CN112134602B - Method for updating user state information in large-scale MIMO system - Google Patents

Method for updating user state information in large-scale MIMO system Download PDF

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CN112134602B
CN112134602B CN202011010318.XA CN202011010318A CN112134602B CN 112134602 B CN112134602 B CN 112134602B CN 202011010318 A CN202011010318 A CN 202011010318A CN 112134602 B CN112134602 B CN 112134602B
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length
base station
wireless sensor
state information
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CN112134602A (en
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蔡跃明
于宝泉
吴丹
张余
杨炜伟
杨文东
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Army Engineering University of PLA
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    • H—ELECTRICITY
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    • 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
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    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0006—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission format
    • H04L1/0007—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission format by modifying the frame length
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H—ELECTRICITY
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
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    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
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Abstract

A method for updating user state information in a large-scale MIMO system relates to the field of wireless communication. The invention comprises the following steps: s1, the wireless sensor sends an access request; s2, designing a data packet structure by the base station; s3 broadcast packet packing scheme; s4, the wireless sensor sends data packet, the base station decodes the state information and updates; s5 continuously updates all user status information. According to the invention, the optimization process of the data packet packing scheme is placed in the base station with strong computing power, and the wireless sensor only needs to adjust the lengths of the pilot frequency information and the state information according to the data packet packing scheme broadcasted by the base station, so that the burden of the wireless sensor is reduced; the base station iteratively optimizes the lengths of the pilot frequency information and the state information by using the golden section algorithm, the iteration times are few, and the method is suitable for the Internet of things with a simple structure and low computing capability of the wireless sensor, but is not limited to the range listed above.

Description

Method for updating user state information in large-scale MIMO system
Technical Field
The invention relates to the field of wireless communication, in particular to a user state information updating method in a large-scale MIMO system.
Background
The arrival of the internet of things era promotes the development of machine communication and greatly changes the production and living modes of people. In some internet of things applications, the base station or the central controller needs to continuously obtain the latest target state information from the wireless sensor so as to make a decision or send an instruction. For example: the intelligent parking lot controller needs to obtain the latest occupancy information of each parking space and pushes the latest occupancy information to nearby drivers; the weather sensor needs to transmit the latest environmental information to the weather station so that the weather station can make scientific and accurate weather forecast; the mobile robot needs to feed back information such as position, speed and the like of the mobile robot to the control end so that the control end can send out an accurate instruction; and so on. However, the receiving end cannot obtain the latest status information due to the wireless communication transmission delay, packet error and other factors.
To characterize the performance of a state update system, Kaul et al, in the paper [ s.kaul, r.yates, and m.gruteser, "Real-time status: How telephone one update? The information age is used as a performance index to reflect the freshness of the state information acquired by a receiving end in proc. In order to reduce the age of system information to improve the performance of a wireless sensor state updating system, most of the existing documents consider designing a scheduling method, and a paper [ z.jiang, b.krishnamachari, x.zheng, et al, "time status update in wireless updates: Analytical solutions with adaptive timings," IEEE Internet changes j. vol, 6, No.2, pp.3885-3898, and apr.2019 ] improves the overall state updating performance of the system by optimizing the scheduling method of the wireless sensor in each time slot and the packet scheduling method of the selected wireless sensor. In addition, the paper [ i.krikidis, "Average Age of Information in Wireless power Sensor Networks," IEEE Wireless commun.lett., vol.8, No.2, pp.628-631, apr.2019 ] analyzed the state update performance under the ideal channel state Information condition using the conventional shannon theory. However, most wireless sensors in practical application have simple structures, and it is often difficult to support a scheduling method with a relatively complex communication protocol. Meanwhile, the wireless sensor state information amount is small, the coding length adopted by the state information is short, the traditional Shannon theory is not applicable any more, and the time-frequency resource overhead caused by the estimation of the channel state information is not negligible. Therefore, the application of the existing state information updating method in the scene of the internet of things is limited.
