CN111224751A - Rate control method for improving wireless network coding gain - Google Patents
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Abstract
The invention discloses a rate control method for improving wireless network coding gain, which can provide rate control aiming at the situation that opportunity network coding faces different users and different channel qualities in an LTE network, and makes up the defect of researching an opportunity network coding rate control mechanism in the prior research; and the code selection strategy based on the transmission efficiency of the coding packet can increase the coding opportunity of network coding under the condition of maximizing the transmission efficiency of the coding packet, improve the average coding degree of the coding packet, and effectively improve the performance gains of time delay, throughput rate and the like of opportunity network coding.
Description
Technical Field
The invention relates to the field of communication, in particular to a rate control method for improving wireless network coding gain.
Background
Network coding technology has been proven to effectively improve wireless network performance, including performance indexes such as throughput rate, delivery delay, energy efficiency, etc., and has been applied to LTE cellular networks, such as cooperative transmission combining network coding and relay selection, etc. However, in a wireless application environment, due to the fact that the wireless application environment is subjected to a complex and variable communication environment and due to frequent changes of channel conditions, channel quality is reduced, and burst packet loss of transmission packets occurs, the network transmission performance is greatly affected. For the situation of high packet loss rate in these wireless network environments, it is difficult to effectively exert expected performance gain by applying the existing network coding architecture.
In order to ensure reliable delivery of coded packets, in a wireless network with a multi-rate control function, an existing network coding architecture generally defaults to a coding node to deliver coded packets with a lowest transmission rate in exchange for a higher delivery rate. If the primary receiving node receives the encoded packet, the default secondary receiving node also receives the encoded packet. On one hand, the method limits the application of multi-rate and cannot better utilize the bandwidth resources of the wireless network. On the other hand, in an actual network scenario, the method neither can completely ensure reliable delivery of the coded packet, nor introduces some other problems, for example, a lower transmission rate may result in a longer transmission time, thereby greatly increasing the chance of collision of the data packet, and reducing the delivery rate of the network data packet and the overall network throughput rate. Meanwhile, for the coding node, how to handle the broadcast bottleneck problem caused by a plurality of receiving nodes of coding packets with different channel qualities is very urgent. Therefore, how to make a better compromise on the reliable delivery of coded packets and coding gain is an important research aspect.
In the related research of the existing network coding and rate control mechanism, joint design of the network coding and the MAC mechanism is mainly discussed to optimize the network throughput rate performance, and the unified design of a network coding algorithm and rate control is rarely researched. With the application of the millimeter wave technology in the LTE cellular network, compared with the traditional frequency band lower than 6GHz, the transmission packet loss rate of the communication in the millimeter wave frequency band is much higher, and it is necessary to ensure reliable, low packet loss rate and stable data rate. By realizing the unified design of the network coding algorithm and the rate control, higher network throughput rate, higher reliability and lower system delivery delay can be obtained. Therefore, it is very important to research a rate control method based on network coding.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a rate control method aiming at the situation that the opportunistic network coding faces different users and different channel qualities in an LTE network, so as to improve the delivery efficiency of a coding packet and further improve the overall performance of the system by the network coding.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a rate control method for improving wireless network coding gain is characterized in that the method comprises the following steps:
step S1, for transmitting a coded packet with a coding degree n, defining the state in the process of speed control during transmission as the coded packet receiving node set GnEach node in the subset having failed to receive the encoded packet, using an n-bit vector (b)1，b2，...，bi，...，bn) To represent this subset, wherein biE {0, 1}, when biWhen 1, it indicates a receiving node set GnThe ith receiving node in the network has not received the encoded packet yet, when biWhen 0, this indicates the receiving node set GnThe ith receiving node in the network receives the coded packet, and for a coded packet with a coding degree of n, there are n receiving nodes, so that | S | ═ 2nAnd a possible state.
Step S2, when an encoding node is to send an encoded packet, it may select from decision set a ═ { r ═ r1，r2，...，rK，r1≤r2…≤rKSelect a transmission rate, the number of transmission rates in the set is the number of types of decisions that can be selected.
