A multi-user power allocation method for Internet of Things based on external information analysis

Abstract

The present invention belongs to the field of wireless communication technology, and specifically discloses a method for allocating power to multiple users of the Internet of Things based on external information analysis, comprising the following steps: NOMA The channel model of the system is analyzed to obtain the optimal power allocation problem; the calculation is NOMA External information of the decoding module in the system, using the external information of the decoding module EXIT Char The analysis tool is used to analyze and obtain the bit error rate; based on the optimal power allocation problem and the bit error rate, the signal to noise ratio level required by each access user is calculated; according to the signal to noise ratio level required by each access user, the total power required by each access user is calculated to complete the user power allocation. The present invention solves the problem that the existing power allocation method is mostly based on the downlink system deployment and the complex power allocation algorithm is accompanied by additional overhead, and has a lower bit error rate.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a design of a multi-user power allocation method for an Internet of Things based on external information analysis. Background Art

[0002] exist OR In the system, each user signal is allocated different power levels in the same resource block through power domain multiplexing technology, and finally transmitted between the transmitting and receiving ends in a superimposed manner. SIC The detection algorithm allows the receiver to separate the signals of different users to ensure the correct reception of individual user data. Naturally, how to allocate the appropriate power level to each user based on the constraints while balancing key performance indicators such as rate, fairness and reliability is a key issue. OR This is a very critical issue in system design.

[0003] Currently common basic OR The system power allocation algorithm mainly includes fixed power allocation algorithm ( fixed per- group power allocation , FPA ), exhaustive search for power allocation algorithm ( exhaustive search power allocation , ESPA ), based on proportional fairness ( proportional fairness , PF ) criterion fractional order power allocation algorithm ( fractional transmit power allocation , FTPA ), and water injection ( water-filling ) power allocation algorithm, etc.

[0004] in, FPA The algorithm completes the allocation of power resources by presetting a consistent proportional coefficient for each user. The fixed power proportional coefficient between users ensures that the transmitter can quickly and flexibly complete the power allocation, so FPA The algorithm can effectively reduce the computational overhead. However, although its implementation is very simple, FPA The performance of the algorithm is not optimal.

[0005] and ESPA The algorithm exhaustively traverses all possible allocation schemes and selects the solution with the best performance. ESPA The algorithm can ensure the optimal solution. However, due to its exhaustive nature, when the number of users is large, ESPA The complexity of the algorithm will become unacceptable. ESPA The implementation of the algorithm is difficult.

[0006] The water injection power allocation algorithm is implemented based on the iterative water injection principle. Its main idea is to adaptively allocate power based on the user's channel conditions, that is, to allocate higher power to users with better channel conditions and less power to users with worse channel conditions. This strategy can effectively improve system performance. FPA and ESPA ,The water-injection power allocation algorithm trades for suboptimal system performance at the cost of lower computational complexity, but the algorithm does not ,focus on fairness among users, the performance of its edge users is relatively poor, and the ,obtained system performance has no lower limit support.,However, in some complex scenarios with a large number of users, as a ,low-complexity algorithm, the water-injection power allocation algorithm is still a feasible ,and efficient technical solution.

[0007] The above discussion of power allocation algorithms is often based on the downlink system. However, complex power allocation algorithms require complete channel state information ( channel status information , CSI ), or involves the calculation of fairness metrics, so in the upstream OR In the system, the access point ( access point , AP ) and user equipment ( user equipment , EU ) need to be fully coordinated before information transmission can begin, and this process is often accompanied by additional overhead. Summary of the invention

[0008] The purpose of the present invention is to solve the problem that the existing power allocation methods are mostly based on downlink system deployment and the complex power allocation algorithm is accompanied by additional overhead, and a multi-user power allocation method for the Internet of Things based on external information analysis is proposed.

[0009] The technical solution of the present invention is: a method for allocating power to multiple users of the Internet of Things based on external information analysis, comprising the following steps:

[0010] S1.According to OR Channel model of the system, analysis OR The achievable rate region of the system, obtains the optimal power allocation problem;

[0011] S2. Calculated OR External information of the decoding module in the system, using the external information of the decoding module EXIT Char The analysis tool is used to analyze and obtain the bit error rate;

[0012] S3. Based on the optimal power allocation problem and the bit error rate, the signal to interference and noise ratio level required by each access user is calculated;

[0013] S4. According to the signal-to-interference-noise ratio level required by each access user, the total power required by each access user is calculated to complete the user power allocation.

