CN106603195B - The adaptive dynamic energy consumption optimization method of enhanced wireless sensor network based on JNCC - Google Patents
The adaptive dynamic energy consumption optimization method of enhanced wireless sensor network based on JNCC Download PDFInfo
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Abstract
The present invention discloses a kind of adaptive dynamic energy consumption optimization method of the enhanced wireless sensor network based on JNCC, it establishes in WSN topology as unit of by cluster, the network code packet number M that the joint decoding bit error rate information that relay node is fed back by destination node D and the mark vector dynamic adjustment epicycle comprising error code codeword position information need to send, so that transmission data are under the premise of meeting bit error rate requirement, system energy consumption is minimum.
Description
Technical field
The present invention relates to and wireless sensor network (Wireless Sensor Networks, WSNs), be specifically related to one
Kind is based on the adaptive dynamic energy consumption of enhanced wireless sensor network of JNCC (Joint Network-Channel Coding)
Optimization method.
Background technique
Present short haul connection such as bluetooth (Bluetooth), ultra wide band (Ultra Wide Band, UWB), ZigBee and
Wi-Fi etc., has come into huge numbers of families, significantly improves people's lives quality.Wireless sensor network is as short distance
Important component from communication, has been obtained and is widely applied, and especially in smart home, field data collection is military
Information gathering etc. has played irreplaceable role.
It is limited to the processing and communication capacity of individual node, the thought of collaboration communication is introduced into WSN, is formd virtual
MIMO technology, basic thought are multiple days that the antenna for the multiple nodes for being located at the same area is regarded as to the same receiving end
Then line can be received using diversity technique, can fight channel fading well.Later researcher's discovery is being transmitted
Middle position processing is carried out to data the performance of system can be improved, here it is the thoughts of network code.With the depth of research
Enter, channel coding and network code two original mutually independent coding techniques have been carried out joint and compiled by the researchers such as C.Hausl
Code decoding forms the thought of combined channel network code, and demonstrates it in terms of transmission reliability by theoretical and emulation
Superior function.Then there is the largely research in terms of combined coding, is concentrated mainly on the code word of combined coding decoding
Optimization, decoding algorithm improvement, adaptive scalability research and energy efficiency etc..Ying etc. utilizes Gaussian approximation algorithm
The decoding threshold of LDPC joint code word is deduced with degree distribution function with Shannon's theorems and distich is compiled in collaboration with code check matrix and carried out
Optimization.Wang etc. proposes the optimization algorithm for combined coding check matrix also based on degree distribution.The scholars such as Hernaez are then
Network code optimum linearity combination coefficient selection algorithm in multi-system combined coding is proposed based on EXIT map analysis.Zheng etc.
Scholar proposes a kind of combined coding decoding scheme NB-JNCC of multi-system and has applied it in multihop network.Xuan etc.
Then theoretically analysis gives a kind of suboptimum joint decoding algorithm to scholar, and decoding performance is effectively promoted.Code set forth above
In the paper of word optimization algorithm and decoding optimization algorithm, there is no the variation for considering network topology, it can be only applied to possess solid
The network of fixed topology, therefore scalability is poor.
In order to solve the problems, such as scalability, X.Bao etc. proposes ANCC and GANCC algorithm, it can be by network topology
The dynamic change of structure is mapped in the check matrix of combined coding, can make adaptive change to the variation of topological structure.
But use all nodes of both algorithms to require to send and receive all data packets, but when channel situation is preferable,
As long as actually a small amount of network code packet ensures that higher reliability, all network code packets are sent to stay of two nights meeting
Waste a large amount of energy.