Step S3, for transmission rate rkWhen, the node i belongs to GnGiven a parameter (delivery rate of packets) of pi(rk) The Bernoulli model of (1), then from state StTransition to State St+1The state transition probability of time can be calculated by the following formula:
step S4, defining the profit obtained in the process of state transition to be divided by the time cost brought by the transmission of the coding packet, defining the reward as the transmission efficiency (CPTE) of the coding packet, and carrying out the encoding packet
It designates the receiving node as set GLIf participating in the encoded data packet PiHas a data packet length of li(bits), i is more than or equal to 1 and less than or equal to L, then the corresponding code packet
Length equal to the length max of the longest data packet therein1≤i≤Lli(ii) a If decision a is taken during decision stage ttThen from state StTransition to state st+1Reporting of time
Comprises the following steps:
step S5, determining an optimization target, optimizing the total expected CPTE value from the decision stage t to the decision stage N-1, and calculating by the following formula:
in a rate selection process with N decision stages, if
Define CPTE(s)t，t)＝0。
Step S6, determining an optimal decision, which is given by the following formula:
for the obtained optimal solution and the corresponding optimal decision, the following backward recursion algorithm is used:
a1, setting t equal to N and
a2, let
Calculating CPTE(s)tT) and πt(st)；
And A3, if t is equal to 0, stopping calculation, and otherwise, turning to A2 to continue calculation.
Further, the codec that achieves the maximum CPTE value is selected from all possible codecs, and pl (D (P) is usedi) Represents node D (P)i) Decoding the data packet set cached in the packet pool, optionally obtaining the encoding solution CA through the XOR operation and the corresponding packet set CsetCan be expressed as:
Cset＝{x1P1}∪{x2P2}∪L{XMPM}；
wherein,
accordingly, the initial reception state of the receiving node that gets the encoded packet may be expressed as:
s0＝{D(x1P1)}∪{D(x2P2)}∪L{D(xMPM)}；
therefore, the Integer Linear Programming (ILP) of the code selection problem based on CPTE values is summarized as:
max CPTE(st，t)|t＝0，
and obtaining an optimal coding solution through solving.
The invention has the beneficial effects that:
(1) aiming at the opportunity network coding, when the opportunity network coding faces different users and different channel qualities in an LTE network, rate control is provided, and the defect of researching an opportunity network coding rate control mechanism in the existing research is overcome;
(2) the code selection strategy based on the transmission efficiency of the coding packet can increase the coding opportunity of network coding under the condition of maximizing the transmission efficiency of the coding packet, improve the average coding degree of the coding packet, and effectively improve the performance gains of time delay, throughput rate and the like of opportunity network coding.
Drawings
The invention is further illustrated with reference to the following figures and examples.
Fig. 1 is a diagram of a typical "Cross" network coding scenario and packet delivery rates of links at different transmission rates, where a network coding group includes 4 code streams:
and
belonging to the case of "Cross" topology;
FIG. 2 is the average delivery delay end-to-end at different rates in the topology shown in FIG. 1, the rate control strategy (COPE) under a typical opportunistic network coding framework and the rate control mechanism (ORC) of the present invention;
fig. 3 is a flow chart of opportunistic network coding rate control.
Detailed Description
A rate control method for improving wireless network coding gain is characterized in that the method comprises the following steps:
step S1, for transmitting a coded packet with a coding degree n,defining the state in the process of controlling the speed rate during transmission as the code packet receiving node set GnEach node in the subset having failed to receive the encoded packet, using an n-bit vector (b)1，b2，...，bi，...，bn) To represent this subset, wherein biE {0, 1}, when biWhen 1, it indicates a receiving node set GnThe ith receiving node in the network has not received the encoded packet yet, when biWhen 0, this indicates the receiving node set GnThe ith receiving node in the network receives the coded packet, and for a coded packet with a coding degree of n, there are n receiving nodes, so that | S | ═ 2nAnd a possible state.
Step S2, when an encoding node is to send an encoded packet, it may select from decision set a ═ { r ═ r1，r2，...，rK，r1≤r2...≤rKSelect a transmission rate, the number of transmission rates in the set is the number of types of decisions that can be selected.
Step S3, for transmission rate rkWhen, the node i belongs to GnGiven a parameter (delivery rate of packets) of pi(rk) The Bernoulli model of (1), then from state StTransition to State st+1The state transition probability of time can be calculated by the following formula:
step S4, defining the profit obtained in the process of state transition to be divided by the time cost brought by the transmission of the coding packet, defining the reward as the transmission efficiency (CPTE) of the coding packet, and carrying out the encoding packet
It designates the receiving node as set GLIf participating in the encoded data packet PiHas a data packet length of li(bits), i is more than or equal to 1 and less than or equal to L, then the corresponding code packet
Length equal to the length max of the longest data packet therein1≤i≤Lli(ii) a If decision a is taken during decision stage ttThen from state StTransition to State St+1Reporting of time
Comprises the following steps:
step S5, determining an optimization target, optimizing the total expected CPTE value from the decision stage t to the decision stage N-1, and calculating by the following formula:
in a rate selection process with N decision stages, if
Define CPTE(s)t，t)＝0。
Step S6, determining an optimal decision, which is given by the following formula:
for the obtained optimal solution and the corresponding optimal decision, the following backward recursion algorithm is used:
a1, setting t equal to N and
a2, let
Calculating CPTE(s)tT) and πt(st)；
And A3, if t is equal to 0, stopping calculation, and otherwise, turning to A2 to continue calculation.
