CN111865488B - Code selection method for multi-hop short packet communication - Google Patents
Code selection method for multi-hop short packet communication Download PDFInfo
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- CN111865488B CN111865488B CN202010386207.2A CN202010386207A CN111865488B CN 111865488 B CN111865488 B CN 111865488B CN 202010386207 A CN202010386207 A CN 202010386207A CN 111865488 B CN111865488 B CN 111865488B
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Abstract
The invention discloses a code selection method for multi-hop short packet communication, which specifically comprises the following steps: setting an analysis algorithm of decoding failure probability of the RLNC coding method in a multi-hop short packet communication scene; solving the minimized decoding failure probability to obtain the RLNC coding parameters of optimal design; judging whether coefficient cost generated by the coding parameters counteracts coding gain of an opposite end-to-end fountain coding method of the RLNC coding method, if so, selecting and using the end-to-end fountain coding method in the multi-hop short packet communication scene. The invention provides the RLNC method which is characterized by selecting whether the multi-hop link uses the end-to-end fountain coding method or recoding under the condition of short packets with smaller data scale, and can effectively guide the evaluation and selection of the system transmission scheme under different scenes.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to a code selection method for multi-hop short packet communication.
Background
The multi-hop short packet communication plays an important role in wireless scenes such as autonomous driving (such as vehicle queues), the internet of things and the like. Because of the long feedback delay of the conventional retransmission-based method, the retransmission method is very inefficient in the system where low-delay data delivery is required. In contrast, the use of packet-level fountain codes is considered an effective approach. The encoded data packets in the fountain code may be sent continuously and not require a feedback until the entire message is recovered. Conventional End-to-End (E2E) fountain codes, such as Raptor codes, have been used in Long-Term Evolution (LTE) systems. On the other hand, random linear network coding (Random Linear Network Coding, RLNC) is also of great application value. RLNC allows re-encoding on intermediate nodes on multi-hop links, which can theoretically further improve throughput, compared to E2E fountain codes. However, no technical solution in the prior art gives a suggestion as to which coding method should be selected.
Disclosure of Invention
The invention provides a code selection method for multi-hop short packet communication, which solves the problem that no technical scheme in the prior art gives a hint of which code method should be selected.
The technical scheme of the invention is realized as follows:
a code selection method for multi-hop short packet communication specifically comprises the following steps:
s1, setting an analysis algorithm of decoding failure probability of an RLNC coding method in a multi-hop short packet communication scene;
s2, solving the minimized decoding failure probability to obtain the RLNC coding parameters of optimal design;
and S3, judging whether coefficient overhead generated by the coding parameters counteracts coding gain of an opposite end-to-end fountain coding method of the RLNC coding method, and if so, selecting the end-to-end fountain coding method in the multi-hop short packet communication scene.
As a preferred embodiment of the present invention, step S1 specifically includes the steps of:
s101, establishing a calculation model of decoding failure probability of an RLNC coding method in a communication scene;
s102, substituting parameters related to the communication scene into a calculation model to obtain decoding failure probability.
As a preferred embodiment of the present invention, the parameters related to the communication scenario in step S102 include, but are not limited to, field size, link hop count, node buffer size, encoding finite field size, and packet loss rate.
As a preferred embodiment of the present invention, step S2 specifically includes the steps of:
s201, given physical layer short packet constraint, cross-layer design is carried out by utilizing a finite block length coding theory and combining a decoding failure probability analysis algorithm;
s202, solving the minimized decoding failure probability based on a low-complexity algorithm to obtain the RLNC coding parameters of the optimal design.
As a preferred embodiment of the present invention, the cross-layer design in step S201 refers to reducing the search theoretical numerical search space.
As a preferred embodiment of the present invention, the low complexity algorithm in step S202 refers to reducing the number of loops of the decoding failure probability analysis algorithm.