Although algorithm above shows good performance in terms of improving system transmission reliability, mostly ignore
Most important energy consumption problem in wireless sensor network.Lu et al. proposes JANCC algorithm, which uses mark vector
Marked erroneous code word only requires that relay node sends a network code packet relevant to wrong code word, joint decoding, but it is adjusted
Whole to be limited in scope, adaptivity is poor.Liu et al. people proposes adaptive dynamic energy consumption optimization (ADEC, Adaptive Dynamic
Energy Consumption Optimization) algorithm, it can transmit what situation dynamic adjustment lower whorl was sent according to epicycle
Network code packet number, to guarantee under the premise of reaching transmission requirement, energy consumption is smaller.But the adaptation mechanism of ADEC algorithm
It is according to epicycle decoding result to next round, rather than what the sending strategy of epicycle was adjusted, it will lead to be calculated in this way
Network code packet number may not be optimal.
Summary of the invention
Present invention aim to address the defects of the prior art, provide a kind of enhanced wireless sensor network based on JNCC
The adaptive dynamic energy consumption optimization method of network, the technical solution adopted is as follows:
The adaptive dynamic energy consumption optimization method of enhanced wireless sensor network based on JNCC is established as unit of by cluster
WSN topology on, relay node is by the destination node D joint decoding bit error rate information fed back and comprising error code codeword bit
The network code packet number M that the mark vector dynamic adjustment epicycle of confidence breath needs to send, so that transmission data are meeting accidentally ratio
Under the premise of special rate requires, system energy consumption is minimum, specifically comprises the following steps:
S11. low=0, high=N are initialized0, the region of search that M is arranged is [low, high], is counted using variable j
It sends wheel number and is initialized as 0,0 vector come marked erroneous code word and is initialized as using vector Fg,
S12., M is set as to the median of the region of search, i.e.,Wherein symbolExpression takes downwards
It is whole；
S13. LDPC coding packet and network code packet r are sentj-1, wherein network code packet marks simultaneously with by mark vector Fg
Related in the wrong code word of upper wheel storage, specific generating mode is defined by the formula:
Wherein: c1'~cNe' it is the code word that the upper wheel of mark vector Fg label decodes not successfully, Ne is failed decoding code
The sum of word,It is network code vector；
S14. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Count out bit error rate BER；
S15. destination node D generates mark vector Fg；
S16. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S17. relay node adjusts the node number M of network code according to the bit error rate situation of feedback, specifically: if
BER≤BER of return0, BER0It indicates errored bit threshold value, then reduces M, execute high=M, conversely, then increasing M, execute low=M
+1；
S18. judge whether low is more than or equal to high, if not return step S12, if so then execute end.
Preferably, step S15 generates mark vector by following mark vector generation method:
S21. initialization LDPC encodes packet number i=0；
S22. destination node is iterated decoding to i-th of LDPC coding packet received；
S23. i-th of code word is determined, if cj,iHT==0, then illustrate it is successfully decoded, then by mark vector Fg
I-th of element fi be set as 0；
If S24. cj,iHT≠ 0, then illustrate to decode unsuccessful, store it in buffer, and by the of mark vector Fg
I element fi is set as 1；
S25. judge whether i is more than or equal to N0, return step S22 if not, if then terminating.
Preferably, sending LDPC coding packet and network code packet, institute according to selection strategy is sent in the step S13
It is as follows to state transmission selection strategy:
S31. source cluster node broadcast transmission N0A LDPC coding packet ciTo destination node D and relay node R；
S32. if wheel number j！=1 and mark vector Fg！=0, then relay node R sends M network code packet rj-1To mesh
Node D, otherwise do not send network code packet.
Preferably, the invention also includes be finely adjusted processing, the trim process again to the network code number M of acquisition
Specifically:
S40., M=M is set0, j=j0, wherein M0And j0Respectively coarse tuning stage obtain about the value of M and the value conduct of j
Initial value；
S41. initialization sends the number total=0 of data packet, and initialization error logging number is error=0；
S42. data of every transmission then total=total+1；
S43. it is selected to send LDPC coding packet and network code packet according to sending strategy；
S44. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Count out bit error rate BER；
S45. destination node D generates mark vector Fg by mark vector generation method；
S46. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S47. relay node receives the bit error rate situation of feedback and judges whether to be less than BER0, if so, S48 is executed,
If executing S48 after otherwise executing error=error+BER；
S48. judge whether total is greater than total0, if so, S49 is executed, if otherwise executing S411；
S49. judge whether BER is greater than BER0, if so then execute M=M+1, S41 is returned to, if otherwise executing S410；
S410. judge whether BER is less than BER0/ 2, if so then execute M=M-1, S41 is returned to, if otherwise executing S411；
S411. judge whether data have all sent, if then terminating, if otherwise returning to S42.
