CN116669016A - Data security transmission method of health monitoring system based on rate splitting - Google Patents

Data security transmission method of health monitoring system based on rate splitting Download PDF

Info

Publication number
CN116669016A
CN116669016A CN202310612676.5A CN202310612676A CN116669016A CN 116669016 A CN116669016 A CN 116669016A CN 202310612676 A CN202310612676 A CN 202310612676A CN 116669016 A CN116669016 A CN 116669016A
Authority
CN
China
Prior art keywords
base station
rate
transmission
data
patient
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310612676.5A
Other languages
Chinese (zh)
Inventor
周家思
左海维
刘付龙
张宇桐
吴加旺
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xuzhou Medical University
Original Assignee
Xuzhou Medical University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xuzhou Medical University filed Critical Xuzhou Medical University
Priority to CN202310612676.5A priority Critical patent/CN116669016A/en
Publication of CN116669016A publication Critical patent/CN116669016A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/03—Protecting confidentiality, e.g. by encryption
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/046—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account
    • H04B7/0465—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account taking power constraints at power amplifier or emission constraints, e.g. constant modulus, into account
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Health & Medical Sciences (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a data security transmission method of a health monitoring system based on rate splitting, which relates to the technical field of data security transmission, and comprises the following steps: the uplink speed division multiple access technology and the serial interference elimination technology are utilized to realize flexible management of co-channel interference, and the data transmission speed is improved; the base station is used as an interference device to transmit artificial noise to inhibit decoding capability of eavesdropping users in the monitoring system, so that information leakage is avoided; constructing an accurate proxy function for the non-convex secret transmission rate based on the idea of substitution optimization, and converting the design problem of the non-convex precoding matrix and the artificial noise covariance matrix into an iterative optimization problem; an alternate optimization algorithm is provided to maximize the secret transmission rate of legal users in the system and enhance the safety transmission performance of the health monitoring system.