The invention has the beneficial effects that: the method provides a method for selecting whether the multi-hop link uses an end-to-end fountain coding method or an RLNC method featuring recoding under the condition of short packets with smaller data scale, and can effectively guide the evaluation and selection of the system transmission scheme under different scenes.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of one embodiment of a code selection method for multi-hop short packet communications in accordance with the present invention;
FIG. 2 is a schematic diagram of a node for multi-hop short packet communications;
fig. 3 is a schematic diagram of DFP calculated using algorithm 1;
fig. 4 is a schematic diagram of a calculation using algorithm 2.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the present invention proposes a code selection method for multi-hop short packet communication, which specifically includes the following steps:
s1, setting an analysis algorithm of decoding failure probability of an RLNC coding method in a multi-hop short packet communication scene;
the step S1 specifically comprises the following steps:
s101, establishing a calculation model of decoding failure probability of an RLNC coding method in a communication scene;
consider the L-hop lossy link in fig. 2, where node S passes through relay R 1 ，…，R L-1 And sending the Fbit message to the node D. The transmission time is measured by the number of network uses. Each time it is used, it is generated on one hop
And L is 1, …, L, respectively. The node S may be an intelligent terminal having a processor and a wireless communication chip in a wireless scenario of the internet of things, where the processor may be configured to determine and select a coding manner.
The transmitted message is equally divided into M source packets of size Kbit, denoted s 0 ，s 1 ，...s M-1 Obtaining MK not less than F. If the case where F cannot be equally divided by M occurs, 0 is appended at the end of the source packet to make it Kbit. Using RLNC coding methods, each packet from node S can be represented as
Here g i，j Representing a finite field F of size q q Is selected at random. Without loss of generality, assume that the selected finite field is F 2 . An Encoding Vector (EV) expressed as [ g ] 0，j ，...，g M-1 ]Size M log 2 q bits. The length of the whole RLNC packet is N, and M log can be obtained 2 q+K is less than or equal to N. Each RLNC packet has a physical layer channel codeword n 1 Is encoded in S-R 1 Equal channel code rate +.>
The error rate (Block Error Ratio, BLER) of the channel block of the 1 st hop is epsilon 1 . Relay R l The buffer size of (a) is m l . When the cache is saturated, the oldest packet may be discarded. Let R be l The buffered packet is r 0 ，...，r k-1 The packet transmitted by the relay is +.>
H here j Also from finite field F q Randomly selected. The new coding coefficient is->
The code rate and BLER of the first hop are +.>
And epsilon l . The destination node D decodes by using gaussian elimination. When D receives M linearly independent encoded packets, it can recover the original message and feed back at the same time, and it should be noted that D does not feed back during transmission.
Let p be fail (T) =pr { T > T } means that the Fbit message has no DFP completed transmission after T network slots. Given F, m l ，n l And
l=1, a.i., L, the transmission completion times T (and its DFP) and N, M, K, q (also related to ε) l Related to.
At a given M, q, ε l Tracking the number of linearly independent packets. L sets of elements, where X l Represented at R l The number of linear independent packets, relative to R l Is invasively independent with respect to downstream nodes of the network. X is X L Representing the number of linear independent packets in D, resulting in
Each transmission on a 1-hop causes a state transition that occurs in one network use
Conversion, the entire transmission phase starts from x=0 to x= [0, …,0, m]And (5) ending. DFP corresponds to X after using t networks L ≠M。
Transmission occurs first at 1 hop, then +.>
The transmission occurs at 2 hops, which in turn. In fact, if each hop can be transmitted asynchronously, it is always possible to select the appropriate point in time, according to their incoming timeInter-transmission ordering.
According to the model, it was found that transmission on 1 hop would cause a slave [ X ] 1 ，…，X L ]To [ X ] 1+1 ，…，X L ]If X is a state transition of 1 ＜m 1 The probability is
If the EV is not within the linear range of all downstream node buffered packets, the S-randomly encoded packets are linearly independent. Otherwise, a self-switching occurs.
