CN112911714B - NOMA two-user downlink decoding method based on power distribution - Google Patents

NOMA two-user downlink decoding method based on power distribution Download PDF

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CN112911714B
CN112911714B CN202110135622.5A CN202110135622A CN112911714B CN 112911714 B CN112911714 B CN 112911714B CN 202110135622 A CN202110135622 A CN 202110135622A CN 112911714 B CN112911714 B CN 112911714B
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CN112911714A (en
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陈平平
陈鹏飞
王聪
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Fuzhou University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/20—Control channels or signalling for resource management
    • H04W72/23—Control channels or signalling for resource management in the downlink direction of a wireless link, i.e. towards a terminal
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • 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

Abstract

The invention relates to a decoding method of NOMA two-user downlink based on power distribution, which comprises the following steps: step S1, the base station generates two user signals to be transmitted and carries out LDPC channel coding on the user signals; step S2, obtaining the optimal distribution of the power of two users by changing the fairness coefficient and the interruption probability value by adopting a power distribution optimization algorithm based on the fairness coefficient and the interruption probability; step S3, modulating the two user signals, the modulated user signals reach the receiving ends of user 1 and user 2 through the channel; and step S4, the receiving end adopts SIC strategy to decode different user signals. When the total power of the base station is not changed, the invention can obviously reduce the error rate of the system and has low complexity and high-efficiency decoding performance.

Description

NOMA two-user downlink decoding method based on power distribution
Technical Field
The invention relates to the technical field of wireless communication, in particular to a power allocation-based NOMA two-user downlink decoding method.
Background
Non-Orthogonal Multiple Access (NOMA) technology has been recognized as one of the key technologies in the fifth Generation (5th-Generation, 5G) wireless networks. Compared with conventional Orthogonal Multiple Access (OMA) technology, NOMA technology can provide higher spectral efficiency and system capacity with the same time and frequency through power domain multiplexing. However, the user signals received by the receiving end of the NOMA system are non-orthogonal superimposed, and there is serious interference between different user signals, which results in greatly increased decoding difficulty of the receiving end. In the NOMA system, the receiver utilizes Successive Interference Cancellation (SIC) technique to avoid co-channel Interference and thereby obtain the desired signal. However, practical wireless systems always use channel codes of limited length. Conventional SIC algorithms can introduce severe error propagation in NOMA systems, thereby compromising system performance. Meanwhile, the distribution of the base station to the user power also affects the interference degree among users and the decoding complexity and accuracy of a receiving end.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a decoding method for a NOMA two-user downlink based on power allocation, which can significantly reduce the error rate of a system when the total power of a base station is not changed, and has low complexity and high decoding performance.
In order to achieve the purpose, the invention adopts the following technical scheme:
a NOMA two-user downlink decoding method based on power allocation comprises the following steps:
step S1, the base station generates two user signals to be sent and carries out LDPC channel coding on the user signals;
step S2, obtaining the optimal distribution of the power of two users by changing the fairness coefficient and the interruption probability value by adopting a power distribution optimization algorithm based on the fairness coefficient and the interruption probability;
step S3, two user signals are modulated, and the modulated user signals reach the receiving ends of the user 1 and the user 2 through the channel;
and step S4, the receiving end adopts SIC strategy to decode different user signals.
Further, the power distribution optimization algorithm based on the fairness coefficient specifically includes:
(1) assuming that user 1 is a user close to the base station, that is, the channel condition of user 1 is good, and user 2 is a user far from the base station, that is, the channel condition of user 2 is poor, the throughput of users 1 and 2 can be expressed as:
Figure GDA0003585566910000021
Figure GDA0003585566910000022
the total throughput of the system is R ═ R1+R2
Defining a fairness coefficient F:
Figure GDA0003585566910000023
the fairness factor indicates the degree of sharing of system capacity among each user, and when F is closer to 1, the throughput among users is closer;
under the condition of meeting the fairness coefficient F' index given by the system, the total throughput of the system is maximized:
Figure GDA0003585566910000031
p is the total power transmitted by the base station;
user 1 and user 2 allocate power of P1And P2The power division factor is alpha, then
P1＝α×P，P2＝(1-α)×P
(2) Initializing power distribution factor alpha, fairness coefficient F, throughput R1、R2；
(3) Calculation of R1And R2The total throughput of the system, R, the fairness coefficient, F;
(4) judging whether the total throughput of the current system is the maximum value or not under the condition of meeting the index of the fairness coefficient;
(5) and (4) judging whether the power factor meets a preset constraint condition, if so, increasing progressively with a certain step length, and repeating the steps (2) - (4) until the optimal system throughput is found.