Description

Data security transmission method of health monitoring system based on rate splitting
Technical Field
The invention relates to the technical field of data safety transmission, in particular to a data safety transmission method of a health monitoring system based on rate splitting.
Background
Health monitoring systems based on wireless body area networks have become one of the important actions to actively respond to health aging. The monitoring system utilizes the miniature sensor arranged in or on the body surface of the patient to collect and analyze physiological data on the premise of not affecting the normal life of the patient. Through uninterrupted data acquisition, the monitoring system can timely provide real-time health status of the patient, and assist medical staff in formulating a more accurate medical intervention scheme.
However, as the number of chronic disease patients increases, severe co-channel interference is one of the major bottlenecks faced in implementing a healthcare system. To reduce co-channel interference, patient monitoring devices must follow a specific multiple access technique in order to reasonably allocate the time and manner of data upload. Current multiple access techniques mainly include orthogonal multiple access (Orthogonal Multiple Access, OMA), spatial division multiple access (Space Division Multiple Access, SDMA) and Non-orthogonal multiple access (Non-OMA, NOMA) techniques. In particular, OMA serves only a single user at the same time-frequency resource block to avoid co-channel interference, but limited spectrum resources result in the technology not being able to support large-scale patients while accessing the healthcare system. SDMA treats all non-target signals as interference and suppresses co-channel interference with the diversity gain of multiple antennas. However, when the number of users served by the monitoring system exceeds the spatial degree of freedom that the transmitting antenna can support, the transmission rate of the users will reach saturation. Even though users can increase the transmission power without limit, the transmission rate tends to be a constant value, and limited transmission rates cannot support the high-rate traffic demands. Compared to OMA and SDMA, NOMA improves the transmission performance of the system by attenuating co-channel interference using a serial interference cancellation technique. However, this technique is extremely strict in terms of channel conditions for users, and is only suitable for a scenario where channels between users are sufficiently aligned and there is a large difference in channel strength. Therefore, none of the three multiple access technologies can meet the requirements of high transmission rate and high access density of the health monitoring system at the same time.
As a novel non-orthogonal multiple access technology, the uplink Rate Splitting (RS) can meet the high transmission Rate requirement of large-scale monitoring equipment by reasonably setting the information Splitting proportion and decoding sequence. By adjusting the information splitting ratio, the RS generalizes SDMA and NOMA technologies as special cases. Specifically, the uplink RS splits the data collected by each monitoring device into two parts and encodes the two parts into two independent information streams. The base station then decodes the received information stream in turn using a serial interference cancellation technique and reconstructs the original acquired data. Through the data splitting and serial interference elimination technology, the uplink RS can flexibly manage co-channel interference, so that the monitoring system realizes high transmission rate under the condition of large-scale equipment access.
Furthermore, since disease information and physiological data of patients are extremely private, it is very important to ensure data transmission security of the health monitoring system. However, the broadcast nature of the wireless channel results in the transmitted medical data being extremely vulnerable to eavesdropping by an unauthorized user. The physical layer safely utilizes the randomness of the wireless channel to design a transmission scheme, and can ensure the safe transmission of information under the condition of not needing any secret key. Compared with the traditional key encryption method, the physical layer security technology remarkably reduces signaling overhead, so that the physical layer security technology becomes a research hotspot for guaranteeing information security transmission.
In 2021, xuewan Zhang et al published "Sparse Vector Coding-Based Multi-Carrier NOMA for In-Home Health Networks" on IEEE Journal on Selected Areas in Communications propose a health monitoring system Based on NOMA technology, and analyze a closed solution of error rate and reachable rate of the monitoring system, but the model is only suitable for a scenario where channels are sufficiently aligned, and cannot guarantee the safety of information transmission.
2021, junaid Ahmed et al, in "On the Physical Layer Security of Federated Learning based IoMT Networks" published on IEEE Journal Biomedical and Health Informatics, proposed a federal learning-based resource allocation algorithm for healthcare systems to enhance the security of medical data, but the multiple access technique employed was unable to support large-scale patients while accessing the monitoring system.