At the first hop (l > 1), send to R l Is re-encoded by the packets in the buffer. A packet that is randomly re-encoded thus increases X l . The probability of which can be expressed as
At R l-1 X in (2) l-1 Of the linearly independent packets, at least one packet contains a non-zero coefficient code. Then there is a state transition, i.e. X l-1 Minus 1 and X l The probability of adding 1 is
The probability of each state after a transmission can be determined to be Pr { u } = Σby using the Chapman-cole Mo Geluo f equation v Pr { u|v } Pr { v }. Wherein Pr { v } represents the probability of each state at present, pr { u|v } represents the upward transition probability, a state set is set as a row of the matrix S, and the probability corresponding to the state set is set as an array p c The DFP may be expressed as
S102, substituting parameters related to the communication scene into a calculation model to obtain decoding failure probability. The communication scenario-related parameters include, but are not limited to, field size, link hop count, node buffer size, encoding finite field size, and packet loss rate.
S2, solving the minimized decoding failure probability to obtain the RLNC coding parameters of optimal design;
the step S2 specifically comprises the following steps:
s201, given physical layer short packet constraint, cross-layer design is carried out by utilizing a finite block length coding theory and combining a decoding failure probability analysis algorithm;
as shown in Algorithm 1 (Algorithm 1), the observable state sets and their corresponding probabilities can be derived from the rows and arrays p of the matrix S c Obtained from the elements of (a). When the probability of transitioning to such a state is calculated for the first time, the state is referred to as an observed state. The empty set pnew is used to store the observed Pr { u }. The newly observed state is added to S.
In steps 7 to 23 of algorithm 1, a large amount of computation time is required to update the probability for each state that has been found. Let χ represent the L-tuple state set, we can get:
here I·| represents the cardinality of the collection, while m L ＝M。
When M, L or M l Upon growth, |χ| will grow rapidly, especially as L grows.
S202, solving the minimized decoding failure probability based on a low-complexity algorithm to obtain the RLNC coding parameters of the optimal design.
As algorithm 1 proceeds, the probability of most observed states is very close to 0. Can be obtained from S and p respectively after the 24 th step c These states and their corresponding probabilities are eliminated so that the number of subsequent cycles remains small. Specifically, only the constant at which the probability of c states is maximum is maintained. To ensure that the sum of the probabilities remaining in pc is 1, an effective distribution is formed, and the probability of discarding and the probability of the smallest possible state among the remaining states are added. This isDesign principles of low complexity algorithms.
Let N, M, K, q be integers, p fail (t) can only be calculated numerically by algorithm 1. This section solves for the minimized decoding failure probability by searching the theoretical numerical space, which is reduced at key times here.
Each hop in fig. 2 is assumed to be a real Additive White gaussian GaussianNoise, AWGN channel. However, the following procedure is also applicable to more complex channel models, given SNR l Representing the signal-to-noise ratio of an AWGN channel, the length of a channel codeword n l Can be used to calculate the BLER, thereby yielding the number of information bits:
here, the
Is the capacity of the channel, ">
Representing channel dispersion, the availability of:
then, keeping the value of N unchanged, M log 2 q+K.ltoreq.N does not affect DFP. For each q, only care needs to be taken so that
K is an integer. Further studies have found that a larger K corresponds to a smaller M and thus also a lower DFP.
By searching for N and q, the minimized decoding failure probability can be solved. N E [ N ] 1b ，N ub ]，
Q which can be used in practice is limited, and these available Q can be denoted by Q. Algorithm 2 (Algorithm 2) is used to perform such a search, rather than traversing all (N, q) combinations. Algorithm 2 traverses N in ascending order, using a hash table to store the (M, q) that has been calculated. This is because a smaller N corresponds to a more reliable physical layer. Thus, at the same (M, q), DFP is strictly smaller than when using a larger N. The same (M, q) will be skipped at step 9. In this way the search space can be significantly reduced. Actually estimated p fail The number of (a) may be less than 2% of the worst case (Nub-N1 b) |q|.
And S3, judging whether coefficient overhead generated by the coding parameters counteracts coding gain of an opposite end-to-end fountain coding method of the RLNC coding method, and if so, selecting the end-to-end fountain coding method in the multi-hop short packet communication scene.
The technical scheme of the invention is illustrated below.