Disclosure of Invention
The invention is suitable for the application occasions of the Internet of things with simple structure requirements and low calculation capability requirements on a wireless sensor, and provides a user state information updating method for improving the user state information updating performance in a large-scale MIMO system.
A method for updating user state information in a large-scale MIMO system comprises the following steps:
step 1: and (3) access request: before K wireless sensors in the large-scale MIMO system send state information to a base station for the first time, sending an access request to the base station, wherein the wireless sensors are used for monitoring and collecting the state information of a user, each wireless sensor is provided with a single antenna, and the access request sent by the wireless sensors contains the position information of the wireless sensors; k is more than or equal to 1, the base station is provided with M antennas, and M > K; if the position of the wireless sensor changes, the wireless sensor sends an access request to the base station again;
step 2: and (3) data packet structure design: after receiving access requests of all wireless sensors, the base station calculates the length n of pilot frequency information sent by the wireless sensors by using a data packet structure design method based on information agepAnd a status information length ndWherein, the data packet structure design method based on the information age is mainly to minimize the average information age of the wireless sensor
Figure BDA0002697359830000026
The determination of the length of the pilot information and the length of the status information in the data packets sent by the wireless sensor for the purpose of targeting may be expressed as
Figure BDA0002697359830000021
s.t.np≥K, (1a)
nd≥nmin, (1b)
np+nd≤nmax, (1c)
Wherein n isminFor the coding length of the payload information in the data packet, nmaxIs the total packet length within one coherence time,
Figure BDA0002697359830000022
is the average age of information of the kth wireless sensor, expressed as
Figure BDA0002697359830000023
Wherein B is the signal bandwidth transmitted by the wireless sensor,
Figure BDA0002697359830000024
the average failure probability of the data packet of the kth wireless sensor is received by the base station, and the average transmission failure probability of the data packet after the short data packet communication theory is expressed as
Figure BDA0002697359830000025
Where D represents the amount of information of the state update content, x is an integral variable, PkIs the transmission power of the kth wireless sensor, dkIs the distance between the kth wireless sensor and the base station, alpha is the path fading coefficient, chioChannel gain, σ, over a path of unit length2Representing the noise power of additive white Gaussian noise, and gamma (M-K +1) is a complete gamma function of M-K + 1;
and step 3: packet grouping scheme broadcast: the base station optimizes the obtained pilot frequency information length according to the step 2
Figure BDA0002697359830000031
And status information length
Figure BDA0002697359830000032
Broadcasting to all wireless sensors, and coding pilot frequency information and state updating information by all wireless sensors according to the data packet structure information fed back by the base station;
and 4, step 4: state information transmission and updating: all wireless sensors synchronously send data packets to a base station, the base station estimates channel fading coefficients from all the wireless sensors to the base station according to pilot frequency information in the data packets, designs a zero forcing detection matrix, implements zero forcing detection by using the zero forcing matrix, and decodes state information sent by the wireless sensors; if the data packet sent by the wireless sensor is successfully decoded, the base station updates the state information of the target monitored by the wireless sensor, otherwise, the base station does not update the state information of the target monitored by the wireless sensor;
and 5: and (4) repeating the step (4), continuously sending the pilot frequency information and the state information to the base station by all the wireless sensors, and updating the base station according to the decoding condition of the data packet.
Compared with the existing method for improving the system state updating performance, the method has the following advantages and effects:
the invention provides a user state information updating method in a large-scale MIMO system, in the method, a wireless sensor for collecting user state information only needs to adjust the lengths of pilot frequency information and state information according to a data packet packaging scheme broadcasted by a base station, no additional complex transmission protocol is needed, and the method is suitable for the application of the Internet of things with simple structure and low computing capacity of the wireless sensor; the base station adopts zero forcing detection to identify the data packet sent by the wireless sensor, so that the interference caused by multi-user communication can be effectively relieved; the base station does not need to frequently update the data packet packaging scheme according to the instantaneous channel state information, so that the resource overhead caused by scheme design is reduced.