Further, the power distribution algorithm based on the outage probability specifically includes:
under the index of the maximum interruption probability, the throughput of the weakest user is maximum, and the optimization model is expressed in the following form:
Figure GDA0003585566910000032
Figure GDA0003585566910000041
Figure GDA0003585566910000042
wherein
Figure GDA0003585566910000043
ε (m) is the tolerable outage probability given by the system; m, j represent the decoding order (j < m), and m ═ 1 represents the first decoding. Pout(m) represents the outage probability for user m,
Figure GDA0003585566910000044
hmis the channel coefficient between the mth decoding user and the base station,
Figure GDA0003585566910000045
is the target rate, σ, for user j2Is the variance of the gaussian channel. M is the number of users, and if epsilon (1) is equal to epsilon (2), the optimization model is simplified as follows:
Figure GDA0003585566910000046
Figure GDA0003585566910000047
Figure GDA0003585566910000048
where t is a parameter of this set of nonlinear equations, M ═ 2, we get:
P2＝tρ(2)+t2ρ(1) (11)
P1＝tρ(1) (12)
the equation is a set of nonlinear equations, t is solved by using a Newton iteration method, and finally P can be calculated1、P2。
Further, the distribution strategy of the power distribution algorithm based on the outage probability specifically includes:
(1) initializing the interruption probability epsilon (m) given by the system and a coefficient lambda;
(2) calculating rho (1) and rho (2) according to the formula (10);
(3) when the total power of the base station is not changed, calculating a parameter t by using a Newton iteration method;
(4) calculating the power P according to the equations (11), (12)1、P2。
Further, the SIC strategy comprises a scheme N-SIC for treating interference as noise, a joint detection scheme J-SIC for treating interference signal modulation of users as auxiliary information, and a scheme E-SIC for exchanging signal external decoding information for two users.
Further, the J-SIC strategy specifically comprises: the interference signal is taken as auxiliary information, the interference signal is utilized to decode the signal, for the user 1 end, the interference elimination algorithm is firstly adopted to decode the user 2, then the decoding is carried out on the BP by the user 1, the demodulator needs to generate a channel log-likelihood ratio corresponding to each bit and transmits the channel log-likelihood ratio to the decoder, and the channel log-likelihood ratio LLR is used for decoding x2The following formula:
Figure GDA0003585566910000051
wherein the content of the first and second substances,
Figure GDA0003585566910000052
a set of all BPSK symbols representing user 1,
Figure GDA0003585566910000053
b2,jcorresponding to the jth bit of the user 2 bit stream, b2,j∈{0,1}；r1,jThe jth bit of the signal received by the receiver corresponding to the user 1; after LLR is calculated, executing BP decoding algorithm to recover x2(ii) a The channel log-likelihood ratio LLR is then recalculated for decoding x1The following formula:
Figure GDA0003585566910000054
b1,jcorresponding to the jth bit of the user 1 bit stream, b1,j∈{0,1}；
Figure GDA0003585566910000061
Indicating the jth bit of the signal after the interference information has been subtracted by the user 1 receiver. And after the LLR is calculated in the same way, executing BP decoding algorithm recovery.
Further, the E-SIC strategy specifically comprises: the user 1 end is provided with two decoders, the signal of the user 2 is decoded by the decoder 2, and the decoder 1 decodes the signal of the user 1; at the user 2 end, only the decoder 2 is needed to directly decode the signal itself; the external information output by the decoder 1 and the decoder 2 is exchanged between the decoder 1 and the decoder 2 at the user 1 side;
in each iteration, the user 2 signal must be decoded first; then, the associated extrinsic information generated by the variable node of the decoder 2 is fed back to the decoder 1 as a priori information; followed by decoding iterations of decoder 1; finally, the associated soft output generated by the variable node of the decoder 1 is fed back to the decoder 2 as prior information, and one iteration is completed;
and repeating iteration until the decoder check is successful or the agreed loop condition is not met, and writing the LLR of the decoder 2 at the user 1 end as follows:
Figure GDA0003585566910000062
Figure GDA0003585566910000063
represents extrinsic information about the user 1 that the decoder 2 gets from the decoder 1;
the LLR for user 1 decoder 1 is written as:
Figure GDA0003585566910000064
wherein the content of the first and second substances,
Figure GDA0003585566910000065
s represents the set of all BPSK symbols for user 2, s ∈ { -1, +1 }. Pr (Pr) of2(s) indicates extrinsic information about user 2 that decoder 1 gets from decoder 2, performing q such loop iterations before finally making bit decisions.
