The invention belongs to the field of digital communication and digital storage, and particularly relates to a method for transmitting additional information by using linear block codes.
In order to perform data scheduling and transmission efficiently, in addition to transmitting data information in a communication system, control information must also be transmitted. For the transmission of data information, we focus on the transmission rate, which is required to approach the channel capacity. However, for the transmission of control information, which comprises line signalling information, routing information, etc. and is usually short, it requires high reliability. In order to ensure a higher reliability of control messages, existing schemes use coding schemes with a lower code rate to independently transmit the control information. Therefore, it takes extra energy and bandwidth to transmit this information. Existing research mainly focuses on the ACK/NACK information fed back by the receiving section in the Hybrid Automatic Repeat reQuest (HARQ) system, and realizes the additional transmission of 1 bit of information by selecting different constellations or different coding schemes.
The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, to provide a method for transmitting additional information using linear block codes, and to embed shorter additional information into basic linear block codes without additional energy consumption and bandwidth.
In order to achieve the above objectives, the present invention adopts the following technical solutions:
This invention provides a method for transmitting additional information using linear block codes, characterized in that, comprises the following steps:
(1) using a linear block code C with a code length of n and an information bit length of k as a payload code, to superposition code an additional information sequence v=(v0, v1, . . . , vm-1) of length m into a codeword c=(c0, c1, . . . , cn-1) of length n, the encode method is specifically:
(2) decoding the additional information sequence, comprising or consisting of specifically:
(3) decoding the payload information sequence, comprising or consisting of specifically the following steps:
As a preferred embodiment, in the step (1), the linear block code C with a code length of n and an information bit length of k is an arbitrary type of linear block code encoder;
As a preferred embodiment, the characteristic metric function μ(i)=ƒC(y, s(i)) is a real-value function related to the linear block code C with input of a received sequence y and a sequence s(i), and represents a likelihood measure of the received sequence y related the coset s(i)⊕C.
As a preferred embodiment, the characteristic metric function ƒC uses the following calculation method:
where:
As a preferred embodiment, the method for calculating the Hamming weight W(i) of the syndrome of the linear block code is:
W(i)=WH(ŵ(i)·HT),
where H is a check matrix of the linear block code C, HT is the transpose of the matrix H, the multiplication “·” is about the matrix multiplication in the binary domain, WH(⋅) is the Hamming weight function, and output the number of non-zero elements in a sequence of arguments.
As a preferred embodiment, wherein the characteristic metric function ƒC uses the following calculation method:
As a preferred embodiment, the calculation of the likelihood function η(i) of the linear block code comprises the following methods:
where m is the number of rows in the check matrix H of the linear block code C, and HP is the index set of the nonzero element in the pth row of H.
As a preferred embodiment, the calculation of the likelihood function η(i) of the linear block code comprises the following methods: input {circumflex over (z)}(i) to a decoder D of the linear block code C, output the decoding sequence as ĉ(i)=(ĉ0(i), ĉ1(i), . . . , ĉn-1(i)), and then calculate s(i)⊕ĉ(i) as a log- likelihood function of a transmission sequence:
where the linear block code C of the decoder D is an arbitrary type of soft input decoder.
As a preferred embodiment, in the step (3.1), the interference of the superposition coding ŝ=R({circumflex over (v)}) is removed from the received sequence y, and the corresponding received sequence {tilde over (y)} of the linear block code C related to the payload information is obtained, which refers to calculating soft information of the j th component {tilde over (y)}j of {tilde over (y)} with:
P({tilde over (y)}j|wj)=P(yj|cj=wj⊕ŝj),
where ŝj is the j th component of ŝ, where 0≤j≤n−1.
As a preferred embodiment, in the step (3.2), the basic linear block code decoder C refers to an arbitrary type of linear block code decoder.
Compared with the prior art, the present invention has the following advantages and beneficial effects:
In the present invention, the payload information sequence is encoded using the linear code as the basic code, and the additional information is encoded by the sequence selector and superposition coded on the basic linear block code. This enables the transmission of additional information sequences without generating additional transmission energy and bandwidth overhead. When decoding the additional information, since the additional information sequence has fewer bits, it can be decoded by traversal searching, which has higher reliability. By removing the influence of the superposition coding of the additional information sequence and then decoding the basic information sequence with linear block codes, when the signal-to-noise is relatively high, the effect of additional bit transmission on the decoding performance of the basic linear group is negligible.
The present method allows extra bits of information to be transmitted using superposition coding, which requires neither extra transmission energy nor extra bandwidth. This method can be used to provide reliable transmissions for 5G/B5G and IoT (Internet of Things) services such as autonomous vehicles, sensing networks, and remote surgery. For example, this method can be used in collaborative communication among the UAVs (Unmanned Aerial Vehicles) in their sensing networks. In this case, UAV identity information can be transmitted as additional information along with sensing data (i.e., the payload information), and the identity information can be read without decoding the entire data block of a transmission. The complexity of processing the transmitted information can thereby be reduced.
A system which uses this method can consist of modules, namely a payload encoder, a superposition (additional information) encoder, an additional information decoder, and a payload decoder. The payload encoder and superposition encoder can be present as software, firmware, or hardware in a system for transmitting digital information, which can be over a wired connection, a wireless connection, or a combination of these. The additional information decoder and payload decoder can be present as software, firmware, or hardware in a system for receiving digital information, which can be over a wired connection, a wireless connection, or a combination of these.