The invention comprehensively considers the influence of short data packet communication and the condition of non-ideal channel state information at a receiving end, and can more accurately depict the updating process of the user state information. According to the invention, complex algorithm design work is carried out at the base station side with strong computing power, and the wireless sensor with a simple structure only needs to receive a data packet packaging scheme broadcasted by the base station and adjust the length of the transmitted pilot frequency information and the length of the state information, so that the method is suitable for the actual situation that the wireless sensor of the Internet of things has a simple structure and low computing power. Aiming at the base station side, the base station uses the golden section algorithm to iteratively optimize the lengths of the pilot frequency information and the state information, the iteration times are few, compared with an exhaustive search algorithm, the algorithm complexity is low, and the optimization performance almost similar to the exhaustive search algorithm can be achieved.
Drawings
FIG. 1 is a system model diagram of the present invention, which includes a large-scale multi-antenna base station, and several single-antenna wireless sensors.
Fig. 2 is a flowchart of a user status information updating method according to the present invention.
Fig. 3 is a schematic diagram of the status information updating process of the kth wireless sensor according to the present invention.
Fig. 4 is a graph of the average information age of the system of the present invention as a function of the pilot information length.
FIG. 5 is a graph of the average information age of the system of the present invention as a function of the length of the status information.
FIG. 6 is a graph comparing the performance of the present invention with an exhaustive search method.
FIG. 7 is a convergence analysis diagram of the present invention.
FIG. 8 is a graph of the average information age of the system of the present invention as a function of the number of base station antennas.
Detailed Description
The system for updating large-scale multi-user uplink state information shown in FIG. 1 comprises a base station with M antennas and K single-antenna wireless sensors, wherein K is larger than or equal to 1, and M is larger than K. Due to the fact that the base station has high computing capacity, the design work of the wireless sensor data packet packaging scheme is conducted on the base station side. The base station broadcasts the packet grouping scheme to all wireless sensors. In the data transmission process, the wireless sensors send pilot frequency information to assist the base station to complete the design of a zero forcing matrix, and each wireless sensor sends state information of Dnats to the base station to update the state information of the base station side about the monitored target. And after carrying out zero forcing detection on the received state updating information, the base station decodes the state updating information sent from each user.
According to the flow chart of the user status information updating method shown in fig. 2, the specific implementation steps of the present invention include:
step S1: and (3) access request: before K wireless sensors in the large-scale MIMO system send state information to a base station for the first time, sending an access request to the base station, wherein the wireless sensors are used for monitoring and collecting the state information of a user, each wireless sensor is provided with a single antenna, and the access request sent by the wireless sensors contains the position information of the wireless sensors; k is more than or equal to 1, the base station is provided with M antennas, and M > K; if the position of the wireless sensor changes, the wireless sensor sends an access request to the base station again;
step S2: and (3) data packet structure design: after the base station receives the access requests of all the wireless sensors, for the number of the wireless sensors, the base station knows the number of the wireless sensors distributed in a certain area in advance, and thus all the wireless sensors are accessed to a redesigned data packet structure; generally, the base station is designed according to the currently accessed wireless sensors, and if some wireless sensors are not accessed at first and then accessed later, the base station receives a new access request, and the scheme is redesigned at this time. Many times, such as water quality detection, the deployment number and the position of the sensors are set in advance, so that whether all the sensors are connected or not can be easily known. For the access content between the base station and the wireless sensor, if the access information is incomplete or fails to be accessed due to the influence of interference and the like, the base station gives feedback to the sensor, and the sensor only needs to transmit the feedback once again.