[0014] The beneficial effects of the present invention are:

[0015] The present invention can support flexible user rate allocation while improving the system and rate, helps to improve fairness among users, and has a lower bit error rate.

[0016] Preferably, the step S1 OR The channel model of the system includes OR Multiple access channel model and OR Broadcast channel model.

[0017] Preferably, the OR The multiple access channel model includes access points and user equipment, and the signal is transmitted from the user equipment to the access point;

[0018] Said OR The calculation formula for the signal-to-interference-to-noise ratio of the user equipment signal received by the access point in the multiple access channel model is:

[0019]

[0020] in, express OR Multiple access channel model The signal-to-interference-to-noise ratio of the access user signal; Indicates the access point to Channel coefficient of each access user; express OR Multiple access channel model The signal transmission power of each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth; represents the Frobenius norm.

[0021] Preferably, the OR The broadcast channel model includes access points and user equipment, and the signal is transmitted from the access point to the user equipment;

[0022] Said OR The calculation formula of the signal-to-interference-to-noise ratio of the signal received by the user equipment in the broadcast channel model is:

[0023]

[0024] in, express OR In the broadcast channel model The signal-to-interference-to-noise ratio of the signal received by each access user; Indicates the access point to Channel coefficient of each access user; express OR In the broadcast channel model, the access point is The signal transmission power allocated to each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth.

[0025] Preferably, in step S1, OR The system's achievable rate area includes the multiple access channel achievable rate area and the broadcast channel achievable rate area.

[0026] Preferably, the optimal power allocation problem is expressed as:

[0027]

[0028] in, Indicates the total number of all access users; Indicates The signal-to-interference-and-noise ratio level required by each access user; Indicates the minimum total power; Indicates The total power required by each access user; It means that after the filter is amplified The signal-to-interference-noise ratio of the signal received by an access user.

[0029] Preferably, the step S2 specifically comprises the following steps:

[0030] S21. Calculated OR External information of a decoding module in the system, the external information including input external information and output external information;

[0031] The calculation formula of the input external information is:

[0032]

[0033] in, Represents the external input information of the decoding module, represents the integral variable, represents the exponential function, Represents the AWGN noise variance of the channel;

[0034] The calculation formula of the output external information is:

[0035]

[0036] in, Represents the output external information of the decoding module, represents the input codebook of the channel, represents the output codebook of the channel, represents the conditional probability density;

[0037] S22. Input external information and output external information EXIT Char The analysis tool draws the curves of input and output external information, analyzes the convergence of the external information, and outputs the bit error rate.

[0038] Preferably, step S3 comprises the following formula:

[0039] When the optimal power allocation problem is expressed in the formula:

[0040]

[0041] When the total power required is the minimum, the signal-to-interference-to-noise ratio level required by each access user is The calculation formula is:

[0042]

[0043] in, Indicates the codeword length; represents the modulation dimension; Indicates the code rate of channel coding; It represents the normalized equivalent bandwidth of the signal; Indicates the bit error rate; Represents a finite-length achievable bit rate function The inverse function of , represents the continuous channel capacity of the normalized bandwidth; represents the signal-to-interference-noise ratio; represents the channel divergence; Gauss The inverse of a function.

[0044] The beneficial effects of the above preferred solution are:

[0045] The present invention takes into account the uplink system and the downlink system, and integrates the external information analysis to be simple to implement and can ensure a higher average throughput.

[0046] Preferably, the calculation formula for the total power required by each access user in step S4 is:

[0047]

[0048] in, Indicates The total power required by each access user is Indicates The channel coefficient of each access user is represents the number of receiving antennas, represents the Frobenius norm. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Shown is a flow chart of a multi-user power allocation method for the Internet of Things based on external information analysis. DETAILED DESCRIPTION

[0050] Now, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the accompanying drawings are only exemplary and are intended to explain the principles and spirit of the present invention, rather than to limit the scope of the present invention.