The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments.
The term “payload information” refers to a portion of a digital information transmission that comprises data.
The term “additional information” refers to a portion of a digital information transmission that consists of metadata relating to the payload information in the transmission.
The term “data” refers to digital information which represents sensor measurements, communications in human or machine language (in visual, audible, and other form that can be sensed by humans or machines), or information resulting from processing by a processor. Data can include metadata as defined herein.
The term “metadata” refers to digital information that describes or provides further information about data, in particular data of the payload information in a transmission. Metadata can be external descriptive metadata, i.e. information about particular data in the payload information, such as the location of such particular data. Alternatively, metadata can be internal descriptive metadata, i.e. self-contained information which relates to the payload information.
The term “comprise” and variations of the term, such as “comprising” and “comprises,” are not intended to exclude other additives, components, integers or steps. The terms “a,” “an,” and “the” and similar referents used herein are to be construed to cover both the singular and the plural unless their usage in context indicates otherwise.
The present invention will be described in further detail below with reference to examples and drawings, but the embodiments of the present invention are not limited thereto.
As shown in
(1) based on a linear block code C with a code length of n and an information bit length of k as a payload code, superposition code an additional information sequence v=(v0, v1, . . . , vm-1) of length m into a codeword c=(c0, c1, . . . , cn-1) of length n, the encoding method is specifically:
(2) decoding the additional information sequence, comprising or consisting of specifically:
The characteristic metric function μ(i)=ƒC(y, s(i)) is a real-value function related to the linear block code C with input of a received sequence y and a sequence s(i) represents a likelihood measure of the received sequence y related the coset s(i)⊕C.
(3) decoding the payload information sequence, comprising or consisting of specifically the following steps:
The solution of the present invention is further elaborated below in conjunction with specific applications:
The (3,6)-regular LDPC code constructed with PEG (progressive edge growth) method with a code length of 8064 and an information bit length of 4032 is used as the basic code, which is modulated by BPSK (binary phase-shift keying) and is transmitted in a AWGN (additive white Gaussian noise) channel. The length of the additional information sequence is set to m=5 and m=10 respectively. That is to say, each sequence with a code length of 8064 contains 4032 bits of payload information encoded by an LDPC code and additional information of 5 or 10 bits of random superposition code. When coding, as shown in
This embodiment is implemented by means of hard decision, specifically:
The characteristic metric function ƒC uses the following calculation method:
Calculate a hard decision sequence r from the received sequence y, obtain the sequence ŵ(i) by removing an interference of the sequence s(i) from r, then calculate the Hamming weight W(i) of the syndrome of the linear block code with respect to ŵ(i), and finally use n-k-W(i) as the output of the function ƒC;
where:
P(yj|cj) represents the channel transition probability with respect to input cj and output yj;
The method for calculating the Hamming weight W(i) of the syndrome of the linear block code is:
W(i)=WH(ŵ(i)·HT),
where H is a check matrix of the linear block code C, HT is the transpose of the matrix H, the multiplication “·” is about the matrix multiplication in the binary domain, WH(⋅) is the Hamming weight function, and output the number of non-zero elements in a sequence of arguments.
As shown in
As shown in
Except for the following technical features, other technical solutions of this Example 2 are the same as those of Example 1, that is, this Example 2 is implemented by means of soft decision, specifically:
The characteristic metric function ƒC comprises the following calculation method:
The calculation of the likelihood function η(i) of the linear block code comprises the following methods:
where m is the number of rows in the check matrix H of the linear block code C, and HP is the index set of the nonzero element in the p th row of H.
The calculation method of Example 2 (i.e., soft decision) has better performance of frame error rate than hard decision. The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited by the above examples. Any other changes, modifications, substitutions, combinations, simplifications, without departing from the spirit and principle of the present invention, should all be equivalent replacement methods, which are all included in the protection scope of the present invention. The examples set forth herein are provided to illustrate certain concepts of the disclosure.
Aspects of the present disclosure have been described above with reference to schematic flowchart diagrams and/or schematic block diagrams of methods, apparatus, systems, and computer program products according to embodiments of the disclosure. It will be understood that each block of the schematic flowchart diagrams and/or schematic block diagrams, and combinations of blocks in the schematic flowchart diagrams and/or schematic block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a computer or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor or other programmable data processing apparatus, create means for implementing the functions and/or acts specified in the schematic flowchart diagrams and/or schematic block diagrams block or blocks.
It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more blocks, or portions thereof, of the illustrated figures. Although various arrow types and line types may be employed in the flowchart and/or block diagrams, they are understood not to limit the scope of the corresponding embodiments.
The subject matter described herein may be formed by an apparatus controlled by hardware, software, firmware, or any combination thereof. As such, the terms module, encorder, decorder, and the like as used herein may refer to hardware, which may also include software and/or firmware components, for implementing the feature being described. In one example implementation, the subject matter described herein may be implemented using a computer readable or machine readable medium having stored thereon computer executable instructions that when executed by a computer (e.g., a processor) control the computer to perform the functionality described herein. Examples of machine readable media suitable for implementing the subject matter described herein include non-transitory computer-readable media, such as disk memory devices, chip memory devices, programmable logic devices, and application specific integrated circuits. In addition, a machine readable medium that implements the subject matter described herein may be located on a single device or computing platform or may be distributed across multiple devices or computing platforms.
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