Compared with the prior art, the invention has the following beneficial effects:
compared with a decoding scheme without considering power optimization, the improved algorithm combining power allocation and interference elimination can obviously reduce the error rate of a system when the total power of a base station is unchanged, and has low complexity and high-efficiency decoding performance.
Drawings
Fig. 1 is a schematic diagram of a downlink model of two NOMA users in the embodiment of the present invention;
FIG. 2 is a system architecture diagram of an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a power distribution algorithm based on a fairness coefficient in an embodiment of the present invention;
FIG. 4 is a schematic flow chart of a power distribution algorithm based on interrupt probability according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a J-SIC detection framework adopted by the user 1 in the embodiment of the present invention;
FIG. 6 is a schematic diagram of an E-SIC detection framework adopted by the user 1 in the embodiment of the present invention;
FIG. 7 is a diagram of error performance of user 1 adopting N-SIC, J-SIC, and E-SIC schemes, respectively, in an embodiment of the present invention;
fig. 8 is an error performance diagram after user 1 adopts the fairness coefficient-based power distribution optimization algorithm in the embodiment of the present invention;
fig. 9 is a diagram of error performance after the user 1 adopts the power distribution optimization algorithm based on the outage probability in the embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 1, the present embodiment considers a system model of the downlink of two NOMA users. Both a base station and two users are equipped with a single antenna. Channel state information is well known at the base station and the user. User 1 is a user close to the base station, i.e., user 1 has good channel conditions. User 2 is a user that is far away from the base station, i.e., user 2 has poor channel conditions.
Referring to fig. 2, the present embodiment provides a decoding method for a NOMA two-user downlink based on power allocation, including the following steps:
step S1, the base station generates bit sequences to be sent to user 1 and user 2, and then carries out LDPC channel coding on the user signals;
step S2, obtaining the optimal distribution of the power of two users by changing the fairness coefficient and the interruption probability value by adopting a power distribution optimization algorithm based on the fairness coefficient and the interruption probability;
step S3, BPSK modulation is carried out on the two user signals, and the modulated user signals reach receiving ends of a user 1 and a user 2 through a channel;
and step S4, the receiving end adopts SIC strategy to decode different user signals.
In this embodiment, as shown in fig. 4, the power distribution optimization algorithm based on the fairness coefficient specifically includes:
the throughput of users 1, 2 is expressed as:
Figure GDA0003585566910000081
Figure GDA0003585566910000082
the total throughput of the system is R ═ R1+R2
Defining a fairness coefficient F:
Figure GDA0003585566910000091
the fairness factor indicates the degree of sharing of system capacity among each user, and when F is closer to 1, the throughput among users is closer;
under the condition of meeting the fairness coefficient F' index given by the system, the total throughput of the system is maximized:
Figure GDA0003585566910000092
p is the total power transmitted by the base station;
setting the power allocated to user 1 and user 2 to P1And P2The power division factor is alpha, then P1＝α×P，P2＝(1-α)×P
(2) Initializing a power distribution factor alpha, a fairness factor F, a throughput R1、R2；
(3) Calculation of R1And R2The total throughput of the system, R, the fairness coefficient, F;
(4) judging whether the total throughput of the current system is the maximum value or not under the condition of meeting the index of the fairness coefficient;
(5) and (5) judging whether the power factor meets a preset constraint condition, if so, increasing progressively with a certain step length, and repeating the steps (2) - (4) until the optimal system throughput is found.