Calculating pilot frequency information length n transmitted by wireless sensor by using data packet structure design method based on information agepAnd a status information length ndWherein the data packet structure design method based on information age is mainly to minimize the average information age of all wireless sensors
Figure BDA0002697359830000051
The determination of the length of the pilot information and the length of the status information in the data packets sent by the wireless sensor for the purpose of targeting may be expressed as
Figure BDA0002697359830000052
s.t.np≥K, (1a)
nd≥nmin, (1b)
np+nd≤nmax, (1c)
Wherein n isminFor the coding length of the payload information in the data packet, nmaxIs the total packet length within one coherence time,
Figure BDA0002697359830000053
is the average age of information of the kth wireless sensor, expressed as
Figure BDA0002697359830000054
Wherein B is the signal bandwidth transmitted by the wireless sensor,
Figure BDA0002697359830000055
and averaging the failure probability of receiving the data packet of the kth wireless sensor for the base station. Because the data packet sent by the wireless sensor node is very short, the traditional interruption probability based on the infinite packet length assumption cannot well describe the condition of short data packet transmission failure. In this respect, the average transmission failure probability of the data packet after the short data packet communication theory is adopted in the invention is expressed as
Figure BDA0002697359830000056
Where D represents the amount of information of the state update content, x is an integral variable, PkIs the transmission power of the kth wireless sensor, dkIs the distance between the kth wireless sensor and the base station, alpha is the path fading coefficient, chioChannel gain, σ, over a path of unit length2Representing the noise power of additive white Gaussian noise, and gamma (M-K +1) is a complete gamma function of M-K + 1;
the wireless sensor average information age optimization model given by the formula (1) is realized by adopting a golden section method, and the method specifically comprises the following steps:
step 2.1: the method for optimizing the average information age of all wireless sensors in the minimization process given by the formula (1) is equivalent to an optimization method for solving the pilot information length and solving the state information length, wherein the method for solving the pilot information length is obtained based on the following optimization model
Figure BDA0002697359830000061
s.t.K≤np≤nmax-nd； (4a)
The method for solving the length of the state information is obtained based on the following optimization model
Figure BDA0002697359830000062
s.t.nmin≤nd≤nmax-np； (5a)
Step 2.2: length of initialization status information
Figure BDA0002697359830000063
The iteration number tau is 0 and the golden section coefficient rho is 0.618;
step 2.3: based on the length of the state information of the Tth iteration
Figure BDA0002697359830000064
Preliminary determination of pilot information length
Figure BDA0002697359830000065
Two golden section points for calculating optimized pilot frequency information length
Figure BDA0002697359830000066
And
Figure BDA0002697359830000067
wherein the content of the first and second substances,
Figure BDA0002697359830000068
Figure BDA0002697359830000069
a lower bound for the search of the pilot information length,
Figure BDA00026973598300000610
Figure BDA00026973598300000611
an upper bound for the search for pilot information length,
Figure BDA00026973598300000612
step 2.4: calculating and comparing average information age values at two golden section points
Figure BDA00026973598300000613
And
Figure BDA00026973598300000614
if it is
Figure BDA00026973598300000615
Then search the upper bound
Figure BDA00026973598300000616
Without change, the lower search bound is updated to
Figure BDA00026973598300000617
At the same time, the positions of the two golden section points are updated to
Figure BDA00026973598300000618
If it is
Figure BDA00026973598300000619
Then search the lower bound
Figure BDA00026973598300000620
Unchanged, the search upper bound is updated to
Figure BDA00026973598300000621
At the same time, the positions of the two golden section points are updated to
Figure BDA00026973598300000622
Figure BDA00026973598300000623
Step 2.5: repeating step 2.4, and continuously reducing the search range of the pilot frequency information length until
Figure BDA00026973598300000624
Information length of paired pilots
Figure BDA00026973598300000625
After rounding and optimizing, the pilot frequency information length is obtained
Figure BDA0002697359830000071
Wherein
Figure BDA0002697359830000072
The obtained pilot length is calculated for the (t +1) th iteration,
Figure BDA0002697359830000073
meaning that the rounding is done up for x,
Figure BDA0002697359830000074
represents rounding down on x;
step 2.6: pilot information length obtained based on calculation
Figure BDA0002697359830000075
Preliminary determination of status information length
Figure BDA0002697359830000076
Two golden section points for calculating length of optimized state information
Figure BDA0002697359830000077
And