Compared with prior art, beneficial effects of the present invention: the present invention can not only be according to the variation dynamic of channel condition
The number of network code packet is adjusted, and uses mark vector to identify decoding error code word, relay node only needs to send
Network code packet relevant to wrong code word can more accurately correct error code, bit error rate be reduced, to reduce network code
Packet number, thus under the premise of reaching bit error rate requirement, so that energy consumption further decreases.
Detailed description of the invention
Fig. 1 is cluster processing stage schematic diagram in source in system mode of the invention；
Fig. 2 is network code stage schematic diagram in system mode of the invention；
Fig. 3 is flow diagram of the invention；
Fig. 4 is the flow diagram that the present invention is finely adjusted processing to the network code number M of acquisition；
Fig. 5 is Rayleigh channel, the bit error rate contrast schematic diagram of each algorithm under the conditions of L=64bit, N=5；
Fig. 6 is Rayleigh channel, the energy consumption comparison schematic diagram of each algorithm under the conditions of L=64bit, N=5；
Fig. 7 is Rayleigh channel, the bit error rate contrast schematic diagram of each algorithm under the conditions of L=128bit, N=5；
Fig. 8 is Rayleigh channel, the energy consumption comparison schematic diagram of each algorithm under the conditions of L=128bit, N=5.
Specific embodiment
The present invention is described in further details with reference to the accompanying drawings and examples.
Embodiment:
System model used in the present invention is established in WSN topology as unit of by cluster, needs to send the node position of data
In in the same cluster, as shown in Figure 1.N number of node S in one cluster1~SN, in the transmission of jth wheel, respectively need to save in relaying
By data packet u under the assistance of point R (being located in cluster)j1~ujNIt is sent to destination node D.If data packet length is L, node i is in
The generator matrix G of (n, k) LDPC code has been deployed respectively after node RjiWith network code vector And GiElement all belong to
In two element field GF (2).For simplified model, guaranteeing to send every time can all encode data packet, if L=k.
Transmission is completed by three phases, including source cluster processing stage, network code stage and joint decoding stage.In order to just
In narration, these three stages are known as a wheel by the present invention, describe system adopted by the present invention by taking jth wheel transmission process as an example below
System mode.
1. source cluster processing stage: the stage includes LDPC coding and broadcast transmission process.As shown in Figure 1, node S1~SN
Respectively by data packet uj,1~uj,NLDPC is carried out using formula (1) to encode to obtain cj,1~cj,N, then through ovennodulation,
Destination node D is sent to by way of the time-division again.Due to the broadcast characteristic of wireless communication, it is located in spread scope
Relay node R also will receive these data packets.In addition, the link of link-quality in cluster far better than cluster and destination node D
Quality, it can be assumed that the communication of cluster interior nodes is zero defect.And the channel of each node to destination node D can be in cluster
Think approximately uniform.
cj,i=uj,iGj,i,i∈[1,N]。 (1)
2. the network code stage: as shown in Fig. 2, relay node R demodulates the data packet received, then in GF (2)
M network code vector of upper selectionRi≠R1, by formula (2) by data packet cj,1~cj,NCarry out network
It is encoded to rj,1~rj,M, destination node is sent to after modulation in the way of the time-division.