In this embodiment, as shown in fig. 3, the power distribution algorithm based on the outage probability specifically includes:
under the index of the maximum interruption probability, the throughput of the weakest user is maximum, and the optimization model is expressed in the following form:
Figure GDA0003585566910000101
Figure GDA0003585566910000102
Figure GDA0003585566910000103
wherein
Figure GDA0003585566910000104
ε (m) is the tolerable outage probability given by the system; m, j represent the decoding order (j < m), and m ═ 1 represents the first decoding. Pout(m) represents the outage probability for user m,
Figure GDA0003585566910000105
hm is the channel coefficient between the m-th decoding user and the base station,
Figure GDA0003585566910000106
is the target rate, σ, for user j2Is the variance of the gaussian channel. M is the number of users, and if epsilon (1) is equal to epsilon (2), the optimization model is simplified as follows:
Figure GDA0003585566910000107
Figure GDA0003585566910000108
Figure GDA0003585566910000109
where t is a parameter of this set of nonlinear equations, M ═ 2, we get:
P2＝tρ(2)+t2ρ(1) (11)
P1＝tρ(1) (12)
the equation is a set of nonlinear equations, t is solved by using a Newton iteration method, and finally P can be calculated1、P2。
Preferably, the distribution strategy of the power distribution algorithm based on the outage probability specifically includes:
(1) initializing the interruption probability epsilon (m) given by the system and a coefficient lambda;
(2) calculating rho (1) and rho (2) according to the formula (10);
(3) when the total power of the base station is not changed, calculating a parameter t by using a Newton iteration method;
(4) calculating power P according to equations (11), (12)1、P2。
In the embodiment, the SIC strategy comprises a scheme N-SIC for treating interference as noise, a joint detection scheme J-SIC for treating interference signal modulation of users as auxiliary information, and a scheme E-SIC for exchanging signal external decoding information for two users. For the N-SIC and J-SIC strategies, the user 1 end close to the base station firstly decodes the user 2 signal far away from the base station, then subtracts the user 2 signal from the total received signal, and then decodes the user 1 signal. It is for the user 2 receiving end to decode the signal itself directly. For the E-SIC strategy, the user 1 and the user 2 realize decoding by exchanging external information output by a decoder and circularly iterating. All the three strategies have corresponding channel Likelihood Ratio (Log-Likelihood Ratio, LLR) deduced, and then, the user signal decoding can be realized by adopting a BP decoding algorithm.
Preferably, the J-SIC strategy is specifically as follows: the interference signal is taken as auxiliary information, the interference signal is used for decoding the signal, for the user 1 end, the interference elimination algorithm is firstly adopted to decode the user 2, then the decoding algorithm of the user 1 is adopted to decode the BP, the demodulator needs to generate a channel log-likelihood ratio corresponding to each bit and transmits the channel log-likelihood ratio to the decoder, and the channel log-likelihood ratio LLR is used for decoding x2The following formula:
Figure GDA0003585566910000111
wherein the content of the first and second substances,
Figure GDA0003585566910000121
a set of all BPSK symbols representing user 1,
Figure GDA0003585566910000122
b2,jcorresponding to the jth bit of the user 2 bit stream, b2,j∈{0,1}；r1,jThe jth bit of the signal received by the receiver corresponding to the user 1; after LLR is calculated, executing BP decoding algorithm to recover x2(ii) a The channel log-likelihood ratio LLR is then recalculated for decoding x1The following formula:
Figure GDA0003585566910000123
b1,jcorresponding to the jth bit of the user 1 bit stream, b1,j∈{0,1}；
Figure GDA0003585566910000124
Indicating the jth bit of the signal after the interference information has been subtracted by the user 1 receiver. And after the LLR is calculated in the same way, executing a BP decoding algorithm for recovery.
In this embodiment, the E-SIC policy specifically includes: the user 1 end is provided with two decoders, the signal of the user 2 is decoded by the decoder 2, and the decoder 1 decodes the signal of the user 1; at the user 2 end, only the decoder 2 is needed to directly decode the signal itself; the external information output by the decoder 1 and the decoder 2 is exchanged between the decoder 1 and the decoder 2 at the user 1 side;
in each iteration, the user 2 signal must be decoded first; then, the associated extrinsic information generated by the variable node of the decoder 2 is fed back to the decoder 1 as a priori information; followed by decoding iterations of decoder 1; finally, the associated soft output generated by the variable node of the decoder 1 is fed back to the decoder 2 as prior information, and one iteration is completed;
and repeating iteration until the decoder check is successful or the agreed loop condition is not met, and writing the LLR of the decoder 2 at the user 1 end as follows:
Figure GDA0003585566910000131
Figure GDA0003585566910000134
indicating that decoder 2 is derived from decoder 1, usingExternal information of the user 1;
the LLR for user 1 decoder 1 is written as:
Figure GDA0003585566910000132
wherein the content of the first and second substances,
Figure GDA0003585566910000133
s represents the set of all BPSK symbols for user 2, s ∈ { -1, +1 }. Pr (Pr)2(s) indicates extrinsic information about user 2 that decoder 1 gets from decoder 2, performing q such loop iterations before finally making bit decisions.