Figure BDA0002697359830000078
wherein the content of the first and second substances,
Figure BDA0002697359830000079
Figure BDA00026973598300000710
for the lower bound of the search for the length of the state information,
Figure BDA00026973598300000711
Figure BDA00026973598300000712
the upper bound of the search for the length of the state information,
Figure BDA00026973598300000713
step 2.7: calculating and comparing average information age values at two golden section points
Figure BDA00026973598300000714
And
Figure BDA00026973598300000715
if it is
Figure BDA00026973598300000716
Then search the upper bound
Figure BDA00026973598300000717
Without change, the lower search bound is updated to
Figure BDA00026973598300000718
At the same time, the positions of the two golden section points are updated to
Figure BDA00026973598300000719
If it is
Figure BDA00026973598300000720
Then search the lower bound
Figure BDA00026973598300000721
Unchanged, the search upper bound is updated to
Figure BDA00026973598300000722
At the same time, the positions of the two golden section points are updated to
Figure BDA00026973598300000723
Figure BDA00026973598300000724
Step 2.8: repeating the step 2.7, and continuously reducing the searching range of the length of the state updating data packet until the searching range is up to
Figure BDA00026973598300000725
Length of channel state information
Figure BDA00026973598300000726
After rounding and optimizing, the state information length is obtained
Figure BDA00026973598300000727
And calculating tau as tau + 1;
step 2.9: repeating the step 2.3 to the step 2.8, and iteratively calculating the pilot frequency information length
Figure BDA00026973598300000728
And status information length
Figure BDA00026973598300000729
Until the algorithm converges, because the pilot information length and the state information length affect the average information age, different pilot information lengths and state information lengths correspond to different information ages. The optimal pilot frequency information length and the optimal state information length enable the average information age to be the lowest, the iterative process is the process approaching the lowest value, the algorithm convergence standard is that the change of the average information ages of all the sensors is smaller than a certain threshold value compared with the value of the last iteration, and the condition of the algorithm convergence is considered to be met. Obtaining optimal pilot information length
Figure BDA00026973598300000730
Sum status information lengthDegree of rotation
Figure BDA00026973598300000731
The specific solution implementation of the average information age optimization method based on the golden section can be expressed as follows:
Figure BDA00026973598300000732
Figure BDA0002697359830000081
wherein the content of the first and second substances,
Figure BDA0002697359830000082
representing an algorithm convergence threshold;
step S3: packet grouping scheme broadcast: the base station optimizes the obtained pilot frequency information length according to the step 2
Figure BDA0002697359830000091
And status information length
Figure BDA0002697359830000092
Broadcasting to all wireless sensors, and coding pilot frequency information and state updating information by all wireless sensors according to the data packet structure information fed back by the base station;
step S4: state information transmission and updating: all wireless sensors synchronously send data packets to a base station, the base station estimates channel fading coefficients from all the wireless sensors to the base station according to pilot frequency information in the data packets, and a zero forcing detection matrix V is designed to be expressed as
Figure BDA0002697359830000093
Wherein the content of the first and second substances,
Figure BDA0002697359830000094
representing transmissions from radioA channel estimation matrix from the sensor nodes to the base station,
Figure BDA0002697359830000095
V＝[v1,…,vK]，
Figure BDA0002697359830000096
the channel fading coefficient between the kth wireless sensor to the base station estimated for the base station,
Figure BDA0002697359830000097
a detection vector indicating the state information transmitted from the kth wireless sensor by the base station,
Figure BDA0002697359830000098
a complex vector representing M rows and one column,
Figure BDA0002697359830000099
representation matrix
Figure BDA00026973598300000910
The conjugate transpose of (1);
the base station performs zero forcing detection by using the zero forcing matrix and decodes the state information sent by the wireless sensor; if the data packet sent by a certain wireless sensor is successfully decoded, the base station updates the state information of the target monitored by the wireless sensor, otherwise, the base station does not update the state information of the target monitored by the wireless sensor;
step S5: step S4 is repeated, as shown in the status information updating process of the wireless sensor shown in fig. 3, all the wireless sensors continuously send the pilot frequency information and the status information to the base station, and the base station updates according to the decoding condition of the data packet.