Wherein,
3. the joint decoding stage: the operation in order to simplify node often exists in the wireless sensor network of practical application
With disposing identical LDPC code, i.e. G on the node in clusterj1=Gj2=...=GjN=G0, Hj1=Hj2=...=HjN=H0.Mesh
The data packet c that will receive of nodej,1,cj,2...,cj,N, rj,1,rj,2...,rj,NIt combines and carries out joint decoding, can ask
Generator matrix G must be combinedj:
Its joint decoding matrix are as follows:
Easily card,Therefore, HjIt is the joint check matrix of system, LDPC BP decoding algorithm can be used and joined
Close decoding.
Energy consumption model of the present invention is described below, and the system of comprehensive energy consumption model and combined coding is transmitted across
Journey analyzes the specific energy consumption in each stage of Combined Cipher Machine.
The energy consumption of WSN node is mainly made of reception energy consumption and transmission energy consumption, and receiving energy consumption includes receiving circuit energy consumption
With receiving antenna energy consumption, sending energy consumption then includes transmitting line energy consumption and antenna amplifier antennafire energy consumption, and the two all contains number certainly
Word signal processor (Digital Signal Processor, DSP) energy consumption.The increased joint decoding part of institute of the invention is disappeared
The energy consumption of consumption is exactly the processing energy consumption from processor.Energy consumption consumed by DSP be it is very small, compared to sending and receiving energy
Consumption can be ignored.But analyze in order to be more accurate and energy optimization algorithm is discussed, the present invention is by the place of cluster interior nodes DSP
Reason energy consumption also calculates in system energy consumption model, and can be followed by progress detailed analysis.
It first provides below and does not consider energy consumption consumed by the combined coding decoding stage, send and receive the consumption of 1bit data
Total energy consumption is respectively as follows:
ET=ETB+ETRF+EA, (6)
ER=ERB+ERRF+EL=ER0, (7)
Wherein, ETBAnd ERBIt is the energy consumption of baseband signal processor when sending or receiving 1bit data；ETRFAnd ERRFIt is hair
When sending or receive 1bit data, the energy consumption of front-end circuit；EAIt is power amplifier PA (Power when sending 1bit data
Amplifier energy consumption)；ELIt is the energy of low-noise amplifier LNA (Low Noise Amplifier) when receiving 1bit data
Consumption.
Based on the system model of Fig. 1 and Fig. 2, the energy consumption of a combined coding system equally point three parts are analyzed, and are respectively
Source cluster processing stage, network code stage and joint decoding stage.Receiving node is aggregation node, generally has lasting energy
Supply, so the energy of its consumption can be ignored, so the energy consumption that system one is taken turns is the sum of the first two stage.Given below is
One wheel sends energy consumed by each stage.
The energy consumption of source cluster processing stage are as follows:
Wherein, ach、bchIt is constant related with channel coding algorithm, EDBeing that baseband signal processor is every executes an instruction
Consumed energy, r are LDPC encoder bit rate, and N is sending node number, and M is network code packet number, EchIt is LDPC coding energy
Consumption is Ech=(achL+bch)ED, EtrIt is to send energy consumption as Etr=ET L/r,ElsIt is that relay node receives energy consumption as Els=ERL/r。
The energy consumption in network code stage are as follows:
Wherein an、bnIt is constant related with network code algorithm, EnIt is that network code energy consumption is
EtrIt is to send network code energy consumption to be
Since destination node is usually aggregation node, has the ability of continued power, so ignoring purpose decoding and feedback
The energy of consumption of information.
In conclusion the total energy consumption in combined coding transmission process are as follows:
Eall(N, M)=Ebr+ENA=N (Ech+Els)+(N+M)Etr+MEn. (10)
In actual wireless sensor network, multi-node wireless communication module is typically all to be emitted with fixed radio-frequency power
Signal, therefore the following conditions can regard establishment as:
1. the radio-frequency power of sensor node remains unchanged in entire transmission process.
2. the communication in cluster between each node does not decline.
3. system operation is with " wheel " (round) for unit, N number of every wheel of source node has channel coding packet (i.e. data packet) hair
It send.