Further, the codec that achieves the maximum CPTE value is selected from all possible codecs, and pl (D (P) is usedi) Represents node D (P)i) Decoding the data packet set cached in the packet pool, optionally obtaining the encoding solution CA through the XOR operation and the corresponding packet set CsetCan be expressed as:
Cset＝{x1P1}∪{x2P2}∪L{xMPM}；
wherein,
accordingly, the initial reception state of the receiving node that gets the encoded packet may be expressed as:
s0＝{D(x1P1)}∪{D(x2P2)}∪L{D(xMPM)}；
therefore, the Integer Linear Programming (ILP) of the code selection problem based on CPTE values is summarized as:
max GPTE(st，t)}t＝0，
and obtaining an optimal coding solution through solving.
Referring to fig. 1-3, a typical "Cross" network coding (opportunistic network coding) rate control mechanism is provided;
first constructing a weighted graph G (V, E, f (C)) corresponding to the problem, thereby converting the search for a good package combination problem into a search for the largest weighted cluster in the graph; by separating the vertices in the graph one by one, a suitable coding solution will eventually be found.
In a coding structure with n coded streams, the transmission queue of a coding node contains | qiI from coded stream fiSo that the transmission queues Q of the coding nodes are shared
A packet, and Q ═ P1，P2，…，PK}; according to data packet PiNext hop node D (P)i) And node D (P)i) Decoded packet pool of (2) buffered packet set pl (D (P)i) The method of constructing the weighted graph G (V, E, ω) is as follows:
E＝{(v1，vj)|D(Pi)≠D(Pj)，F(Pi)≠F(Pj)，Pi∈pl(D(Pj))，Pj∈pl(D(Pi))}；
ω:C→R；
for each data packet PiE.g. Q, 1 is more than or equal to i and less than or equal to K, all correspond to a vertex v in the graphiE.g. V (G); an edge in the edge set E in graph G can be defined as follows: for any two data packets P in the coding node sending queue Qi，PjI ≠ j, packet PiNext hop node D (P)i) Different from the data packet PjNext hop node D (P)j) (ii) a Data packet PiThe associated stream F (P)i) Different from the data packet PjThe associated stream F (P)j) (ii) a Node D (P)j) The buffered data packet set pl (D (P) of the decoded packet pool ofj) Contains a data packet Pi(ii) a Likewise, node D (P)i) The buffered data packet set pl (D (P) of the decoded packet pool ofi) Contains a data packet Pj(ii) a Then there is an undirected edge between the 2 vertices in graph G corresponding to these two packets, since the blob in graph G is a subset of vertex set v (G), the subgraph derived from this subset is a complete graph, and the blob in graph G is a complete graph
Is a coding solution, ω is a weight function of the clique C; if we define n (g) as the set of next-hop nodes corresponding to vertices in the clique C, ω (C) ═ CPTE(s)t＝N(C)|t)|t＝0The value of ω (C) reflects the transmission efficiency of the encoded packet.
The code selection algorithm based on CPTE can be divided into two phases: the first stage is to search the graph G (V, E) for the maximum clique, i.e. the clique with the most number of vertices, and according to the definition of cliques, if the optimal coding solution corresponds to the clique C in the graph G (V, E) and the clique C contains a vertex V, the degree d (V) of which is less than the maximum degree of the vertex in the graph G (V, E), we will derive a sub-graph G from the graph G (V, E)vThe sub-graph GvConsists of vertex V and its neighbors and removes vertex V from graph G (V, E). Here, the set C is used to save the searched maximum clique result; if sub-graph GvIs greater than the number of vertices in set C, we search for subgraph GvAnd stores the searched results in the set CvIn, if set CvIf the number of vertices in (C) is greater than the number of vertices in the set C, then C is usedvThe search results in (1) replace the maximum clique results saved in (C), otherwise we keep set (C) unchanged and will continue searching until set of vertices (V), (G) is empty; if we cannot find a vertex V, so that his degree is smaller than the maximum degree of the vertices in the graph G (V, E), we search directly the maximum degree of the vertices in the graph G (V, E), and due to the limited number of vertices, the search process can be completed in a limited step, and after we obtain the maximum clique C in the first stage, we search the subset of vertices in the set C that can obtain the maximum CPTE value in the second stage.