The RLNC and E2E fountain codes are evaluated and compared by typical numerical values and simulation results. In the simulation, bernoulli elimination is used to generate random content packets, which are then encoded, re-encoded, and decoded.
q∈Q＝{2，4，...，256}，|Q|＝8，/>
For different L, FIG. 3 is an approximation of the DFPs obtained by algorithm 1. Although c=5000 is inaccurate, increasing it to 10000 is sufficient to obtain DFPs that match the simulation. This indicates that this approximation is valid and the analysis is correct. For l=12, c=10000 means that only about 0.034% of the state (|χ|=29, 867, 487) is retained in the algorithm.
Fig. 4 shows a solution process using algorithm 2, with 4-hop relay of f=4000 bits
m l ＝8，n l ＝256，t＝20，SNR l Comparison of =5, let us set for all AWGN channels, for simplicity>
n l =256, snr1=snr=5. Each red dot corresponds to one DFP evaluation at step 12 of algorithm 2, which invokes algorithm 1, c=10000. As a comparison, DFP was calculated for all possible (N, M, q) combinations, with the blue line representing the minimum DFP for each N. It can be seen that the number of DFPs calculated (i.e. 24) is only a very small fraction of the worst case (1.46%), at which time (Nub-N1 b) |q|=1640. Algorithm 2 successfully obtained the optimal parameters that minimize DFP, demonstrating that when the optimal N (or equivalent epsilon l ) A trade-off is required. Also shown is the DFP modeled using parameters corresponding to the blue line, which exactly match the blue line.
Finally, cross-layer optimized RLNC and E2E fountain codes, including Raptor code for R10 and RLNC for E2E (without reediting) are compared. The numerical results of RLNC (with recoding) DFP are given below. Through simulation, the optimal DFP of the E2E code corresponding to the cross-layer design is obtained. The E2E code is almost always lower than the recoded DFP. The signal-to-noise ratio of the Raptor code is only 10 due to its sparsity. It is well known that re-encoding is beneficial on multi-hop lossy links (when CO is ignored), but data shows that re-encoding is poor if CO is not negligible. The optimized parameters indicate that due to CO effects, the RLNC M and corresponding optimal (or N) is not less than the E2E code, resulting in more data packets being sent over more lossy channels, and thus higher DFP. It follows that the E2E coding scheme should be selected for use at this time.
The invention provides the RLNC method which is characterized by selecting whether the multi-hop link uses the end-to-end fountain coding method or recoding under the condition of short packets with smaller data scale, and can effectively guide the evaluation and selection of the system transmission scheme under different scenes.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (4)
1. A code selection method for multi-hop short packet communication, comprising the steps of:
s1, setting an analysis algorithm of decoding failure probability of an RLNC coding method in a multi-hop short packet communication scene;
the step S1 specifically comprises the following steps:
s101, establishing a calculation model of decoding failure probability of an RLNC coding method in a communication scene;
s102, substituting parameters related to a communication scene into the calculation model to obtain decoding failure probability;
s2, solving the minimized decoding failure probability to obtain the RLNC coding parameters of optimal design;
the step S2 specifically comprises the following steps:
s201, given physical layer short packet constraint, cross-layer design is carried out by utilizing a finite block length coding theory and combining a decoding failure probability analysis algorithm;
s202, solving the minimized decoding failure probability based on a low-complexity algorithm to obtain an optimally designed RLNC coding parameter;
and S3, judging whether coefficient overhead generated by the coding parameters counteracts coding gain of an opposite end-to-end fountain coding method of the RLNC coding method, and if so, selecting the end-to-end fountain coding method in the multi-hop short packet communication scene.
2. The code selection method for multi-hop short packet communication according to claim 1, wherein the communication scenario-related parameters in step S102 include a field size, a link hop count, a node buffer size, a code finite field size, and a packet loss rate.
3. The code selection method for multi-hop short packet communication according to claim 1, wherein the cross-layer design in step S201 refers to reducing a search theoretical numerical search space.
4. The code selection method for multi-hop short packet communication according to claim 1, wherein the low complexity algorithm in step S202 refers to a reduction in the number of loops of the decoding failure probability analysis algorithm.
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