Example (b):
consider a circular cell with a radius of 180m in conjunction with the 3GPP Release-15 standard, with the base station located at the center of the cell. The wireless sensor nodes are evenly distributed in a ring-shaped area from 50m to the cell edge from the base station. The system bandwidth is 180kHz, the power spectral density of noise is-174 dBm/Hz, the path fading factor alpha is 3.6, and a unit pathSignal gain x on path0The number of base station antennas M is 32 and the number of wireless sensors K is 12 at-60 dB. All wireless sensors in the system are the same type of wireless sensors, have the same transmitting power and are all 13 dBm. It is worth mentioning that the method is also applicable to the case that the wireless sensors have different transmission powers. The information quantity D of the target state information transmitted by the wireless sensor is 300nats, and the coding lengths of the pilot frequency and the state information are n p50 channels and nd＝200channeluses。
Fig. 4 and 5 show graphs of the variation of the average information age with the length of the pilot information and the length of the status information, respectively. The figure shows that the simulation point is overlapped with the theoretical curve, and the average information age of the system is firstly reduced and then increased along with the increase of the pilot frequency information length and the state information length, thereby proving that the effectiveness of improving the state information updating performance by optimizing the data packet structure.
FIG. 6 is a comparison of the performance of the method of the present invention with an exhaustive search algorithm. Figure 6 shows that the method of the present invention can achieve almost the same performance as an exhaustive search algorithm. The exhaustive search algorithm calculates and compares the average information age value by traversing all the effective pilot information lengths and state information lengths, and finally outputs the optimal pilot information length and state information length. The exhaustive search method is a method that can obtain the optimal solution, but the complexity is high. The method greatly reduces the complexity of the algorithm by decoupling the original problem into two subproblems and solving each subproblem by utilizing the golden section. Fig. 7 shows the convergence characteristics of the present invention, and fig. 7 shows that the number of iterations required for the algorithm of the present invention is small, demonstrating that the complexity of the algorithm of the present invention is low.
Fig. 8 is a graph showing the relationship between the average information age of the system and the number of antennas of the base station, and fig. 8 shows that the average information age of the system can be reduced in an order by deploying large-scale antennas at the base station side, and the state information updating performance of the system can be effectively improved.

Claims (4)

1. A method for updating user state information in a large-scale MIMO system is characterized in that: the method comprises the following steps:
step S1: and (3) access request: k wireless sensors used for monitoring and collecting user state information in the large-scale MIMO system send access requests to a base station before sending the state information to the base station for the first time, each wireless sensor is provided with a single antenna, and the access requests sent by the wireless sensors contain wireless sensor position information; k is more than or equal to 1, the base station is provided with M antennas, and M > K; if the position of the wireless sensor changes, the wireless sensor sends an access request to the base station again;
step S2: designing a data packet structure: after receiving access requests of all wireless sensors, the base station calculates the length n of pilot frequency information sent by the wireless sensors by using a data packet structure design method based on information agepAnd a status information length ndWherein, the data packet structure design method based on the information age is to minimize the average information age of the wireless sensor
Figure FDA0002697359820000016
Determining the length of pilot frequency information and the length of state information in data packets sent by the wireless sensor for a target, and expressing an average information age optimization model of the wireless sensor as
Figure FDA0002697359820000011
s.t.np≥K, (1a)
nd≥nmin, (1b)
np+nd≤nmax, (1c)
Wherein n isminFor the coding length of the payload information in the data packet, nmaxIs the total packet length within one coherence time,