Since the radio-frequency power of WSN node is fixed, i.e. EA=EA0, then wireless communication module sends the energy consumption E of 1bit dataT
For constant, then formula (6) can be rewritten as:
ET=ETB+ETRF+EA0=ET0 (11)
For the data packet that length is all L, EtrIt also is constant, therefore, the total energy consumption E that formula (10) is statedallIt can work as
It is the function of variable at N, M:
Eall=Ebr+ENA=N (Ech+Els+Etr)+M(Etr+En). (12)
Since wireless communication RF power remains unchanged in entire transmission process and channel and noise are constant, purpose
Total bit error rate that node D is obtained is also and the relevant function of N, M to be set as BER (N, M), and given bit error rate threshold value is
BER0, then problem to be solved is: how to reach given errored bit threshold value BER0Under the premise of, so that the energy of system
It consumes as small as possible.
Since each round has N number of node to need to send data, first item N (E on the right of formula (12)ch+Els+Etr) it is that cannot subtract
Few, so can only adjustment type (12) the right Section 2 M (Etr+En).And according to LDPC code relevant knowledge, M is bigger to be illustrated to combine
The verification relationship of decoding matrix is more, and successfully decoded probability is bigger, and bit error rate is lower, that is to say, that network code packet
Number M and bit error rate BER (N, M) are negatively correlated.On the other hand it can be obtained by formula (12), the bigger E of MallIt is bigger, it is meant that energy consumption is bigger,
That is, M and EallIt is positively correlated.How to find a suitable M value is problem to be solved of the present invention.In data transmission procedure
In, if the data volume that each node needs to send is SD, then the optimization problem is described as follows with mathematical linguistics:
With natural language description are as follows: in the case where having N number of node to need to send data packet in cluster, giving each node is needed
The data packet number SD and need bit error rate BER to be achieved to be transmitted0, optimal network coding nodes number M is sought, makes to transmit
The total energy consumption of process is minimum.Wherein MmaxIt is the maximum number for sending network code packet.Known joint decoding matrix, channel parameter
And signal-to-noise ratio solution (13) formula is relatively difficult, and measurement channel parameter and noise are also extremely complex work, so logical
The mode for crossing mathematical derivation finds optimal M and unrealistic.
Therefore it is excellent to devise a kind of adaptive dynamic energy consumption of enhanced wireless sensor network based on JNCC for the present embodiment
Change method, to find optimal M, the technical solution adopted is as follows:
As shown in figure 3, the adaptive dynamic energy consumption optimization method of enhanced wireless sensor network based on JNCC, is established
In WSN topology as unit of cluster, relay node by the destination node D joint decoding bit error rate information fed back and comprising
The network code packet number M that the mark vector dynamic adjustment epicycle of error code codeword position information needs to send, so that transmission data
Under the premise of meeting bit error rate requirement, system energy consumption is minimum, specifically comprises the following steps:
S11. low=0, high=N are initialized0, the region of search that M is arranged is [low, high], is counted using variable j
It sends wheel number and is initialized as 0,0 vector come marked erroneous code word and is initialized as using vector Fg,
S12., M is set as to the median of the region of search, i.e.,Wherein symbolIt indicates to be rounded downwards；
S13. LDPC coding packet and network code packet r are sentj-1, wherein network code packet marks simultaneously with by mark vector Fg
Related in the wrong code word of upper wheel storage, specific generating mode is defined by the formula:
Wherein: c1'~cNe' it is the code word that the upper wheel of mark vector Fg label decodes not successfully, Ne is failed decoding code
The sum of word,It is network code vector；
S14. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Count out bit error rate BER；
S15. destination node D generates mark vector Fg；
S16. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S17. relay node adjusts the node number M of network code according to the bit error rate situation of feedback, specifically: if
BER≤BER of return0, then reduce M, execute high=M, conversely, then increasing M, execute low=M+1；
S18. judge whether low is more than or equal to high, if not return step S12, if so then execute end.
