CN109600817B - User error code performance analysis method of cooperative NOMA system based on user relay - Google Patents

User error code performance analysis method of cooperative NOMA system based on user relay Download PDF

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CN109600817B
CN109600817B CN201910033045.1A CN201910033045A CN109600817B CN 109600817 B CN109600817 B CN 109600817B CN 201910033045 A CN201910033045 A CN 201910033045A CN 109600817 B CN109600817 B CN 109600817B
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李素月
王安红
武迎春
李东红
王海东
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Shanxi Xuanzhong Environmental Protection Equipment Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/022—Site diversity; Macro-diversity
    • H04B7/026—Co-operative diversity, e.g. using fixed or mobile stations as relays
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences

Abstract

The invention discloses a cooperative NOMA system multi-user error code performance analysis method based on user relay, belonging to the field of wireless communication signal processing and transmission, and comprising the specific steps that a base station sequences the strength of users according to large-scale fading, selects the strongest user as a relay, and transmits multi-user superposed signals to the strong user by utilizing NOMA technology; the strong user sends a signal to the weak user in a mode of amplifying and forwarding AF or decoding and forwarding DF; then, calculating the sequence statistic of the strong user channel according to a sequence statistic theory, and deducing closed PEP expressions analyzed by the strong user and the weak user respectively according to the received signals of different users by using mathematical theories such as probability theory, calculus and the like; and finally, calculating the BER joint bound of each user based on a theoretical PEP expression to complete system performance analysis. The method is more suitable for the situation that the exact BER closed expression cannot be obtained by adopting the complex nonlinear multi-user detection.