In 2022, wen Wang et al in "Robust Design for STAR-RIS Secured Internet of Medical Things" published in IEEE ICC 2022 Workshop on E-health Security for Further G, use an intelligent reflection surface technology to enhance the security of information transmission, and propose a rotation optimization algorithm to design precoding vectors based on a continuous convex approximation method, so as to improve the energy efficiency of a health monitoring system. However, the multiple access technology adopted in the paper cannot meet the transmission rate requirement of medical data in a large connection scenario.
In 2023, hamed Basami et al, "Large-scale rate-splitting multiple access in uplink UAV networks: effective secrecy throughput maximization under limited feedback channel" published in IEEE Transactions on Vehicular Technology designed an uplink RS-based physical layer secure transmission method to enhance the security of data transmission by an unmanned aerial vehicle, but the scheme did not design the decoding capability of artificial noise to suppress eavesdroppers. Therefore, when a legal user and an eavesdropping user in the system have very similar channel vectors or there are many eavesdropping users in the system, the system will not completely avoid information leakage.
All four health monitoring systems cannot ensure the safety and high-speed transmission of medical data when large-scale monitoring equipment is accessed into the system.
Disclosure of Invention
The invention aims to solve the technical problem of providing a data safety transmission method of a health monitoring system based on rate splitting aiming at the defects of the background technology, and the method guarantees the privacy of medical data by using a physical layer safety transmission scheme based on cooperation of an uplink RS and a base station, and simultaneously provides a rotation optimization algorithm for realizing accurate allocation of wireless resources so as to improve the safety transmission performance of the health monitoring system.
The invention adopts the following technical scheme for solving the technical problems:
a data security transmission method of a health monitoring system based on rate splitting comprises the health monitoring system, wherein the health monitoring system comprises a data transmission unit and a data transmission unitThe health monitoring system comprises K more than or equal to 1 patient and L eavesdropping users, wherein the monitoring equipment of the patient is used for safely uploading acquired medical data to a base station for further analysis and processing; marking a set of patients and eavesdropping users as respectively and />In the health monitoring system, a base station and a patient monitoring device are respectively provided with T b>1 and Tu >1 transmission antenna; the base station and the eavesdropping user are respectively provided with A b>1 and Ae >1 receiving antenna; the channel matrix from the kth patient to the base station and the ith eavesdropping user is marked +.> and />The channel matrix from the base station to the first eavesdropping user is marked +.>Since both the base station and the patient monitoring device are equipped with multiple antennas, the kth patient can transmit an N-dimensional data vector>Wherein N is less than or equal to min (A) b ，T u ) The method comprises the steps of carrying out a first treatment on the surface of the In order to increase the data transmission rate, the monitoring system uploads the data by adopting a rate splitting multiple access technology, and the coding process of the rate splitting multiple access technology is as follows:
step 1, each data in the kth patient N-dimensional data vectorSplit into two parts, i.e.)> and />Where j e {1,., N };
step 2, the monitoring equipment willCoding as-> wherein />
Step 3, N-dimensional data vectorIn the course of->After linear precoding, the monitoring device stacks the two information streams and uploads the two information streams to the base station.
According to the encoding process of rate splitting, the signal transmitted by the kth patient can be expressed as x k ＝W k，1 x k，1 +W k， 2 x k，2 To ensure the safety of information transmission, the artificial noise x emitted by the base station an From the following componentsLinear precoding is performed, so the signal received by the receiver is:
wherein ,is additive white gaussian noise; in equation (1), when +.>When A is m ＝A e The method comprises the steps of carrying out a first treatment on the surface of the After receiving the signal, the receiver decodes the data stream in sequence by utilizing a serial interference elimination technology; the signal-to-interference-and-noise ratio of the receiver m to decode the nth data stream transmitted by the kth patient is:
wherein ,is the interference power, expressed as:
in equation (3), when m=b, δ m =0, otherwise δ m ＝1；π i，k >π k，n Represented in information stream x k，n The decoded information stream thereafter; the decoding rate obtained according to shannon's formula is:
based on this, according to the secret rate calculation method of physical layer security, secret rate can be obtainedThe expression of (2) is