Preferably, the step S15 generates mark vector by following mark vector generation method:
S21. initialization LDPC encodes packet number i=0；
S22. destination node is iterated decoding to i-th of LDPC coding packet received；
S23. i-th of code word is determined, if cj,iHT==0, then illustrate it is successfully decoded, then by mark vector Fg
I-th of element fi be set as 0；
If S24. cj,iHT≠ 0, then illustrate to decode unsuccessful, store it in buffer, and by the of mark vector Fg
I element fi is set as 1；
S25. judge whether i is more than or equal to N0, return step S22 if not, if then terminating.
Wherein, when bit error rate can be decoded according to LDPC, the number of check equations is unsatisfactory for estimate.
In the present embodiment, in the step S13, LDPC coding packet and network code packet are sent according to selection strategy is sent,
The transmission selection strategy is as follows:
S31. source cluster node broadcast transmission N0A LDPC coding packet cjTo destination node D and relay node R；
S32. if wheel number j！=1 and mark vector Fg！=0, then relay node R sends M network code packet rj-1To mesh
Node D, otherwise do not send network code packet.
Since in above process, bit error rate is existed certain by estimating to obtain after destination node D joint decoding
Deviation, therefore may not be optimal M value in the network code number M obtained by above-mentioned process.In addition, channel condition with
Time, there is also slight changes, and therefore, the present embodiment further includes that the network code number M obtained to search adjustment is finely adjusted again
Processing, the trim process process as shown in figure 4, specifically:
S40., M=M is set0, j=j0, wherein M0And j0Respectively coarse tuning stage obtain about the value of M and the value conduct of j
Initial value；
S41. initialization sends the number total=0 of data packet, and initialization error logging number is error=0；
S42. data of every transmission then total=total+1；
S43. it is selected to send LDPC coding packet and network code packet according to sending strategy；
S44. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Count out bit error rate BER；
S45. destination node D generates mark vector Fg by mark vector generation method；
S46. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S47. relay node receives the bit error rate situation of feedback and judges whether to be less than BER0, if so, S48 is executed,
If executing S48 after otherwise executing error=error+BER；
S48. judge whether total is greater than total0, if so, S49 is executed, if otherwise executing S411；
S49. judge whether BER is greater than BER0, if so then execute M=M+1, S41 is returned to, if otherwise executing S410；
S410. judge whether BER is less than BER0/ 2, if so then execute M=M-1, S41 is returned to, if otherwise executing S411；
S411. judge whether data have all sent, if then terminating, if otherwise returning to S42.
For the performance of method more proposed by the present invention, the present embodiment has carried out Computer Simulation, and the present embodiment uses
IT++ software package completes that binary system (n, k) LDPC code word generates, work, the channel such as decoding use Rayleigh channel model,
Change received signal to noise ratio at a distance from destination node by adjusting cluster.All emulation uses binary phase shift keying modulation methods
Formula.Allocation of computer is 3GB memory, Intel (R) Core (TM) 2Duo CPU E4400 2.00GHz Ubuntu14.04 operation
System, emulation experiment parameter is as shown in table 1,
List is arranged in 1 simulation parameter of table
In simulation result diagram, method of the invention is referred to EDEC, and BER results of property is as shown in figure 5, energy consumption and performance knot
Fruit is as shown in Figure 6.In figure, Eb/N0 indicates Normalized Signal/Noise Ratio, and unit is decibel (dB).Fig. 5 and Fig. 6 compare long data packet
Degree is 64, code rate 1/2, when source node number is 5, the performance comparison of each algorithm.The present invention mentions it can be seen from Fig. 5 and Fig. 6
Adaptive dynamic energy consumption optimization algorithm has more preferable energy consumption and performance compared to other algorithms out.
For traditional combined coding algorithm (JNCC), network code packet number is in entire data transmission procedure
It remains unchanged.The present embodiment simulates M=0, and 1,3,5 four kind of situation is indicated respectively with JNCC (M=0,1,3,5), wherein working as M
When=0, illustrate no network code packet, only channel coding portions.