Referring to fig. 7-9, in this embodiment, fig. 7 is a bit error rate simulation diagram of the scheme of only adopting the interference cancellation algorithms N-SIC, J-SIC and E-SIC. It can be seen that the E-SIC algorithm has the lowest error rate, the second order of J-SIC and the worst N-SIC. Fig. 8 and fig. 9 both take optimization based on the E-SIC algorithm as an example. Fig. 8 is a diagram of the simulation results of the ber after the improved algorithm of the joint power allocation-interference cancellation of the present invention is adopted, wherein the power allocation algorithm adopts an optimization scheme based on a Fairness coefficient Fairness. Three curves with fairness coefficients F of 0.80, 0.85 and 0.9 are given, and it can be seen that the bit error rate reaches 10-4And when the error rate is even lower, the error rate of the E-SIC interference elimination algorithm for merging power distribution is obviously reduced. Fig. 9 is a bit error rate simulation result after an optimization scheme based on the interrupt probability is adopted, and three curves of 0.02, 0.05 and 0.2 of the interrupt probability outage are given. And similarly, the performance of the optimized E-SIC interference elimination algorithm is greatly improved. Compared with a decoding scheme without considering power optimization, the improved algorithm of joint power allocation-interference cancellation provided by the invention can obviously reduce the error rate of a system when the total power of a base station is unchanged, and has low complexity and high-efficiency decoding performance.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.

Claims (5)

1. A NOMA two-user downlink decoding method based on power allocation is characterized by comprising the following steps:
step S1, the base station generates two user signals to be sent and carries out LDPC channel coding on the user signals;
step S2, obtaining the optimal distribution of the power of two users by changing the fairness coefficient and the interruption probability value by adopting a fairness coefficient-based power distribution optimization algorithm or an interruption probability-based power distribution optimization algorithm;
step S3, modulating the two user signals, the modulated user signals reach the receiving ends of user 1 and user 2 through the channel;
step S4, the receiving end adopts SIC strategy to decode different user signals;
the SIC strategy comprises a scheme N-SIC for treating interference as noise, a joint detection scheme J-SIC for modulating interference signals of users as auxiliary information, and a scheme E-SIC for exchanging external decoding information of signals for two users;
the J-SIC strategy specifically comprises the following steps: the interference signal is taken as auxiliary information, the interference signal is utilized to decode the signal, for the user 1 end, the interference elimination algorithm is firstly adopted to decode the user 2, then the decoding is carried out on the BP by the user 1, the demodulator needs to generate a channel log-likelihood ratio corresponding to each bit and transmits the channel log-likelihood ratio to the decoder, and the channel log-likelihood ratio LLR is used for decoding x2The following formula:
Figure FDA0003604651660000021
wherein the content of the first and second substances,
Figure FDA0003604651660000022
Figure FDA0003604651660000023
a set of all BPSK symbols representing user 1,
Figure FDA0003604651660000024
b2,jcorresponding to the jth bit of the user 2 bit stream, b2,j∈{0,1}；r1,jThe jth bit of the signal received by the receiver corresponding to the user 1; after LLR is calculated, executing BP decoding algorithm to recover x2(ii) a The channel log-likelihood ratio LLR is then recalculated for decoding x1The following formula:
Figure FDA0003604651660000025
b1,jcorresponding to the jth bit of the user 1 bit stream, b1,j∈{0,1}；
Figure FDA0003604651660000026
Represents the j bit of the signal after the interference information is subtracted by the receiver of the user 1; after LLR is calculated in the same way, BP decoding algorithm recovery is executed; p is1And P2Power allocated for user 1 and user 2.