Wherein the symbol [ x ]] + ＝max(x，0)。
In order to improve the safety transmission performance of medical data, a precoding and artificial noise covariance matrix is jointly designed to maximize the confidentiality rate of the health monitoring system; the optimization problem of modeling is specifically as follows:
wherein ,Pu and Pth The maximum transmission power thresholds of the patient monitoring device and the base station, respectively.
As a further preferable scheme of the data safety transmission method of the health monitoring system based on rate splitting, three constraint conditions of the modeling optimization problem are respectively transmission power constraint of patient monitoring equipment, transmission power constraint of a base station and transmission safety constraint of all data streams in sequence.
As a further preferable scheme of the data security transmission method of the health monitoring system based on rate splitting, the invention adopts a rotation optimization algorithm to solve the optimal precoding and artificial noise covariance matrix so as to maximize the confidentiality rate, and the solving steps of the rotation optimization algorithm are as follows:
1) To eliminate the product form between covariance matrices, a semi-positive definite matrix is introducedAndbased on the introduced semi-positive definite matrix, the secret rate can be converted into
wherein
2) To overcome non-smoothness, auxiliary variables are introducedRejecting maximum and minimum symbols, reconstructing formula i 6) to be
(10.4)Tr(Q an )≤P th ，
(10.6)Rank(Q an )＝min(T b ，A e )，
wherein ,containing the variable { Q k，n ，Q an -a }; since Rank (Q) needs to be satisfied after introducing the semi-positive definite matrix x )≤Rank(W x ) Therefore, the matrix rank limits (10.5) and (10.6) are increased, the +.> and />The method is as follows
3) The following axiom 1 is proposed to construct an accurate proxy function to convert the problem (10) into a rotation optimization problem;
wherein, lemma 1: by introducing the function f (T) = -Tr (Tx) +logdet (T) +n, whereinAnd X > 0, can be obtained
And the optimal solution on the right side of the equation is T * ＝X -1 ；
And (3) proving: since f (T) is a concave function with respect to T, by calculating a first order partial derivativeT capable of solving maximization function f (T) * I.e. t=x -1 The method comprises the steps of carrying out a first treatment on the surface of the Will T * Substituting the function f (T) to obtain f (T) * ) = -log|x|, so axiom 1 holds;
applying lemma 1 to equation (11)Is set to +.>The available substitution functions are:
wherein ,is an introduced auxiliary variable; according to lemma 1->The substitution function of the second term can be expressed as:
in connection with equations (11), (13) and (14), problem (10) can be reconstructed as:
(10.3)，(10.4)，(10.5)，(10.6)，
wherein The method is as follows
4) Dividing the variable in question (15) into Q 1 ＝{Q k，n ，Q an} and Under the condition of neglecting the limits (10.5) and (10.6), a round-robin optimization algorithm loop iteration optimization covariance matrix is provided>And auxiliary variable +.> wherein , and />Respectively solving by using a convex optimization tool box and a closed solution; auxiliary variable->Closed form solution of (2)
5) If it is found thatThe constraints (10.5) and (10.6) of the matrix rank can be met, then the eigenvalue decomposition method is used to obtain the optimal precoding and artificial noise covariance matrix, otherwise the randomization and scaling method is used to obtain the suboptimal precoding and artificial noise covariance matrix.
As a further preferable scheme of the data security transmission method of the health monitoring system based on rate splitting, the rotation optimization algorithm is specifically as follows:
a) Initializing: setting up initiallyi=1 and the maximum tolerated error ζ;
b) While does not converge execution;
c) Calculating an optimum according to equation (17)
d) FixingSolving the problem (15) using a convex optimization tool box, outputting an optimal +.>
e) Updating i=i+1;
f)End while；
g) Output ofCalculation of W k，n and Wan ；
h) Computing suboptimal solutions for privacy rates
Compared with the prior art, the technical scheme provided by the invention has the following technical effects:
the invention relates to a data safety transmission method of a health monitoring system based on rate splitting, which guarantees the privacy of medical data by using a physical layer safety transmission scheme based on the cooperation of an uplink RS and a base station; meanwhile, the patent provides a rotation optimization algorithm for realizing the accurate allocation of wireless resources so as to improve the safety transmission performance of the health monitoring system.
Drawings
FIG. 1 is a schematic diagram of data transmission and eavesdropping of a healthcare system;
FIG. 2 is a graph showing the trend of the secret rate performance of the proposed scheme and four reference transmission schemes according to the increase of the transmitting power of the patient monitoring device;
FIG. 3 is a graph showing the change of the secret rate with the transmission power threshold of the base station;