As can be known from Fig. 5 and Fig. 6, the adaptability of JNCC algorithm is poor, regardless of channel conditions quality, keeps network
Coding packet number is constant, and when signal-to-noise ratio is smaller, less M value, which does not ensure that, reaches bit error rate requirement (10-3).Work as noise
Than it is bigger when, biggish M value means to send more network code packets, wastes energy unnecessary.JANCC is calculated
For method, when destination node decoding is undesirable, a network code packet relevant to wrong code word, mesh are sent by relay node
Node the wrong code word of storage and this network code packet are subjected to joint decoding again, improve error performance.Although JANCC
Algorithm has the function of some adaptive, and still, what can be adjusted is limited in scope.From fig. 5, it can be seen that when signal-to-noise ratio is less than
When 6dB, JANCC algorithm does not ensure that bit error rate requirement.
For EDEC and ADEC algorithm, since they can be according to decoding situation (the estimation errored bit of destination node
Rate), to adjust the network code packet number M for needing to send, can guarantee in SNR ranges to be to reach in the section [3dB ,+∞]
Transmission requirement, so adaptability is stronger.But when signal-to-noise ratio is less than 3dB, they are even if sending N number of network code packet
It can not reach given transmission requirement.When signal-to-noise ratio is greater than or equal to 9dB, since channel is good enough, it is not required under maximum probability
It sends network code packet and carries out joint decoding, so the bit error rate of the bit error rate curve of EDEC algorithm and JNCC (M=0)
Curve is almost overlapped.
And in terms of energy consumption, from fig. 6, it can be seen that when signal-to-noise ratio is less than or equal to 2dB, the energy of EDEC and ADEC algorithm
Consumption can be the same, this is because EDEC algorithm and ADEC algorithm are all under greater probability in the case where channel is poor
The network code packet of maximum quantity (M=8) is sent, to reach given bit error rate requirement, energy consumption curve as much as possible
Close to JNCC (M=8).But when signal-to-noise ratio section (2dB, 9dB] on change when, EDEC algorithm is better than ADEC algorithm, this is
Because of the method that EDEC algorithm uses mark vector, network code packet relevant to wrong code word is only sent, epicycle biography is improved
Defeated reliability reduces the transmission of network code packet, while reaching bit error rate requirement, is reduced as far as energy and disappears
Consumption.In addition the thought of HARQ is used in EDEC, there is no need to retransmit network code if channel coding packet is successfully received
Packet carries out additional interpretations, avoids unnecessary energy consumption.
Fig. 7 and Fig. 8 is the bit error rate and energy consumption of each algorithm under the conditions of Rayleigh channel, L=128bit, N=5 respectively
Performance comparison figure, it can be seen that algorithm of the invention still has good energy consumption and performance.
Claims (4)
1. the adaptive dynamic energy consumption optimization method of enhanced wireless sensor network based on JNCC is established as unit of by cluster
In WSN topology, which is characterized in that relay node by the destination node D joint decoding bit error rate information fed back and comprising
The network code packet number M that the mark vector dynamic adjustment epicycle of error code codeword position information needs to send, so that transmission data
Under the premise of meeting bit error rate requirement, system energy consumption is minimum, specifically comprises the following steps:
S11. low=0, high=N are initialized0, the region of search that M is arranged is [low, high], and transmission is counted using variable j
Wheel number is simultaneously initialized as 0, come marked erroneous code word and is initialized as 0 vector using vector Fg,
S12., M is set as to the median of the region of search, i.e.,Wherein symbolIt indicates to be rounded downwards；
S13. LDPC coding packet and network code packet r are sentj-1, wherein it network code packet and is marked by mark vector Fg and upper
The wrong code word for taking turns storage is related, and specific generating mode is defined by the formula:
Wherein: c1'~cNe' it is the code word that the upper wheel of mark vector Fg label decodes not successfully, Ne is failed code word
Sum,It is network code vector；
S14. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Bit error rate BER；
S15. destination node D generates mark vector Fg；
S16. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S17. relay node adjusts the node number M of network code according to the bit error rate situation of feedback, specifically: if returned
BER≤BER0, BER0It indicates errored bit threshold value, then reduces M, execute high=M, conversely, then increasing M, execute low=M+1；
S18. judge whether low is more than or equal to high, if not return step S12, if so then execute end.