[0051] like Figure 1 As shown, a method for allocating power to multiple users of the Internet of Things based on external information analysis comprises the following steps:

[0052] S1. Based on non-orthogonal multiple access ( OR ) System channel model, analysis OR The achievable rate region of the system, obtains the optimal power allocation problem;

[0053] S2. Calculated OR External information of the decoding module in the system, using the external information of the decoding module EXIT Char The analysis tool is used to analyze and obtain the bit error rate;

[0054] S3. Based on the optimal power allocation problem and the bit error rate, the signal to interference and noise ratio level required by each access user is calculated;

[0055] S4. According to the signal-to-interference-noise ratio level required by each access user, the total power required by each access user is calculated to complete the user power allocation.

[0056] In this embodiment, the step S1 OR The channel model of the system includes OR Multiple access ( MAC ) Channel Model and OR broadcast( BC ) channel model.

[0057] In this embodiment, the OR The multiple access channel model includes an access point and a user device, and the signal is transmitted from the user device to the access point; OR The calculation formula for the signal-to-interference-to-noise ratio of the user equipment signal received by the access point in the multiple access channel model is:

[0058]

[0059] in, express ORMultiple access channel model The signal-to-interference-to-noise ratio of the access user signal; Indicates the access point to Channel coefficient of each access user; express OR Multiple access channel model The signal transmission power of each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth; represents the Frobenius norm.

[0060] In this embodiment, the OR The broadcast channel model includes access points and user equipment, and the signal is transmitted from the access point to the user equipment;

[0061] Said OR The calculation formula of the signal-to-interference-to-noise ratio of the signal received by the user equipment in the broadcast channel model is:

[0062]

[0063] in, express OR In the broadcast channel model The signal-to-interference-to-noise ratio of the signal received by each access user; Indicates the access point to Channel coefficient of each access user; express OR In the broadcast channel model, the access point is The signal transmission power allocated to each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth.

[0064] In this embodiment, the optimal power allocation problem is expressed as:

[0065]

[0066] in, Indicates the total number of all access users; Indicates The signal-to-interference-and-noise ratio level required by each access user; Indicates the minimum total power; Indicates The total power required by each access user; It means that after the filter is amplified The signal-to-interference-noise ratio of the signal received by an access user.

[0067] In this embodiment, step S2 specifically includes the following steps:

[0068] S21. Calculated OR External information of a decoding module in the system, the external information including input external information and output external information;

[0069] The calculation formula of the input external information is:

[0070]

[0071] in, Represents the external input information of the decoding module, represents the integral variable, represents the exponential function, Represents the AWGN noise variance of the channel;

[0072] The calculation formula of the output external information is:

[0073]

[0074] in, Represents the output external information of the decoding module, represents the input codebook of the channel, represents the output codebook of the channel, represents the conditional probability density;

[0075] S22. Based on the input external information and the output external information, EXIT Char The analysis tool draws the curves of input and output external information and analyzes the convergence of the external information curve. The "path" between the two curves reflects the convergence of the external information. The larger the "path", the faster the information converges. The smaller the "path", that is, the two curves intersect in advance, the external information cannot converge. The convergence of the external information reflects the level of the bit error rate. EXIT Char Analysis tool, output bit error rate .

[0076] exist EXIT Char In the analysis tool, the calculation formula based on the output information of the decoding module is:

[0077]

[0078] And bit error rate The calculation formula is:

[0079]

[0080] Combining the two formulas, we can calculate the bit error rate ,in, represents the extrinsic information log-likelihood ratio.

[0081] In this embodiment, step S3 includes the following formula:

[0082] When the optimal power allocation problem is expressed in the formula: When the total power required is the minimum, the signal-to-interference-to-noise ratio level required by each access user is The calculation formula is:

[0083]

[0084] in, Indicates The signal-to-interference-and-noise ratio level required by each access user; Indicates the codeword length; represents the modulation dimension; Indicates the code rate of channel coding; It represents the normalized equivalent bandwidth of the signal; Indicates the bit error rate; Indicates the total number of all access users; Represents a finite-length achievable bit rate function The inverse function of , Denotes the continuous channel capacity of normalized bandwidth, ; represents the signal-to-interference-noise ratio; represents the channel divergence, ; represents the natural base, Gauss The inverse of a function.