Description

User error code performance analysis method of cooperative NOMA system based on user relay
Technical Field
The invention belongs to the key technical field of fifth-generation wireless communication, is particularly suitable for a wireless communication power domain cooperative non-orthogonal multiple access (NOMA) system, and mainly introduces a user error code performance analysis method of a cooperative NOMA system based on user relay.
Background
The fifth generation mobile communication includes many important physical layer technologies, such as massive MIMO, millimeter wave communication, hybrid digital-analog precoding, non-orthogonal multiple access, etc. Among them, the main advantages of non-orthogonal multiple access (NOMA) are that it can implement high frequency spectrum efficiency and large-scale user connection, and can service several users to simultaneously communicate with same frequency. The power domain NOMA refers to a NOMA base station which adopts different power coefficients to transmit signals by superposing signals of a plurality of users, and the distribution of the power coefficients needs to meet the requirements of user fairness or QoS quality of different users.
In order to enhance the reliability of the NOMA system, in recent years, many researchers have focused on collaborating NOMA. According to different collaboration modes, generally, two collaboration schemes mainly exist: dedicated relay cooperation and user cooperation. The former uses one or more fixed and special relays to forward NOMA information, and the latter considers that a user with good channel state (strong user) is selected to serve as a relay to forward NOMA information. The strong user needs to recover the information of the strong user while serving the communication of other weak users, so that the strong user needs to consume more energy resources. It is therefore desirable to give strong users the ability to collect rf electromagnetic wave energy in order to encourage strong user cooperation. Therefore, cooperative NOMA with both energy harvesting and information transfer (SWIPT) is also a relatively practical and popular research direction today.
For the NOMA system, except the user with the largest power distribution coefficient, other users recover the information of the user by utilizing a nonlinear multi-user detection technology, namely Serial Interference Cancellation (SIC). The processing of SIC makes accurate bit error rate analysis difficult for NOMA systems to perform. While the current literature on NOMA system performance studies focuses almost mostly on evaluating outage probability, and rate or spectral efficiency. Actually, the analysis and research of the error code performance of different users of the NOMA system are necessary, the invention starts with the Paired Error Probability (PEP) performance to analyze the error code performance of the NOMA, the paired PEP is used as the performance upper limit of the BER, a useful reference is provided for the system error code performance, and on the basis, the progressive PEP can be further deduced to analyze the achievable diversity gain. Therefore, the invention provides a NOMA error performance analysis method based on user relay.
Disclosure of Invention
For the user cooperation NOMA system, most of the systems are researched on the interrupt probability performance, and the research on the error performance analysis is almost not available, particularly the error performance analysis is carried out by combining the energy collection and transmission technology. Because the processing of SIC makes accurate bit error rate BER analysis of NOMA systems difficult, especially considering the effects of imperfect interference cancellation. The invention aims to provide a NOMA system user performance analysis method based on user relay and energy collection, which utilizes Monte Carlo verification derived and analyzed PEP closed expression of each user to explore the influence of an energy collection factor on error code performance.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a NOMA system multi-user performance analysis method based on user relay is realized according to the following steps:
s1, base station BS sequences the user intensity according to large scale fading, selects the strongest user as relay, the base station determines the power distribution coefficient by NOMA technique, transmits multi-user superimposed signal to the strong user, the base station transmits the superimposed signal
Figure GDA0003043848860000021
To the optimal relay, where s1,s2Respectively representing strong and weak users, alpha1And alpha2Represents the power distribution coefficients of strong and weak users, and alpha2+α1＝1，α2＞α1，PsRepresenting the total power of the base station;
s2, selecting a strong user as a relay, and performing energy collection and information reception by the strong user;
s3, the strong user 1 sends information to the weak user in a mode of amplifying and forwarding AF or decoding and forwarding DF by using the collected energy; the user has no energy, the energy receiver of the strong user collects the electromagnetic wave energy from the base station, and the collected energy is used for helping the weak user to forward the signal in an Amplifying Forwarding (AF) or Decoding Forwarding (DF) mode, and the AF amplification factor
Figure GDA0003043848860000022
Energy harvesting P taking into account averaging1＝ηρσ2PsI.e. the amplification factor is independent of the instantaneous state of the channel and the variance σ of the channel from the base station to the strong user2Variance of noise
Figure GDA0003043848860000023
And the energy harvesting power factor p. For DF, perfect decoding and instantaneous energy collection can be considered, i.e. the energy collected by a strong user is
Figure GDA0003043848860000024