Figure FDA0002697359820000012
is the average age of information of the kth wireless sensor, expressed as
Figure FDA0002697359820000013
Wherein B is the signal bandwidth transmitted by the wireless sensor,
Figure FDA0002697359820000014
the average failure probability of the data packet of the kth wireless sensor is received by the base station, and the average transmission failure probability of the data packet after the short data packet communication theory is expressed as
Figure FDA0002697359820000015
Where D represents the amount of information of the state update content, x is an integral variable, PkIs the transmission power of the kth wireless sensor, dkIs the distance between the kth wireless sensor and the base station, alpha is the path fading coefficient, chioChannel gain, σ, over a path of unit length2Representing the noise power of additive white Gaussian noise, and gamma (M-K +1) is a complete gamma function of M-K + 1;
step S3: the broadcast data packet grouping scheme comprises the following steps: the base station optimizes the obtained pilot information length according to step S2
Figure FDA0002697359820000021
And status information length
Figure FDA0002697359820000022
Broadcasting to all wireless sensors, and coding pilot frequency information and state updating information by all wireless sensors according to the data packet structure information fed back by the base station;
step S4: state information transmission and updating: all wireless sensors synchronously send data packets to a base station, the base station estimates channel fading coefficients from all the wireless sensors to the base station according to pilot frequency information in the data packets, designs a zero forcing detection matrix, implements zero forcing detection by using the zero forcing matrix, and decodes state information sent by the wireless sensors; if the data packet sent by the wireless sensor is successfully decoded, the base station updates the state information of the target monitored by the wireless sensor, otherwise, the base station does not update the state information of the target monitored by the wireless sensor;
step S5: and step S4 is repeated, all wireless sensors continuously send pilot frequency information and state information to the base station, and the base station updates according to the decoding condition of the data packet.
2. The method of claim 1, wherein the user status information in the massive MIMO system is updated by: the wireless sensor average information age optimization method in step S2 is equivalent to an optimization method of pilot information length solution and state information length solution, where the pilot information length solution method is obtained based on the following optimization model
Figure FDA0002697359820000023
s.t.K≤np≤nmax-nd； (4a)
The method for solving the length of the state information is obtained based on the following optimization model
Figure FDA0002697359820000024
s.t.nmin≤nd≤nmax-np； (5a)。
3. The method of claim 2, wherein the model for optimizing the age of the average information of the wireless sensors is solved by a golden section method after being decomposed, comprising the following steps:
step 2.1: length of initialization status information
Figure FDA0002697359820000025
The iteration number tau is 0 and the golden section coefficient rho is 0.618;
step 2.2: based on the length of the state information of the Tth iteration
Figure FDA0002697359820000026
Preliminary determination of pilot information length
Figure FDA0002697359820000031
Two golden section points for calculating optimized pilot frequency information length
Figure FDA0002697359820000032
And
Figure FDA0002697359820000033
wherein the content of the first and second substances,
Figure FDA0002697359820000034
Figure FDA0002697359820000035
a lower bound for the search of the pilot information length,
Figure FDA0002697359820000036
Figure FDA0002697359820000037
an upper bound for the search for pilot information length,
Figure FDA0002697359820000038
step 2.3: calculating and comparing average information age values at two golden section points
Figure FDA0002697359820000039
And
Figure FDA00026973598200000310
and updating the upper search bound for pilot information length
Figure FDA00026973598200000311
Lower search bound for pilot information length
Figure FDA00026973598200000312
And two golden section points
Figure FDA00026973598200000313
And
Figure FDA00026973598200000314
the position of (a);
step 2.4: repeating the step 2.3, and continuously reducing the search range of the pilot frequency information length until
Figure FDA00026973598200000315