[0085] In this embodiment, the calculation formula for the total power required by each access user in step S4 is:

[0086]

[0087] in, Indicates The total power required by each access user is Indicates The channel coefficient of each access user is represents the number of receiving antennas, represents the Frobenius norm.

[0088] By comparing the power allocation method of the present invention with the traditional method, the power allocation method of the present invention brings performance gain when the number of access users is 20 and 30. -4 When the number of users is 20, the power allocation scheme of the present invention brings about 1.2dB performance improvement. -5, when the number of users is 30, the power allocation scheme of the present invention brings about 1.5dB performance improvement. The multi-user power allocation method for the Internet of Things based on external information analysis proposed by the present invention has a lower bit error rate.

[0089] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for multi-user power allocation in the Internet of Things based on external information analysis, characterized in that: The following steps are involved: S1.According to NOMA The channel model of the system is analyzed to obtain the optimal power allocation problem; The optimal power allocation problem is expressed as follows: in, Indicates the total number of all access users; Indicates The signal-to-interference-and-noise ratio level required by each access user; Indicates the minimum total power; Indicates The total power required by each access user; It means that after the filter is amplified The signal-to-interference-to-noise ratio of the signal received by each access user; S2. Calculated NOMA External information of the decoding module in the system, using the external information of the decoding module EXIT Char The analysis tool is used to analyze the bit error rate, which specifically includes the following steps: S21. Calculated NOMA External information of a decoding module in the system, the external information including input external information and output external information; The calculation formula of the input external information is: in, Represents the external input information of the decoding module, represents the integral variable, represents the exponential function, represents the AWGN noise variance of the channel; The calculation formula of the output external information is: in, Represents the output external information of the decoding module, represents the input codebook of the channel, represents the output codebook of the channel, represents the conditional probability density; S22. Input external information and output external information EXIT Char Analysis tool, which draws the curves of input and output external information, analyzes the convergence of external information, and outputs the bit error rate; S3. Based on the optimal power allocation problem and the bit error rate, the signal to interference and noise ratio level required by each access user is calculated, including the following formula: When the optimal power allocation problem is expressed in the formula: When the total power required is the minimum, the signal-to-interference-to-noise ratio level required by each access user is The calculation formula is: in, Indicates the codeword length; represents the modulation dimension; Indicates the code rate of channel coding; It represents the normalized equivalent bandwidth of the signal; Indicates the bit error rate; Represents a finite-length achievable bit rate function The inverse function of , represents the continuous channel capacity of the normalized bandwidth; represents the signal-to-interference-noise ratio; represents the channel divergence; Gauss The inverse of a function; S4. According to the signal to noise ratio level required by each access user, the total power required by each access user is calculated to complete the user power allocation. The calculation formula for the total power required by each access user is: in, Indicates The total power required by each access user is Indicates The channel coefficient of each access user is represents the number of receiving antennas, represents the Frobenius norm.

2. The method for multi-user power allocation in the Internet of Things based on external information analysis according to claim 1 is characterized in that: The step S1 NOMA The channel model of the system includes NOMA Multiple access channel model and NOMA Broadcast channel model.

3. The method for multi-user power allocation in the Internet of Things based on external information analysis according to claim 2 is characterized in that: Said NOMA The multiple access channel model includes an access point and a user device, and the signal is transmitted from the user device to the access point; NOMA The calculation formula for the signal-to-interference-to-noise ratio of the user equipment signal received by the access point in the multiple access channel model is: in, express NOMA Multiple access channel model The signal-to-interference-to-noise ratio of the access user signal; Indicates the access point to Channel coefficient of each access user; express NOMA Multiple access channel model The signal transmission power of each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth; represents the Frobenius norm.

4. The method for multi-user power allocation in the Internet of Things based on external information analysis according to claim 2 is characterized in that: Said NOMA The broadcast channel model includes access points and user equipment, and the signal is transmitted from the access point to the user equipment; Said NOMA The calculation formula of the signal-to-interference-to-noise ratio of the signal received by the user equipment in the broadcast channel model is: in, express NOMA In the broadcast channel model The signal-to-interference-to-noise ratio of the signal received by each access user; Indicates the access point to Channel coefficient of each access user; express NOMA In the broadcast channel model, the access point is The signal transmission power allocated to each access user; represents the noise unilateral power spectral density; Indicates the signal bandwidth.

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