2. the enhanced wireless sensor network adaptive dynamic energy consumption optimization side according to claim 1 based on JNCC
Method, which is characterized in that step S15 generates mark vector by following mark vector generation method:
S21. initialization LDPC encodes packet number i=0；
S22. destination node is iterated decoding to i-th of LDPC coding packet received；
S23. i-th of code word is determined, if cJ, iHT==0, then illustrate it is successfully decoded, then by the i-th of mark vector Fg
A element fi is set as 0；
If S24. cJ, iHT≠ 0, then illustrate to decode unsuccessful, stores it in buffer, and by i-th yuan of mark vector Fg
Plain fi is set as 1；
S25. judge whether i is more than or equal to N0, return step S22 if not, if then terminating.
3. the enhanced wireless sensor network adaptive dynamic energy consumption optimization side according to claim 1 based on JNCC
Method, which is characterized in that in the step S13, send LDPC coding packet and network code packet, the hair according to selection strategy is sent
Send selection strategy as follows:
S31. source cluster node broadcast transmission N0A LDPC coding packet cjTo destination node D and relay node R；
S32. if wheel number j！=1 and mark vector Fg！=0, then relay node R sends M network code packet rj-1To purpose section
Point D, does not otherwise send network code packet.
4. the enhanced wireless sensor network adaptive dynamic energy consumption optimization side according to claim 1 based on JNCC
Method, which is characterized in that further include that processing, the trim process are finely adjusted again to the network code number M of acquisition specifically:
S40., M=M is set0, j=j0, wherein M0And j0What respectively coarse tuning stage obtained is used as initial about the value of M and the value of j
Value；
S41. initialization sends the number total=0 of data packet, and initialization error logging number is error=0；
S42. data of every transmission then total=total+1；
S43. it is selected to send LDPC coding packet and network code packet according to sending strategy；
S44. the wrong code word of the network code packet received and upper wheel storage is carried out joint decoding by destination node D, is estimated
Bit error rate BER；
S45. destination node D generates mark vector Fg by mark vector generation method；
S46. the bit error rate BER of estimation and mark vector Fg are back to relay node R by destination node D；
S47. relay node receives the bit error rate situation of feedback and judges whether to be less than BER0, if so, S48 is executed, if otherwise
S48 is executed after executing error=error+BER；
S48. judge whether total is greater than total0, if so, S49 is executed, if otherwise executing S411；
S49. judge whether BER is greater than BER0, if so then execute M=M+1, S41 is returned to, if otherwise executing S410；
S410. judge whether BER is less than BER0/ 2, if so then execute M=M-1, S41 is returned to, if otherwise executing S411；
S411. judge whether data have all sent, if then terminating, if otherwise returning to S42.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104618993A (en) * | 2014-12-29 | 2015-05-13 | 中山大学 | Self-adaptive dynamic energy consumption optimizing method for wireless sensor network based on JCNC |
| CN105120503A (en) * | 2015-07-17 | 2015-12-02 | 杭州电子科技大学 | High-energy-efficiency node cooperative transmission method in wireless sensor network |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104618993A (en) * | 2014-12-29 | 2015-05-13 | 中山大学 | Self-adaptive dynamic energy consumption optimizing method for wireless sensor network based on JCNC |
| CN105120503A (en) * | 2015-07-17 | 2015-12-02 | 杭州电子科技大学 | High-energy-efficiency node cooperative transmission method in wireless sensor network |
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