S4, calculating the sequence statistic of the strong user channel according to the sequence statistic theory, and deducing closed PEP expressions analyzed by the strong user and the weak user respectively according to the received signals of different users by using the probability theory and the mathematical theory of calculus;
and S5, calculating the BER joint bound of each user based on a theoretical PEP expression, and completing system performance analysis.
Further, the strong user acts as a relay in S2 and has energy collection and information transmission functions, and the steps of information reception and performance analysis for the strong user are as follows:
s201, the information receiver of the strong user 1 processes the information sent by the base station, the SIC is used for decoding the information of the weak user 2 first, the interference of the user 2 is subtracted from the receiving expression of the SIC, and the information of the strong user 1 is recovered;
s202, deducing an error code Q function expression of a conditional PEP of the strong user under a Rayleigh fading channel according to the receiving expression of the strong user, and then obtaining an analytic PEP expression of the strong user by utilizing mathematical processing such as probability theory, calculus and the like based on a sequence statistic theory, wherein specifically, an information receiving signal of the strong user is
Figure GDA0003043848860000025
Thus, a conditional PEP expression for a strong user can be obtained:
Figure GDA0003043848860000031
wherein
Figure GDA0003043848860000032
The strong user is selected by the base station through sequencing, and the channel sequence statistic of the strong user is
Figure GDA0003043848860000033
Wherein, ω is1＝|hs1I represents the channel amplitude from the base station to the strong user 1, and unconditional analysis PEP of the strong user can be obtained through integral operation
Figure GDA0003043848860000034
Thus, the strong user-final closed PEP expression is
Figure GDA0003043848860000035
Further, S4 derives an analytic PEP expression of the weak user in the rayleigh fading channel according to the received signal expression of the weak user, where the derivation process mainly includes the following two cases:
s401, AF condition, condition PEP of weak user can be calculated as
Figure GDA0003043848860000036
Wherein the content of the first and second substances,
Figure GDA0003043848860000037
Figure GDA0003043848860000038
can be further expressed as
Figure GDA0003043848860000039
Wherein
Figure GDA00030438488600000310
Figure GDA00030438488600000311
And (3) solving double integrals by using the sequence statistic of the strong user channel to obtain an analyzed PEP closed expression:
Figure GDA00030438488600000312
s402, DF, weak user PEP probability under given channel condition is
Figure GDA00030438488600000313
Wherein
Figure GDA00030438488600000314
Next, using double integration, unconditional PEP expression is obtained
Figure GDA0003043848860000041
Wherein A is2＝2，
Figure GDA0003043848860000042
And
Figure GDA0003043848860000043
Kv(. cndot.) represents a modified Bessel function of order v of the second kind.
The formula derivation of the present invention is exemplified for the case of two users, and the method is naturally applicable to the case of multiple users.
The invention provides a user performance analysis method of a cooperative NOMA system based on user relay, and the considered cooperative NOMA system user can be used as the relay and has the functions of energy collection and information receiving. The method has the advantages that an exact analysis PEP expression is deduced by using mathematical theories such as probability theory, calculus and the like, and simulation results show that the theoretical PEP is consistent with the corresponding Monte Carlo simulation performance, so that the method can be used for analyzing the error code performance of the cooperative NOMA system and simultaneously provides theoretically valuable references for determining parameters such as the user power distribution coefficient, the energy collection power factor and the like of the NOMA system. The proposed error code analysis method of the cooperative NOMA system is low in complexity, and the influence of error code performance and parameter selection of the NOMA system can be conveniently known by using analyzed PEP closed expression.
Drawings
FIG. 1 is a general flow chart of an embodiment of the present invention.
Fig. 2 is a BER joint bound curve of a strong user and a weak user of the cooperative NOMA system.
Fig. 3 shows the influence of the energy collection power factor ρ on the error performance of each user.
Fig. 4 is a comparison of simulated and resolved error performance of weak user monte carlo under AF and DF.
Detailed Description
In order to make the objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
As shown in fig. 1, the method for analyzing user performance of a cooperative NOMA system of a user relay according to the present invention is implemented according to the following steps:
s1, the base station sequences the user states according to large-scale fading or other methods, selects the strong users as relays, distributes power coefficients required to be superposed by each user, and then transmits superposed signals to the strong users. Weak users are assigned a relatively high power coefficient compared to strong users. The base station adds the signals
Figure GDA0003043848860000044
To the optimal relay, where s1,s2Respectively representing strong and weak users, alpha1And alpha2Represents the power distribution coefficients of strong and weak users, and alpha2+α1＝1，α2＞α1，PsTo representThe total power of the base station.
S2, the strong user considered by the invention can be used as a relay and has the functions of energy collection and information transmission, and the steps of information receiving and performance analysis about the strong user are as follows:
s201, the information receiver of the strong user 1 processes the information sent by the base station, the SIC is used for decoding the information of the weak user 2 first, the interference of the user 2 is subtracted from the receiving expression of the SIC, and the information of the strong user 1 is recovered.
S202, deducing an error code Q function expression of the conditional PEP of the strong user under the Rayleigh fading channel according to the receiving expression of the strong user. And then, based on the order statistic theory, obtaining an analysis PEP expression of the strong user by utilizing mathematical processing such as probability theory, calculus and the like. Specifically, the information receiving signal of the strong user is
Figure GDA0003043848860000051
Thus, a conditional PEP expression for a strong user can be obtained:
Figure GDA0003043848860000052
wherein
Figure GDA0003043848860000053
The strong user is selected by the base station through sequencing, and the channel sequence statistic of the strong user is
Figure GDA0003043848860000054
Wherein, ω is1＝|hs1I represents the channel amplitude from the base station to the strong user 1, and unconditional analysis PEP of the strong user can be obtained through integral operation
Figure GDA0003043848860000055
Thus, the strong user-final closed PEP expression is
Figure GDA0003043848860000056
S3, the user does notEnergy, the energy receiver of strong user collects the electromagnetic wave energy from the base station, and uses the collected energy to forward the signal to the weak user in the mode of Amplification Forwarding (AF) or Decoding Forwarding (DF), AF amplification factor
Figure GDA0003043848860000057
Energy harvesting P taking into account averaging1＝ηρσ2PsI.e. the amplification factor is independent of the instantaneous state of the channel and the variance σ of the channel from the base station to the strong user2Variance of noise
Figure GDA0003043848860000058
And the energy harvesting power factor p. For DF, perfect decoding and instantaneous energy collection can be considered, i.e. the energy collected by a strong user is
Figure GDA0003043848860000059
S4, deducing an analytic PEP expression of the weak user under the Rayleigh fading channel according to the receiving signal expression of the weak user, wherein the deduction process mainly comprises the following two conditions:
s401, AF condition, condition PEP of weak user can be calculated as
Figure GDA0003043848860000061
Wherein the content of the first and second substances,
Figure GDA0003043848860000062
Figure GDA0003043848860000063
can be further expressed as
Figure GDA0003043848860000064
Wherein
Figure GDA0003043848860000065
Figure GDA0003043848860000066
And (3) solving double integrals by using the sequence statistic of the strong user channel to obtain an analyzed PEP closed expression:
Figure GDA0003043848860000067
s402, DF, weak user PEP probability under given channel condition is
Figure GDA0003043848860000068
Wherein
Figure GDA0003043848860000069
Next, using double integration, unconditional PEP expression is obtained
Figure GDA00030438488600000610
Wherein A is2＝2，
Figure GDA00030438488600000611
And
Figure GDA00030438488600000612
Kv(. cndot.) represents a modified Bessel function of order v of the second kind. The formula derivation of the present invention is exemplified for the case of two users, and the method is naturally applicable to the case of multiple users.
The invention analyzes and deduces the error code performance of the NOMA system, and figure 2 shows the error code performance (solid line) of Monte Carlo simulation and the analyzed error code performance (different symbols represent the strong user and the weak user) of the strong user and the weak user under different energy collection power factors rho. The ordinate of the graph is an error performance index, which is obtained by averaging PEPs under different interference conditions. It can be seen that the analytical PEP theoretical expression of each user is completely consistent with its corresponding monte carlo simulation performance. At high snr, it can be seen from the slope of the curve that strong users have higher diversity gain than weak users, although they are assigned smaller power coefficients. The energy collection power factor is from ρ 0.3 to ρ 0.6, so that the error performance of the strong user is reduced and the error performance of the weak user is improved.
Fig. 3 shows the effect of the energy harvesting power factor p on the user error performance. The error code performance of the strong user is gradually reduced along with the increase of the power factor rho, the error code performance of the weak user is firstly enhanced, and slowly becomes worse after rho is greater than 0.6, so the comprehensive performance of the NOMA system user should be considered in the selection of rho.
Fig. 4 shows the performance of a weak user under different relay schemes AF and DF. Due to error code derivation under the DF protocol, the strong user is supposed to decode the information of the weak user perfectly, and the ideal hypothesis makes the error code performance under the DF obviously better than that under the AF. However, at high signal-to-noise ratios, DF and AF exhibit the same diversity gain. In addition, the figure also demonstrates that the error performance of the Monte Carlo simulation and the analysis derived by the present invention are completely consistent.
The above embodiments are only for illustrating the invention and not for limiting the invention, and those skilled in the art can make various changes and modifications without departing from the principle and scope of the invention, so that all equivalent technical solutions also belong to the scope of the invention, and the scope of the invention should be defined by the claims.