fig. 4 is a schematic diagram of the change of the privacy rate along with the number of patients served by a time-frequency resource block.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the accompanying drawings:
in order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. 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, a schematic diagram of data transmission and eavesdropping of the healthcare system is shown. The health monitoring system designed by the patent comprises K more than or equal to 1 patient and L eavesdropping users, wherein the patient aims to safely upload acquired medical data to a base station for further analysis and processing.
To ensure the privacy of medical data, this patent devised a cooperative transmission mechanism, i.e. the base station acts as an jammer to transmit artificial noise to impair the decoding ability of eavesdropping users. The patient and eavesdropping user sets are labeled as respectively and />In the designed health monitoring system, a base station and a patient monitoring device are respectively provided with T b>1 and Tu >1 transmission antenna; the base station and the eavesdropping user are respectively provided with A b>1 and Ae >1 receiving antenna. The channel matrix from the kth patient to the base station and the ith eavesdropping user are marked +.> and />Similarly, the channel matrix from the base station to the first eavesdropping user is marked +.>
Since the base station and the patient monitoring device are equipped with multiple antennas, the kth patient can transmit an N-dimensional data vectorWherein N is less than or equal to min (A) b ，T u ). In order to improve the transmission rate, the patent designs a data uploading scheme based on RS, which is specifically as follows: first, the kth patient N-dimension data vectorEach data of->Split into two parts, i.e.)> and />Where j ε {1, once again, N. Second, the monitoring device will->Coding as-> wherein />Then, N-dimensional data vector +.>In the course of->And after linear precoding, the two information streams are overlapped and uploaded to the base station. Thus, the signal transmitted by the kth patient can be represented as x k ＝W k，1 x k，1 +W k，2 x k，2 . Similarly, the artificial noise x emitted by the base station an By->Linear precoding is performed. From this, the signals received by the receiver (base station and eavesdropping user) are:
wherein Is additive white gaussian noise. In equation (1), when +.>When A is m ＝A e . After receiving the signal, the receiver decodes the data stream in turn using a serial interference cancellation technique. In the designed transmission scheme, the artificial noise is transmitted by the base station, so the base station can decode and reject the artificial noise by using the SIC, but the eavesdropper cannot reject the artificial noise. From this, the signal-to-interference-and-noise ratio of the receiver m to decode the nth data stream transmitted by the kth patient is:
wherein Is the interference power, and can be expressed as:
in equation (3), δ when m=b, since the base station is not subject to interference of artificial noise m =0, otherwise δ m ＝1。π i，j >π k，n Represented in information stream x k，n And then decoded. The decoding rate obtained according to shannon's formula is:
based on this, according to the secret rate calculation method of physical layer security, secret rate can be obtainedThe expression of (2) is
Wherein the symbol [ x ]] + ＝max(x，0)。
In order to improve the safety transmission performance of medical data, the patent jointly designs a precoding and artificial noise covariance matrix to maximize the confidentiality rate of the health monitoring system. The optimization problem of modeling is specifically as follows:
wherein Pu and Pth The maximum transmission power thresholds of the patient monitoring device and the base station, respectively. The three constraints of the problem (6) are, in turn, the transmission power constraint of the patient monitoring device, the transmission power constraint of the base station, and the transmission security constraint for ensuring all data streams, respectively.
The objective function of the problem (6) is the difference of two logarithmic functions, and each logarithmic function is a complex partial function, so the problem (6) has non-convexity and non-smoothness, and is difficult to directly solve. The patent designs a rotation optimization algorithm to solve the optimal precoding and artificial noise covariance matrix based on the alternative optimization idea so as to maximize the confidentiality rate. The solving steps of the rotation optimization algorithm are as follows:
first, to eliminate the product form between covariance matrices, a semi-positive definite matrix is introducedAndbased on the introduced semi-positive definite matrix, the secret rate can be converted into
wherein
Second, to overcome non-smoothness, an auxiliary variable is introducedRejecting maximum and minimum symbols, reconstructing problem (6) as:
(10.4)Tr(Q an )≤P th ，
(10.6)Rank(Q an )＝min(T b ，A e )，
wherein Containing the variable { Q k，n ，Q an }. (10.5) and (10.6) increase the limit of matrix rank becauseAfter the introduction of the semi-positive definite matrix, the Rank (Q) x )≤Rank(W x ). Problem (10)> and />The method is as follows
