\left\{\begin{array}{c}\frac{\mathrm{Pr}(X(k+i+1)=0,Z\left(k\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(k\right)\right|\mathrm{\&lambda;})},i=0\\ \frac{\mathrm{Pr}(X(k+1)=0,...,X(k+i)=0,X(k+i+1)=0,Z\left(k\right)|\mathrm{\&lambda;})}{\mathrm{Pr}\left(Z\left(k\right)\right|\mathrm{\&lambda;})}\\ 0<i\&le;S-1\end{array}\right.,$

Wherein, i is prediction step number sequence number, and 0≤i≤S-1, S are the multi-step prediction step number.Pr (|) is illustrated under the specified conditions conditional probability of certain incident of generation, calculate finish after with U _k(i) and V _k(i) value is input to the transmission probability computing module.

5. according to the described throughput-maximized cognitive radio system of claim 4, it is characterized in that:

The transmission probability computing module calculates the transfer of data probability that wireless set should adopt in the following manner:

Suppose that current system is in k and detects sub-slots, prediction module is with U _k(i) and V _k(i) value is input to the transmission probability computing module.For make main users next time packet by collision probability D _kWithin the thresholding R scope that is limited in presetting, 0≤R≤1 makes Secondary Users transmit sub-slots respectively according to probability Q at k to k+S-1 _k(0) ..., Q _k(i) ..., Q _k(S-1) carry out transfer of data, 0≤i≤S-1 then needs to satisfy following constraint:

$D_k=\underset{i=0}{\overset{S-1}{\mathrm{\&Sigma;}}}{U}_k\left(i\right)\&CenterDot;Q_k\left(i\right)\&le;R$

Secondary Users are at the desired value T of the normalization throughput of this clear area _kBe expressed as:

$T_k=\frac{\underset{i=0}{\overset{S-1}{\mathrm{\&Sigma;}}}{V}_k\left(i\right)\&CenterDot;Q_k\left(i\right)}{\underset{i=0}{\overset{S-1}{\mathrm{\&Sigma;}}}{V}_k\left(i\right)}$

Make T _kQ is found the solution in maximization _k(i); List the canonical form of linear programming, as follows:

Max?T _k

s.t.D _k≤R

0≤Q _k(i)≤1，i＝0，1，...，S-1

HMM HMM based on discrete time dopes U _k(0)～U _k(S-1) value and V _k(0)～V _k(S-1) value by the method for linear programming, obtains making T _kMaximized one group of Secondary Users' transfer of data probability Q _k(0)～Q _k(S-1) value; If the length of this clear area is greater than multi-step prediction step number S, Q so _k(S-1) Secondary Users' transfer of data probability afterwards all is used as 0 processing.

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