Claims (1)

1. A cooperative NOMA system multi-user error code performance analysis method based on user relay is characterized in that: the method is realized according to the following steps:
s1, base station BS sequences the user intensity according to large scale fading, selects the strongest user as relay, the base station determines the power distribution coefficient by NOMA technique, transmits multi-user superimposed signal to the strong user, the base station transmits the superimposed signal
Figure FDA0003084744020000011
To the optimal relay, where s1,s2Signals transmitted, alpha, representing strong and weak users respectively1And alpha2Represents the power distribution coefficients of strong and weak users, and alpha2+α1＝1，α2＞α1，PsRepresenting the total power of the base station;
s2, selecting a strong user as a relay, and performing energy collection and information reception by the strong user; calculating the order statistic of the strong user channel according to the order statistic theory, deducing the analytic closed PEP expression of the strong user according to the received signal of the strong user by using the mathematical theory of probability theory and calculus, wherein the information receiving and performance analysis steps about the strong user are as follows:
s201, the information receiver of the strong user 1 processes the information sent by the base station, the SIC is used for decoding the information of the weak user 2 first, the interference of the user 2 is subtracted from the receiving expression of the SIC, and the information of the strong user 1 is recovered;
s202, deducing an error code Q function expression of a conditional PEP of the strong user under a Rayleigh fading channel according to the receiving expression of the strong user, and then obtaining an analytic PEP expression of the strong user by utilizing mathematical processing such as probability theory, calculus and the like based on a sequence statistic theory, wherein specifically, an information receiving signal of the strong user is as follows:
Figure FDA0003084744020000012
thus, a conditional PEP expression for a strong user can be obtained:
Figure FDA0003084744020000013
wherein, ω is1＝|hs1I represents the channel amplitude from the base station BS to the strong user 1, obeying Rayleigh distribution, hs1Represents the channel fading gain, h, from the base station BS to user 1s1Obedience mean 0 and variance σ2Complex gaussian distribution of (a)2Which represents the variance of the channel and is,
Figure FDA0003084744020000014
representing equivalent noise;
β1the gain coefficients are received for user 1 containing the pair-wise error,
Figure FDA0003084744020000015
coefficient of performance
Figure FDA0003084744020000016
Where ρ ∈ (0,1) denotes an energy collection power factor, ρ' ═ 1 — ρ denotes an information transfer power factor, and the pair-wise error of user 1
Figure FDA0003084744020000017
Figure FDA0003084744020000018
Error signal indicating detected strong user, interference cancellation error of user 2
Figure FDA0003084744020000019
Figure FDA00030847440200000110
Error signal, σ, representing detected weak usersnIs the standard deviation of zero mean gaussian white noise,
Figure FDA0003084744020000021
representing the operation of taking a real part;
user 1 received noise standard deviation
Figure FDA0003084744020000022
The strong user is selected by the base station through sequencing, and the channel sequence statistic of the strong user is as follows:
Figure FDA0003084744020000023
wherein the coefficient of binomial equation
Figure FDA0003084744020000024
Through integral operation, unconditional analysis PEP of strong users can be obtained as follows:
Figure FDA0003084744020000025
thus, the strong user final closed PEP expression is:
Figure FDA0003084744020000026
s3, the strong user 1 collects energy of the signal from the BS and helps the weak user to forward information based on the collected energy;
s4, the weak user receives the forwarding signal from the strong user, two forwarding modes of amplifying forwarding AF and decoding forwarding DF are considered, the analytic closed PEP expression of the weak user in the AF or DF mode is deduced according to the received signal of the weak user by using the probability theory and the mathematical theory of calculus, and the deduction process mainly comprises the following two conditions:
s401, in the AF situation, the condition PEP of the weak user can be calculated as follows:
Figure FDA0003084744020000027
wherein the content of the first and second substances,
Figure FDA0003084744020000028
AF amplification factor
Figure FDA0003084744020000029
Strong user 1 collected energyQuantity P1＝ηρσ2PsWhere eta to (0,1)]Represents the energy conversion efficiency;
can be further expressed as
Figure FDA00030847440200000210
Wherein ω is2＝|h21I represents the channel amplitude from strong user 1 to weak user 2, user 2 receiving gain coefficient containing pairwise error
Figure FDA00030847440200000211
User 2 received noise standard deviation
Figure FDA00030847440200000212
Order statistic f using strong user channelss(ω1) Solution of ω1And ω2The unconditional PEP closed expression analyzed by the weak user can be obtained by double integration:
Figure FDA0003084744020000031
wherein the coefficients are respectively
Figure FDA0003084744020000032
Figure FDA0003084744020000033
Furthermore, Kv(. h) a modified Bessel function of order v representing the second class;
s402, DF, weak user PEP probability under given channel condition is
Figure FDA0003084744020000034
Wherein
Figure FDA0003084744020000035
Next, using double integration, unconditional PEP expression is obtained
Figure FDA0003084744020000036
Wherein the content of the first and second substances,
Figure FDA0003084744020000037
and
Figure FDA0003084744020000038
and S5, calculating the BER joint bound of each user based on a theoretical PEP expression, and completing system performance analysis.
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* Cited by examiner, † Cited by third party
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CN110113274B (en) * 2019-05-06 2021-05-14 电子科技大学 NOMA system based on multi-wavelet pulse forming
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107087274A (en) * 2017-05-15 2017-08-22 华中科技大学 A kind of two users' communication means based on D2D and up NOMA
CN108430040A (en) * 2017-02-14 2018-08-21 王晋良 Federated user is grouped with power distribution method and uses the base station of the method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108430040A (en) * 2017-02-14 2018-08-21 王晋良 Federated user is grouped with power distribution method and uses the base station of the method
CN107087274A (en) * 2017-05-15 2017-08-22 华中科技大学 A kind of two users' communication means based on D2D and up NOMA

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Bit Error Rate Analysis of Non-Orthogonal Multiple Access (NOMA) Technique in 5G with Different Power and User Scenarios;Utku Ozmat et al.;《2018 Advances in Wireless and Optical Communications》;20181231;全文 *
Derivation of the Closed-Form BER Expressions for DL-NOMA over Nakagami-m Fading Channels;Ferdi KARA et al.;《2018IEEE》;20181231;全文 *
On the Performance of Perfect and Imperfect SIC in Downlink Non Orthogonal Multiple Access (NOMA);Muhammad Rehan Usman et al.;《ICSGTEIS 2016》;20161008;全文 *
认知协作网络中非正交多址接入技术性能研究;李美玲等;《通信学报》;20180930;全文 *

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