Then, the following axiom 1 is proposed to construct a precise proxy function, converting the problem (10) into a rotation optimization problem.
Lemma 1: by introducing the function f (T) = -Tr (TX) +logdet (T) +n, whereinAnd X > 0, can be obtained
And the optimal solution on the right side of the equation is T * ＝X -1 。
And (3) proving: since f (T) is a concave function with respect to T, by calculating a first order partial derivativeT of the maximization function f (T) can be solved * T, i.e * ＝X -1 . Will T * Substituting the function f (T) to obtain f (T) * ) = -log|x|, so the axiom 1 holds.
Applying lemma 1 to equation (11)Is set to +.>The available substitution functions are:
wherein Is an auxiliary variable introduced. Similarly, a->The substitution function of the second term can be expressed as:
in connection with equations (11), (13) and (14), problem (10) can be reconstructed as:
(10.3)，(10.4)，(10.5)，(10.6)，
wherein Is that
Then, the variables in the problem (15) are divided into and />Under the condition of neglecting the limits (10.5) and (10.6), a round-robin optimization algorithm loop iteration optimization covariance matrix is provided>And auxiliary variable +.> wherein /> and />And respectively solving by using a convex optimization tool box and a closed solution. Auxiliary variable->Closed form solution of (2)
Finally, if it is found thatThe constraints (10.5) and (10.6) of the matrix rank can be met, then the eigenvalue decomposition method is used to obtain the optimal precoding and artificial noise covariance matrix, otherwise the randomization and scaling method is used to obtain the suboptimal precoding and artificial noise covariance matrix.
Algorithm 1 summarizes the specific flow of the rotation optimization algorithm proposed in this patent.
a) Initializing: setting up initiallyi=1 and the maximum tolerated error ζ;
b) While does not converge execution;
c) Calculating an optimum according to equation (17)
d) FixingSolving the problem (15) using a convex optimization tool box, outputting an optimal +.>
e) Updating i=i+1;
f)End while；
g) Output ofCalculation of W k，n and Wan ；
h) Computing suboptimal solutions for privacy rates
Specific examples are as follows:
the simulation test parameters of the health monitoring system are as follows: the simulation test area is a circle with a radius of 100 meters, the base station is placed at the center of the circle, and 2 patients and 2 eavesdropping users are independently and randomly distributed in the circle. The base station and each patient's monitoring device are equipped with 2 transmit antennas and the base station and eavesdropping user are equipped with 2 receive antennas. The maximum transmission power for the patient and base station is 15dBm and 20dBm, respectively. The large-scale path loss of the Rayleigh channel is 128.1+37.6log 10 (d) Where d represents the distance in kilometers between the transmitter and the receiver. The background noise was-102 dBm.
Fig. 2 is a graph showing the trend of the privacy rate performance of the proposed scheme and the four reference transmission schemes as the patient monitoring device transmit power increases. The results show that the transmission scheme proposed by the present patent has three advantages over the four reference schemes.
(1) Compared with a transmission scheme without the assistance of a base station, the base station transmission artificial noise scheme provided by the patent achieves more than twice performance gain, which indicates that the artificial noise can effectively inhibit the decoding capability of eavesdropping users;
(2) Compared with space division multiple access and non-orthogonal multiple access schemes, the confidentiality rate of the uplink rate splitting scheme provided by the patent is respectively improved by 1.4bps/Hz and 0.7bps/Hz;
(3) The rotation optimization algorithm provided by the patent is superior to the traditional continuous convex approximation algorithm.
Fig. 3 simulates the change of the privacy rate with the base station transmission power threshold. Simulation results show that increasing the transmission power of the base station is beneficial to improving the security rate. However, when the transmission power of the base station exceeds 25dBm, the change in privacy rate will flatten out, mainly because the artificial noise power transmitted by the base station is already sufficient to suppress eavesdropping by eavesdropping users.
Fig. 4 simulates the variation of privacy rate along with the number of patients served by a time-frequency resource block. Simulation results show that the transmission scheme provided by the patent is superior to four reference schemes. In addition, the privacy rate of the proposed algorithm decreases more slowly as the number of patients increases. It is worth noting that when the number of patients exceeds 4, the transmission scheme without the assistance of the base station cannot guarantee the safe transmission of medical information, which again verifies the superiority of the transmission scheme proposed by the present patent.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereto, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the present invention. The embodiments of the present invention have been described in detail, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the spirit of the present invention.