Referring to fig. 3, the operation in the opportunistic network coding rate control is completed in two stages, in the first stage, based on the construction rules of all candidate original data packets and codes that can participate in coding, an undirected graph G (V, E) is constructed first and the maximum clique C in the graph G (V, E) is searched, any non-empty subset in the set C
Corresponding to one possible encoding solution; in the second stage, the arbitrary codes are decoded
For coding packet C1Selects a suitable transmission rate for each transmission within one hop range, we define a measurable metric called the Coded Packet Transmission Efficiency (CPTE) to measure the expected cumulative return, and search for coded packet C1An optimal rate control strategy; then, based on the specific CPTE value of each code packet, the code solution with the largest CPTE value is selected from all possible code solutions, so that the performance gain of opportunistic network coding can be optimized. Therefore, a reasonable coding solution and the corresponding optimal rate control strategy can be found.
The above embodiments do not limit the scope of the present invention, and those skilled in the art can make equivalent modifications and variations without departing from the overall concept of the present invention.
Claims (2)
1. A rate control method for improving wireless network coding gain is characterized in that the method comprises the following steps:
step S1, for transmission a degree of encoding of
Defining the state in the process of rate control during transmission as the receiving node set of the coded packet
One for each node in the subset that did not receive the encoded packet
Vector of bits
To indicate this subset, wherein,
when is coming into contact with
Representing a set of receiving nodes
To (1)
A receiving node has not received the encoded packet yet
Then, it represents the receiving node set
To (1)
A receiving node receives the encoded packet with a degree of encoding of
To the coded packet of (A), it has
A receiving node, therefore, has
A possible state;
step S2, when an encoding node is to send an encoded packet, it may select from the decision set
Selecting a transmission rate, wherein the number of the transmission rates contained in the set is the number of the types of the selectable decisions;
step S3, for transmission rate of
Time, node
Given a parameter (delivery rate of packets) of
The Bernoulli model of (1), then the slave state
Transition to State
The state transition probability of time can be calculated by the following formula:
step S4, defining the profit obtained in the process of state transition to be divided by the time cost brought by the transmission of the coding packet, defining the reward as the transmission efficiency (CPTE) of the coding packet, and carrying out the encoding packet
Which designates the receiving node as a set
If participating in an encoded data packet
Length of data packetIs composed of
，
Then the corresponding code packet
The length is equal to the length of the longest data packet in the data packet
(ii) a If in the decision stage
Taking decisions at all times
Then slave state
Transition to a State
Reporting of time
Comprises the following steps:
step S5, determining an optimization target, and optimizing a secondary decision stage
To the decision stage
General desiresCPTE value, calculated by the following formula:
at one is provided with
In the rate selection process of a decision stage, if
Then define
；
Step S6, determining an optimal decision, which is given by the following formula:
for the obtained optimal solution and the corresponding optimal decision, the following backward recursion algorithm is used:
a1, setting
And is
；
A2, let
Calculating
And
；
a3, if
Otherwise, go to A2 to continue the calculation.
2. The method as claimed in claim 1, wherein in step S6, the coding solution that can obtain the maximum CPTE value is selected from all possible coding solutions for use in the method
Representing nodes
Decoding the data packet set cached in the packet pool, optionally obtaining the encoding solution CA through the XOR operation and the corresponding packet set
Can be expressed as:
wherein,
accordingly, the initial reception state of the receiving node that gets the encoded packet may be expressed as:
integer linear programming of the code selection problem based on CPTE values
The result is:
and obtaining an optimal coding solution through solving.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103746775A (en) * | 2014-01-23 | 2014-04-23 | 电子科技大学 | Cache mechanism for improving wireless opportunity network coding gain |
| US20150049677A1 (en) * | 2013-08-14 | 2015-02-19 | National Cheng Kung University | Method and device for frame aggregation transmission of wireless network system |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150049677A1 (en) * | 2013-08-14 | 2015-02-19 | National Cheng Kung University | Method and device for frame aggregation transmission of wireless network system |
| CN103746775A (en) * | 2014-01-23 | 2014-04-23 | 电子科技大学 | Cache mechanism for improving wireless opportunity network coding gain |
Non-Patent Citations (1)
| Title |
|---|
| 刘青龙: "《提高无线机会性网络编码性能增益机制研究》", 《中国优秀博硕学位论文全文数据库(博士) 信息科技辑》 * |
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