Information length of paired pilots
Figure FDA00026973598200000316
After rounding and optimizing, the pilot frequency information length is obtained
Figure FDA00026973598200000317
Wherein the content of the first and second substances,
Figure FDA00026973598200000318
the obtained pilot length is calculated for the (t +1) th iteration,
Figure FDA00026973598200000319
meaning that the rounding is done up for x,
Figure FDA00026973598200000320
represents taking down for xFinishing;
step 2.5: pilot information length obtained based on calculation
Figure FDA00026973598200000321
Preliminary determination of status information length
Figure FDA00026973598200000322
Two golden section points for calculating length of optimized state information
Figure FDA00026973598200000323
And
Figure FDA00026973598200000324
wherein the content of the first and second substances,
Figure FDA00026973598200000325
Figure FDA00026973598200000326
for the lower bound of the search for the length of the state information,
Figure FDA00026973598200000327
Figure FDA00026973598200000328
the upper bound of the search for the length of the state information,
Figure FDA00026973598200000329
step 2.6: calculating and comparing average information age values at two golden section points
Figure FDA00026973598200000330
And
Figure FDA00026973598200000331
and updating the upper search bound of the length of the state information
Figure FDA00026973598200000332
Lower search bound for length of state information
Figure FDA00026973598200000333
And two golden section points
Figure FDA00026973598200000334
And
Figure FDA00026973598200000335
the position of (a);
step 2.7: repeating the step 2.6, and continuously reducing the searching range of the length of the state updating data packet until the searching range is up to
Figure FDA00026973598200000336
Length of channel state information
Figure FDA00026973598200000337
After rounding and optimizing, the state information length is obtained
Figure FDA00026973598200000338
And calculating tau as tau + 1;
step 2.8: repeating the step 2.2 to the step 2.7, and iteratively calculating the pilot frequency information length
Figure FDA00026973598200000339
And status information length
Figure FDA00026973598200000340
Until the algorithm is converged, obtaining the optimal pilot frequency information length
Figure FDA00026973598200000341
And status information length
Figure FDA00026973598200000342
4. The method for updating user status information in a massive MIMO system according to any one of claims 1 to 3, wherein: the zero forcing detection matrix V in the above step S4 is represented as
Figure FDA0002697359820000041
Wherein the content of the first and second substances,
Figure FDA0002697359820000042
representing the channel estimation matrix from the wireless sensor to the base station,
Figure FDA0002697359820000043
V＝[v1,…,vK]，
Figure FDA0002697359820000044
the channel fading coefficient between the kth wireless sensor to the base station estimated for the base station,
Figure FDA0002697359820000045
a detection vector indicating the state information transmitted from the kth wireless sensor by the base station,
Figure FDA0002697359820000046
a complex vector representing M rows and one column,
Figure FDA0002697359820000047
representation matrix
Figure FDA0002697359820000048
The conjugate transpose of (c).
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110543185A (en) * 2019-07-19 2019-12-06 宁波大学 unmanned aerial vehicle data collection method based on minimum information age
CN111030764A (en) * 2019-10-31 2020-04-17 武汉大学 Crowdsourcing user information age management algorithm based on random game online learning
CN111601269A (en) * 2020-05-15 2020-08-28 中国民航大学 Event trigger Kalman consistency filtering method based on information freshness judgment

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8102944B2 (en) * 2007-05-18 2012-01-24 Qualcomm Incorporated Mode and rate control for MIMO transmission
US9973939B2 (en) * 2015-09-25 2018-05-15 Vivint, Inc. UAV network design
US10667144B2 (en) * 2018-01-25 2020-05-26 Qualcomm Incorporated Techniques and apparatuses for measuring beam reference signals based at least in part on location information

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110543185A (en) * 2019-07-19 2019-12-06 宁波大学 unmanned aerial vehicle data collection method based on minimum information age
CN111030764A (en) * 2019-10-31 2020-04-17 武汉大学 Crowdsourcing user information age management algorithm based on random game online learning
CN111601269A (en) * 2020-05-15 2020-08-28 中国民航大学 Event trigger Kalman consistency filtering method based on information freshness judgment

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