Claims (4)

1. A data security transmission method of a health monitoring system based on rate splitting is characterized by comprising the following steps: the system comprises a health monitoring system, wherein the health monitoring system comprises K is more than or equal to 1 patient and L eavesdropping users, and monitoring equipment of the patient safely uploads acquired medical data to a base station for further analysis and processing; the patient and eavesdropping user sets are labeled as respectively and />In the health monitoring system, a base station and a patient monitoring device are respectively provided with T b＞1 and Tu More than 1 transmission antenna; the base station and the eavesdropping user are respectively provided with A b＞1 and Ae > 1 receive antenna; the channel matrix from the kth patient to the base station and the ith eavesdropping user are marked +.> and />The channel matrix from the base station to the first eavesdropping user is marked +.>Since both the base station and the patient monitoring device are equipped with multiple antennas, the kth patient can transmit an N-dimensional data vector>Wherein N is less than or equal to min (A) b ，T u ) The method comprises the steps of carrying out a first treatment on the surface of the To increase the data transmission rate, the monitoring system adopts a fast speedThe rate splitting multiple access technique uploads data, and the encoding process of the rate splitting multiple access technique is as follows:
step 1, each data in the kth patient N-dimensional data vectorSplit into two parts, i.e.)> and />Where j e {1,., N };
step 2, the monitoring equipment willCoding as-> wherein />
Step 3, N-dimensional data vectorIn the course of->After linear precoding, the monitoring device stacks the two information streams and uploads the two information streams to the base station;
according to the encoding process of rate splitting, the signal transmitted by the kth patient can be expressed as x k ＝W k，1 x k，1 +W k，2 x k，2 The method comprises the steps of carrying out a first treatment on the surface of the To ensure the safety of information transmission, the artificial noise x emitted by the base station an From the following componentsPerforming linear precoding; the signal received by the receiver is:
wherein ,is additive white gaussian noise; in equation (1), when +.>When A is m ＝A e The method comprises the steps of carrying out a first treatment on the surface of the After receiving the signal, the receiver decodes the data stream in sequence by utilizing a serial interference elimination technology; the signal-to-interference-and-noise ratio of the receiver m to decode the nth data stream transmitted by the kth patient is:
wherein ,is the interference power, expressed as:
in equation (3), when m=b, δ m =0, otherwise δ m ＝1；π i，j ＞π k，n Represented in information stream x k，n The decoded information stream thereafter; the decoding rate obtained according to shannon's formula is:
based on this, the privacy speed according to the physical layer securityRate calculation method, secret rate can be obtainedThe expression of (2) is
Wherein the symbol [ x ]] + ＝max(x，0)。
In order to improve the safety transmission performance of medical data, a precoding and artificial noise covariance matrix is jointly designed to maximize the confidentiality rate of the health monitoring system; the optimization problem of modeling is specifically as follows:
wherein ,Pu and Pth The maximum transmission power thresholds of the patient monitoring device and the base station, respectively.
2. The method for securely transmitting data in a healthcare system based on rate splitting according to claim 1, wherein: the three limiting conditions of the modeling optimization problem are respectively a transmission power constraint of the patient monitoring device, a transmission power constraint of the base station and a transmission safety constraint for ensuring all data streams in sequence.
3. The method for securely transmitting data in a healthcare system based on rate splitting according to claim 2, wherein: the optimal precoding and artificial noise covariance matrix is solved by adopting a rotation optimization algorithm to maximize the confidentiality rate, and the solving steps of the rotation optimization algorithm are as follows:
1) To eliminate the product form between covariance matrices, a semi-positive definite matrix is introducedAndbased on the introduced semi-positive definite matrix, the secret rate can be converted into
wherein
2) To overcome non-smoothness, auxiliary variables are introducedRejecting maximum and minimum symbols, reconstructing problem (6) as
s.t.(10.1)
(10.2)
(10.3)
(10.4)Tr(Q an )≤P th ，
(10.5)
(10.6)Rank(Q an )＝min(T b ，A e )，
wherein ,containing the variable { Q k，n ，Q an -a }; since Rank (Q) needs to be satisfied after introducing the semi-positive definite matrix x )≤Rank(W x ) Therefore, the matrix rank limits (10.5) and (10.6) are increased, the +.> and />The method is as follows
3) The following axiom 1 is proposed to construct an accurate proxy function to convert the problem (10) into a rotation optimization problem;
wherein, lemma 1: by introducing the function f (T) = -Tr (TX) +logdet (T) +n, wherein and />Is available in the form of
And the optimal solution on the right side of the equation is T * ＝X -1 ；
And (3) proving: since f (T) is a concave function with respect to T, by calculating a first order partial derivativeT capable of solving maximization function f (T) * T, i.e * ＝X -1 The method comprises the steps of carrying out a first treatment on the surface of the Will T * Substituting the function f (T) to obtain f (T) = -log|x|, so that the argument 1 holds;
applying lemma 1 to equation (11)Is set to +.>The available substitution functions are:
wherein ,is an introduced auxiliary variable; by means of the lemma 1, & lt>The substitution function of the second term can be expressed as:
in connection with equations (11), (13) and (14), problem (10) can be reconstructed as:
(10.3)，(10.4)，(10.5)，(10.6)，
wherein The following is shown
4) Dividing the variables in question (15) into and />Under the condition of neglecting the limits (10.5) and (10.6), a round-robin optimization algorithm loop iteration optimization covariance matrix is provided>And auxiliary variable +.> wherein ,/> and />Respectively solving by using a convex optimization tool box and a closed solution; auxiliary variable->Closed form solution of (2)
5) If it is found thatThe constraints (10.5) and (10.6) of the matrix rank can be met, then the eigenvalue decomposition method is used to obtain the optimal precoding and artificial noise covariance matrix, otherwise the randomization and scaling method is used to obtain the suboptimal precoding and artificial noise covariance matrix.
4. The method for securely transmitting data in a healthcare system based on rate splitting according to claim 3, wherein: the rotation optimization algorithm is specifically as follows:
a) Initializing: setting up initiallyi=1 and the maximum tolerated error ζ;
b) While does not converge execution;
c) Calculating an optimum according to equation (17)
d) FixingSolving the problem (15) using a convex optimization tool box, outputting an optimal +.>
e) Updating i=i+1;
f)End while；
g) Output ofCalculation of W k，n and Wan ；
h) Computing suboptimal solutions for privacy rates
CN202310612676.5A 2023-05-25 2023-05-25 Data security transmission method of health monitoring system based on rate splitting Pending CN116669016A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310612676.5A CN116669016A (en) 2023-05-25 2023-05-25 Data security transmission method of health monitoring system based on rate splitting