2. The method of claim 1, wherein the power allocation based power allocation optimization algorithm is specifically:
(1) let user 1 be a user close to the base station, that is, user 1 has good channel condition, user 2 be a user far from the base station, that is, user 2 has poor channel condition, and the throughput of users 1 and 2 is expressed as:
Figure FDA0003604651660000027
Figure FDA0003604651660000028
the total throughput of the system is R ═ R1+R2
Defining a fairness coefficient F:
Figure FDA0003604651660000031
the fairness factor indicates the degree of sharing of system capacity among each user, and when F is closer to 1, the throughput among users is closer;
under the condition of meeting the fairness coefficient F' index given by the system, the total throughput of the system is maximized:
maxmize R
Figure FDA0003604651660000032
p is the total power transmitted by the base station;
user 1 and user 2 are allocated power P1And P2The power division factor is alpha, then P1＝α×P，P2＝(1-α)×P
(2) Initializing a power distribution factor alpha, a fairness factor F, a throughput R1、R2；
(3) Calculating R1And R2Total throughput of the system, R, fairness factor, F;
(4) judging whether the total throughput of the current system is the maximum value or not under the condition of meeting the index of the fairness coefficient;
(5) and (4) judging whether the power distribution factor meets a preset constraint condition, if so, increasing progressively with a certain step length, and repeating the steps (2) - (4) until the optimal system throughput is found.
3. The method for decoding a downlink of NOMA two users based on power allocation as claimed in claim 2, wherein the power allocation algorithm based on outage probability specifically comprises:
under the index of the maximum interruption probability, the throughput of the weakest user is maximum, and the optimization model is expressed in the following form:
Figure FDA0003604651660000041
Figure FDA0003604651660000042
Figure FDA0003604651660000043
Figure FDA0003604651660000044
wherein
Figure FDA0003604651660000045
ε (m) is the tolerable outage probability given by the system; m, j represents the decoding order j < m, and m ═ 1 represents the first decoding; p isout(m) represents the outage probability for user m,
Figure FDA0003604651660000046
hmis the channel coefficient between the mth decoding user and the base station,
Figure FDA0003604651660000047
is the target rate, σ, for user j2Is the variance of the gaussian channel; m is the number of users, and if epsilon (1) is equal to epsilon (2), the optimization model is simplified as follows:
Figure FDA0003604651660000048
Figure FDA0003604651660000049
Figure FDA00036046516600000410
where t is a parameter of the set of nonlinear equations, and M-2, yields:
P2＝tρ(2)+t2ρ(1) (11)
P1＝tρ(1) (12)
the equation is a set of nonlinear equations, t is solved by using a Newton iteration method, and finally P can be calculated1、P2。
4. The method of claim 3, wherein the allocation strategy of the power allocation algorithm based on outage probability is specifically:
(1) initializing a given interruption probability epsilon (m) and a coefficient lambda (m) of a system;
(2) calculating rho (1) and rho (2) according to the formula (10);
(3) when the total power of the base station is not changed, calculating a parameter t by using a Newton iteration method;
(4) calculating the power P according to the equations (11), (12)1、P2。
5. The method of claim 1, wherein the E-SIC strategy is specifically as follows: the user 1 end is provided with two decoders, the signal of the user 2 is decoded by the decoder 2, and the decoder 1 decodes the signal of the user 1; at the user 2 end, only the decoder 2 is needed to directly decode the signal itself; the external information output by the decoder 1 and the decoder 2 is exchanged between the decoder 1 and the decoder 2 at the user 1 side;
in each iteration, the user 2 signal must be decoded first; then, the associated extrinsic information generated by the variable node of the decoder 2 is fed back to the decoder 1 as a priori information; followed by decoding iterations of decoder 1; finally, the associated soft output generated by the variable node of the decoder 1 is fed back to the decoder 2 as prior information, and one iteration is completed;
and repeating iteration until the decoder check is successful or the agreed loop condition is not met, and writing the LLR of the decoder 2 at the user 1 end as follows:
Figure FDA0003604651660000051
Figure FDA0003604651660000052
represents extrinsic information about the user 1 that the decoder 2 gets from the decoder 1; the LLR for user 1 decoder 1 is written as:
Figure FDA0003604651660000061
wherein the content of the first and second substances,
Figure FDA0003604651660000062
s represents the set of all BPSK symbols for user 2, s ∈ { -1, +1 }; pr (Pr) of2(s) indicates extrinsic information about user 2 that decoder 1 gets from decoder 2, performing q such loop iterations before finally making bit decisions.
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