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310612676.5A CN116669016A (en) 2023-05-25 2023-05-25 Data security transmission method of health monitoring system based on rate splitting

Publications (1)

Publication Number Publication Date
CN116669016A true CN116669016A (en) 2023-08-29

Family

ID=87721798

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310612676.5A Pending CN116669016A (en) 2023-05-25 2023-05-25 Data security transmission method of health monitoring system based on rate splitting

Country Status (1)

Country Link
CN (1) CN116669016A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117641452A (en) * 2023-12-12 2024-03-01 徐州医科大学 Computing and unloading optimization method of medical Internet of things based on rate splitting

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117641452A (en) * 2023-12-12 2024-03-01 徐州医科大学 Computing and unloading optimization method of medical Internet of things based on rate splitting

Similar Documents

Publication Publication Date Title
Wu et al. A CNN-based end-to-end learning framework toward intelligent communication systems
Yang et al. Fifty years of MIMO detection: The road to large-scale MIMOs
Liu et al. Joint power control and fronthaul rate allocation for throughput maximization in OFDMA-based cloud radio access network
Liu et al. Optimized uplink transmission in multi-antenna C-RAN with spatial compression and forward
CN105491563B (en) Method and system for improving security rate of MISO security communication system by utilizing artificial noise
EP3817242A1 (en) Method and apparatus for reporting channel state information in wireless communication system
CN106063215B (en) Signal transmission and received modulator approach and device are carried out in mobile communication system
CN109728865B (en) Interception coding method based on artificial noise in large-scale antenna array
CN116669016A (en) Data security transmission method of health monitoring system based on rate splitting
Liu et al. Capacity for downlink massive MIMO MU-SCMA system
CN112333702A (en) Optimization method for delay minimization based on safe NOMA moving edge calculation
Salah et al. Spectral efficiency enhancement based on sparsely indexed modulation for green radio communication
KR20190140366A (en) Method and apparatus for determining a codebook in non-orthogonal multiple access system
Wang et al. Multicast secrecy rate maximization for reconfigurable intelligent surface backscatter communication
Xiao et al. Low-complexity designs of symbol-level precoding for MU-MISO systems
CN114501580A (en) Cooperative rate segmentation network security transmission method with untrusted relay threat
CN107612669B (en) User pairing method for non-orthogonal multiple access system
Bai et al. Artificial noise aided polar codes for physical layer security
Davaslioglu et al. End-to-end autoencoder communications with optimized interference suppression
Xu et al. Energy efficiency optimization of NOMA IoT communication for 5G
CN113612571B (en) Multi-component safe transmission method based on generalized multi-fraction Fourier transform
CN113938252B (en) Transmission method for reducing time delay default probability
He et al. The interference wiretap channel with an arbitrarily varying eavesdropper: Aligning interference with artificial noise
Zhang et al. Adaptive CSI feedback for deep learning-enabled image transmission
CN110365374B (en) Safe and accurate wireless transmission method based on multi-phased array direction modulation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination