CN112261662B - Transmission method for improving energy efficiency of NOMA cooperative communication system - Google Patents
Transmission method for improving energy efficiency of NOMA cooperative communication system Download PDFInfo
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- 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
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- H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
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Abstract
The invention discloses a transmission method for improving the energy efficiency of an NOMA cooperative communication system, which adopts a relay-assisted NOMA cooperative cognitive communication transmission model to carry out transmission according to a transmission protocol, wherein the cognitive communication transmission model comprises a base station, a first receiving end, a second receiving end and a relay node for cooperative transmission, and all transmission channels are assumed to be independent Rayleigh fading channels; the transmission protocol is that any transmission time slot comprises a first transmission stage and a second transmission stage, in the first transmission stage, the base station sends superposed signals to a first receiving end and a second receiving end, the relay node also receives the superposed signals, and the superposed signals are divided into two parts for energy collection and signal forwarding according to an energy division ratio. And obtaining an optimal value of the power distribution factor and the energy division ratio by a parameter acquisition optimization algorithm for maximizing the energy efficiency of the system. The invention can maximize the energy efficiency of the system.
Description
Technical Field
The invention belongs to the field of energy acquisition cognitive radio networks, and particularly relates to a transmission method for improving the energy efficiency of a NOMA cooperative communication system.
Background
With the rapid development of mobile communication and internet of things (IoT), demands for spectrum efficiency and system capacity have rapidly increased, and conventional Orthogonal Multiple Access (OMA) access technology has been unable to meet user demands. The non-orthogonal multiple access (NOMA) access technology is considered as a multi-access technology with development potential, more spectrum efficiency can be obtained by deploying an ultra-dense network, and therefore the technology can be applied to supporting a large machine type communication scene under a 5G system. Unlike the conventional orthogonal multiple access technology, the NOMA technology can effectively utilize the same transmission resources (such as time, frequency and power) to realize multiple access application, thereby effectively improving the transmission performance of the whole system. In addition, spectrum sharing research has been widely conducted in Cognitive Radio (CR) networks. In a CR network, secondary users may access a licensed spectrum belonging to a primary user without interfering with their transmissions, or may assist the primary user in data transmission in exchange for an opportunity for spectrum sharing. In practical applications, research has also been conducted on Simultaneous Wireless Information and Power Transfer (SWIPT) for low power electronic devices, which can process information of radio frequency signals while harvesting energy. The NOMA technology, the cognitive radio network and the energy collection are combined, and an effective method can be provided for a 5G communication system to improve the energy efficiency and the spectrum efficiency simultaneously.
Among the existing proposals, NOMA technology has been studied by Y.Zhang et al in Energy efficiency optimization in a cognitive Radio induced non-orthogonal multiple access (Proc.IEEE 27th International Symposium on personal, indor and Mobile Radio Communications PIMRC, pp.1-6, 2016.) from the perspective of system Energy efficiency in a multi-user downlink system. Firstly, the existing cognitive radio system based on NOMA is summarized by introducing a multi-antenna technology and expanding the number of primary users to an arbitrary number; the goal of the system is then to optimize the energy efficiency of the proposed system for each primary user, subject to a single quality of service constraint; finally, aiming at the non-convex optimization problem, an author provides an efficient algorithm based on a sequential convex approximation method to achieve energy efficiency maximization, all transmission nodes have stable transmission energy supply, but when a large number of small sensors are connected into a wireless network, fixed energy supply cannot be well provided for all the sensors, and therefore the IoT application based on a 5G communication system in the future is better met by adopting an information energy simultaneous transmission technology. In the Energy efficiency of the system in the Energy efficiency validation for two-way relay assisted CR-NOMA system based on SWIPT (IEEE Access, vol.7, 2019), in W.ZHao et al. Based on the harvested energy and the quality of service requirements of the users, the authors aim to maximize the energy efficiency of the secondary system. The multi-objective energy efficiency optimization problem can be decomposed into three sub-optimization problems, namely transmit power optimization, power allocation optimization and power allocation ratio optimization. The optimization problem of the transmitting power is solved by adopting a Lagrange dual algorithm of a first-order Taylor series expansion function, and the power distribution optimization and the power distribution ratio optimization are jointly obtained through multi-objective iterative arithmetic. However, the transmission model studied by the method is too complex, and an accurate energy efficiency expression cannot be deduced, so that the proposed optimization algorithm cannot obtain a global optimal solution of the studied parameters.
Disclosure of Invention
The invention aims to provide a method for effectively improving the energy efficiency of an energy acquisition cognitive radio system based on a non-orthogonal multiple access technology, which comprises a spectrum sharing protocol design based on wireless information energy simultaneous transmission and a parameter optimization algorithm based on full search, is used for maximizing the energy efficiency of the system, and provides an available energy efficiency improving method for a sensor network and an internet of things based on the energy acquisition cognitive radio technology in the future.
In order to realize the purpose of the invention, the invention adopts the following scheme:
a transmission method for improving energy efficiency of a NOMA cooperative communication system comprises the following steps:
the method comprises the steps that a relay-assisted NOMA cooperative cognitive communication transmission model is adopted to carry out transmission according to a transmission protocol, the cognitive communication transmission model comprises a base station, a first receiving end, a second receiving end and a relay node for cooperative transmission, all transmission channels are assumed to be independent Rayleigh fading channels, and the channels are kept unchanged in one transmission time slot but independently changed in different transmission time slots;
the transmission protocol is that any one of the transmission time slots comprises two transmission phases, defined as a first transmission phase and a second transmission phase, in the first transmission phase, the base station BS sends superposed signals
To the first receiving end and the second receiving end, wherein x 1 And x 2 Respectively representing the signals, alpha, to be received by the first and second receiver 1 And alpha 2 Respectively representing transmission signals x 1 And x 2 The power distribution factor of the time, and the relay node also receives the superposed signal x BS And dividing the superposed signal x according to the energy division ratio beta BS The device is divided into two parts, wherein one part is used for energy collection, and the other part is used for forwarding signals; in the second transmission stage, the relay node sends the remaining base station signals to the first receiving end and the second receiving end in an amplifying and forwarding manner, and the first receiving end U1 directly decodes the required signal x 1 The second receiving end adopts the continuous interference elimination strategy and firstly decodes the interference information x 1 Information x required for re-decoding 2 ；
Respectively obtaining a receiving signal-to-noise ratio of the first receiving end and a receiving signal-to-interference-and-noise ratio of the second receiving end, respectively obtaining an interruption probability of the first receiving end and an interruption probability of the second receiving end based on the receiving signal-to-noise ratios and the receiving signal-to-interference-and-noise ratios, and obtaining a power distribution factor alpha through a parameter acquisition optimization algorithm maximizing system energy efficiency based on the interruption probabilities 1 And alpha 2 And an optimal value of the energy split ratio beta.
Further, the superimposed signal x is divided according to an energy division ratio beta BS The method is divided into two parts, specifically:
the relay node slave radio frequency signal x BS The energy obtained is
The transmission power of the relay node is
P R ＝ηβP BS |h BSR | 2 ， (1)
The relay node adoptsAmplifying signals remaining from forward transmission
The corresponding transfer signal is expressed as
Wherein
Representing the received noise, G representing the power normalization factor,
wherein, P BS Denotes the base station transmit power, h BSR Representing the transmission channel between the base station and the relay node,
representing received white gaussian noise at the relay node, y R Representing the signal received by the relay node during the first transmission phase, η representing the energy conversion efficiency, n R Representing white gaussian noise received at the base station,
representing the noise generated by the circuit as the received signal goes from high frequency to low frequency.
Further, the relay node receives the signal of
Further, the receiving snr of the first receiving end includes receiving snrs of the first receiving end in the first transmission stage and the second transmission stage, respectively, and the receiving sinr of the second receiving end includes receiving snrs of the second receiving end in the first transmission stage and the second transmission stage, respectively.
Further, in the first transmission stage, the receiving snr of the first receiving end is
The second receiving end detects the signal of the first receiving end firstly, and then decodes the required signal, so that the second receiving end detects two signals x simultaneously 1 And x 2 Respectively of signal to interference and noise ratio of
In the second transmission stage, the receiving signal-to-noise ratio of the first receiving end is
Since the second receiver uses successive interference cancellation, the second receiver successively decodes the transmission signal x 1 And x 2 Respectively expressed as
Wherein, eta represents the energy conversion efficiency,
which is indicative of the power of the noise,
representing the noise power at the first receiving end,
representing the noise power at the second receiving terminal, h RU1 Representing the transmission signal between the relay node and the first receiver, h RU2 Representing the transmission channel, h, between the relay node and the second receiver BSU1 Representing the transmission channel, h, between the base station and the first receiver BSU2 Representing the transmission channel between the base station and the second receiving end.
Further, when the achievable rates of the first receiving end and the second receiving end are both lower than the target data rate r D When an event occurs in which the transmission of information is interrupted, the probability that the second receiver will describe such an interruption event is expressed as
Wherein
Representing the lowest receivable SINR, the first receiver will transmit signal x 2 Direct decoding of the information x required for it, seen as noise 1 Thus the probability of interruption at the first receiver is
Wherein the content of the first and second substances,
indicating the probability of interruption at the first receiver,
indicating the probability of interruption at the second receiver.
Further, the parameter obtaining optimization algorithm for maximizing the system energy efficiency specifically comprises:
s1: definition of Δ α 1 And Δ β are each a parameter α 1 And search step size of beta, initialization
Wherein the content of the first and second substances,
which represents the average energy efficiency of the system,
represents the maximum system average energy efficiency;
s2: for arbitrary β = β 0 E (0,1), performing steps S21-S23;
s21: for arbitrary alpha 1 = α ∈ (0.5,1), calculation
The result of (1);
if gamma is equal to U ≥R D Then calculate
If it is not
Then the current optimization parameter
And beta * ＝β 0 Is then updated
Otherwise, keeping the original optimized parameter value;
s22: update α = α + Δ α;
s23: updating beta 0 ＝β 0 +Δβ；
S3: from the formula
Optimization Problem (P1) obtains a global optimal solution.
Further, the average energy efficiency of the system is calculated in the following manner:
compared with the prior art, the invention can realize the following beneficial effects:
1) The transmission protocol and the cognitive communication model are more suitable for practical application scenes, the relay nodes capable of acquiring energy can be better utilized to assist in information transmission, and the overall energy efficiency of the system is effectively improved;
2) The invention sets the maximum system energy efficiency as a target, simultaneously ensures that the signal-to-noise ratio at each receiving end exceeds the set transmission rate, provides a simple algorithm capable of accurately acquiring the optimized power distribution factor and the information energy division ratio, and further improves the energy efficiency of the whole system.
Drawings
Fig. 1 is a schematic diagram of a cognitive communication model based on relay assistance according to an embodiment of the present invention.
Fig. 2 is a transmission protocol of a system according to an embodiment of the present invention.
Fig. 3 is a simulation diagram of the outage probability of the first receiving ends U1 and U2 under different power allocation factors.
Fig. 4 is a simulation diagram of the outage probability of the first receiving ends U1 and U2 under different target transmission rate conditions.
Fig. 5 is a graph of the overall system energy efficiency improvement over straight line transmission for the proposed scheme when an optimization algorithm is employed.
Detailed Description
In order to better understand the present invention, the following examples are further provided to illustrate the present invention, but the present invention is not limited to the following examples.
The technical scheme adopted by the embodiment comprises two parts, wherein the first part is a relay-assisted NOMA cooperative cognitive communication transmission model and a spectrum sharing model diagram, and the second part is an optimized parameter acquisition method for obtaining the maximized system energy efficiency.
1. Transmission model and transmission protocol model diagram illustration
As shown in fig. 1, a base station BS provides an information transmission service to a first receiving end U1 and a second receiving end U2 with the assistance of a relay node R, and the relay node R collects energy from a radio frequency signal transmitted by the base station BS for cooperative transmission. According to the deployment principle of the non-orthogonal multiple access scheme, more base station transmission power is allocated to the far-end user, and less base station transmission power is allocated to the near-end user. The base station BS, the relay node R, the first receiving end U1 and the second receiving end U2 are all equipped with one antenna operating in half duplex mode and it is assumed that all channels experience quasi-static rayleigh fading channels. The transmission model is very suitable for a 5G-based large-scale equipment connection scene, and in practical application, the first receiving end U1 and the second receiving end U2 can be regarded as sensors deployed at remote positions. If the base station is used for directly transmitting data, the base station is overloaded in transmission and the energy efficiency of the system is low, and the cognitive communication transmission model based on relay assistance is adopted, so that the energy efficiency of the system is greatly improved while the transmission efficiency of the system is ensured. h is ij Represents the channel coefficient between the sending end i and the receiving end j, | h ij | 2 Representing the channel gain, which follows an exponential distribution and has a mean value of
Where d and theta denote the transmission distance and the path loss exponent, respectively. All transmission channels are assumed to be independent rayleigh fading channels, so that the channels remain unchanged in one transmission time slot, but independently change in different transmission time slots.
The transmission protocol of the system is shown in fig. 2. In any transmission time slot, the system is divided into the following two transmission stages:
1. in the first 1/2 time slot, i.e. the first transmission phase, the base station transmits the superimposed signal
To a first receiving end U1 and a second receiving end U2, where x 1 And x 2 Respectively represents the signals, alpha, that the first receiving end U1 and the second receiving end U2 need to receive 1 And alpha 2 Respectively representing transmission signals x 1 And x 2 A power allocation factor of time; at the same time, the relay node R also receives the signal x BS Dividing the signal x according to the information energy division ratio beta BS The device is divided into two parts, wherein one part is used for energy collection, and the other part is used for forwarding signals;
2. in the second transmission stage, which is the last 1/2 time slot, the relay node R transmits a base station signal, namely the residual signal information after energy collection, by adopting an amplification forwarding technology; the first receiving end U1 directly decodes the signal x required by the first receiving end U1 1 The second receiving end U2 adopts the successive interference elimination strategy to decode the interference information x first 1 Information x required for re-decoding 2 。
2. System performance analysis method and system energy efficiency maximization optimization algorithm
1. System performance analysis method
(1) In the first 1/2 transmission time slots, i.e. the first transmission stage, the signals received by each node are respectively represented as:
wherein, y R Representing the signal received by the relay node during the first transmission phase,
representing the signal received by the first receiver in the first transmission phase,
representing the signal received by the second receiver during the second transmission phase, P BS Which represents the transmission power of the base station,
representing white gaussian noise received at each node,
representing the noise power. According to the power division method, the relay node R derives from the superimposed signal x BS The energy obtained is
Where β represents the information energy division ratio. The transmission power of the relay node R can be calculated as
P R ＝ηβP BS |h BSR | 2 ， (2)
Where η represents the energy conversion efficiency. At this time, the receiving signal-to-noise ratio of the first receiving end U1 is
The second receiving end U2 uses successive interference cancellation technology to detect the signal of the first receiving end U1 first, and then decodes the signal required by the first receiving end U1. The second receiver U2 thus detects two signals x simultaneously 1 And x 2 Respectively have a signal to interference and noise ratio of
(2) In the second transmission stage which is the last 1/2 transmission time slot, the relay node R adopts an amplification forwarding scheme to transmit the residual signals
The corresponding transfer signal is expressed as
Wherein
Representing the received noise, G representing the power normalization factor
At this stage, the signals received by the first receiving end U1 and the second receiving end U2 are respectively represented as
The received signal-to-noise ratio at the first receiving end U1 is
Since the second receiving end U2 adopts the contact interference elimination technology, the second receiving end U2 continuously decodes x 1 And x 2 Respectively expressed as
When the receiving rates of the first receiving end U1 and the second receiving end U2 are lower than the threshold value r of the transmission data rate D Then an event occurs in which the transmission of information is interrupted. According to the successive interference cancellation process of the second receiving terminal U2, the signal of the first receiving terminal U1 is first detected in both transmission phases. The probability that the second receiver U2 describes such an interruption event can therefore be expressed as
Wherein
Indicating the lowest receivable signal-to-interference-and-noise ratio, i.e. the power of the received signal and the noise power and interferenceThe ratio of the sum of the interference powers. The first receiving end U1 transmits the signal x 2 Direct decoding of the information x required for it, seen as noise 1 Therefore, the interruption probability of the first receiving end U1 is
2. System energy efficiency maximization optimization algorithm
For power allocation factor alpha 1 And alpha 2 Users in NOMA systems cannot achieve optimal reception at the same time. In addition, there is also a trade-off between the transmission power of the node R and the remaining signals for information transmission, where a higher information division ratio can ensure that the relay node R obtains more energy, but the remaining signals for information forwarding are less. Therefore, only when the receiving rate of each user reaches the transmission requirement, the optimal parameters of the system can be jointly obtained. Furthermore, with the development of 5G communication systems, more and more devices will be connected to the network, which will increase the overall energy consumption. Therefore, from the perspective of green communication, optimization of energy efficiency is important. According to the interruption probability of the first receiving end U1 and the second receiving end U2, the present embodiment aims to ensure the achievable rate of each receiving end on the premise of maximizing the average energy efficiency of the system. According to the results of equations (10) and (11), the entire optimization problem (P1) can be equivalently expressed as
Wherein the content of the first and second substances,
represents the average energy efficiency, γ, of the system U Representing the minimum received interference noise among all users; in C1, R D More than 0 represents the lowest requirement of the received signal to interference and noise ratio at the first receiving end U1 and the second receiving end U2; c2 and C3 represent the power allocation factor and the information energy division ratio, respectively. Due to the middleProbability of interruption
And
the optimization problem (P1) cannot solve the analytic solution of the parameter. However, this problem can be solved by a full search algorithm. The algorithm calculates the key performance index of the system model, and when the energy efficiency of the system reaches the maximum, the parameters in the system are the global optimal solution. The specific algorithm is as follows:
s1: definition of Δ α 1 And Δ β are each a parameter α 1 And search step size of beta, initialization
Represents the maximum system average energy efficiency;
s2: for arbitrary β = β 0 E (0,1), performing steps S21-S23;
s21: for arbitrary alpha 1 = α ∈ (0.5,1), calculation
The result of (1);
if gamma is U ≥R D Then calculate
If it is not
Then the current optimization parameter
And beta * ＝β 0 Is then updated
Otherwise, keeping the original optimized parameter value;
s22: update α = α + Δ α;
s23: updating beta 0 ＝β 0 +Δβ；
S3: from the formula
Optimization Problem (P1) obtains a global optimal solution.
According to which alpha can be obtained 1 、α 2 And the optimal value of beta is adopted by the system for information energy transmission, so that stable energy supply can be optimally provided for all transmission nodes in the system, and the energy efficiency of the system can be maximally improved.
FIG. 3 illustrates the distribution coefficient α at different powers 1 And alpha 2 The value of (2) is the interruption probability of the first receiving end U1 and the second receiving end U2. These figures show that as the base station transmits power P BS The interruption performance of both users is improved. When alpha is 1 =0.9 and α 2 When =0.1, the interruption performance of the first receiving end U1 using the proposed scheme is first better than the interruption performance of the direct transmission and then slightly worse than the interruption performance of the direct transmission, because higher transmission power may cause more decoding interference, compared to the interruption probability of the direct transmission. When alpha is 1 =0.8 and α 2 When =0.2, the interruption probability (the curve located at the top in the figure) of the first receiving end U1 is always higher than that in the direct transmission when the proposed scheme is adopted. However, at low P BS Within the scope of the proposed scheme, the interrupt performance of the second receiver U2 is worse than the performance of the direct transmission, and then the interrupt performance follows P BS Becomes better.
FIG. 4 illustrates the transmission power P of the first receiving end U1 and the second receiving end U2 at different base stations BS The interruption probability under the value, the interruption performance of the first receiving end U1 and the second receiving end U2 are similar to that of fig. 3. Furthermore, with the target rate r D The interruption performance of the first receiving end U1 and U2 is reduced because it is more difficult for the transmission channel to support the higher rate requirement.
Fig. 5 shows the average energy efficiency of the proposed scheme versus the boost rate for a straight line transmission.The simulation also adopts the proposed parameter joint optimization algorithm. As shown, although the proposed scheme works with P at the energy efficiency improvement rate BS Is increased and becomes worse, but the overall energy efficiency improvement rate is still kept above 100%. Therefore, the transmission method provided by the invention can effectively improve the energy efficiency of the system.
The parts not involved in the present invention are the same as or implemented using the prior art.
The foregoing is considered as illustrative of the preferred embodiments of the invention and is not to be construed as limiting the invention in any way. Various equivalent changes and modifications can be made by those skilled in the art based on the above-described embodiments, and all equivalent changes and modifications within the scope of the claims should fall within the protection scope of the present invention.
Claims (6)
1. A transmission method for improving energy efficiency of a NOMA cooperative communication system is characterized by comprising the following steps:
the method comprises the steps that a relay-assisted NOMA cooperative cognitive communication transmission model is adopted to carry out transmission according to a transmission protocol, wherein the cognitive communication transmission model comprises a Base Station (BS), a first receiving end (U1), a second receiving end (U2) and a relay node (R) for cooperative transmission, all transmission channels are assumed to be independent Rayleigh fading channels, and the channels are kept unchanged in one transmission time slot but independently changed in different transmission time slots;
the transmission protocol is that two transmission phases are included in any one of the transmission time slots, defined as a first transmission phase and a second transmission phase, in the first transmission phase, the Base Station (BS) sends a superposition signal
To the first receiving terminal (U1) and the second receiving terminal (U2), where x 1 And x 2 Respectively represents the signals, alpha, that the first receiving end (U1) and the second receiving end (U2) need to receive 1 And alpha 2 Respectively representing transmission signals x 1 And x 2 Power allocation factor of time, and, at the same time, relay nodeThe point (R) also receives the superimposed signal x BS And dividing the superposed signal x according to the information energy division ratio beta BS The device is divided into two parts, wherein one part is used for energy collection, and the other part is used for forwarding signals; in the second transmission stage, the relay node (R) sends the remaining base station signals to the first receiving end (U1) and the second receiving end (U2) in an amplify-and-forward manner, and the first receiving end (U1) directly decodes the signal x required by the first receiving end (U1) 1 The second receiving end (U2) adopts the successive interference elimination strategy to decode the interference information x first 1 Information x required for re-decoding 2 ；
Wherein, a receiving signal to noise ratio of the first receiving end (U1) and a receiving signal to interference plus noise ratio of the second receiving end (U2) are respectively obtained, an interruption probability of the first receiving end (U1) and an interruption probability of the second receiving end (U2) are respectively obtained based on the receiving signal to noise ratio and the receiving signal to interference plus noise ratio, and a power distribution factor alpha is obtained by a parameter obtaining optimization algorithm which maximizes the energy efficiency of the system based on the interruption probability 1 And alpha 2 And an optimal value of the information energy division ratio β;
wherein the superimposed signal x is divided according to an information energy division ratio beta BS The method is divided into two parts, specifically:
the relay node (R) is derived from a radio frequency signal x BS The energy obtained is
The transmission power of the relay node (R) is
P R ＝ηβP BS |h BSR | 2 ， (2)
The relay node (R) transmits the remaining signals by adopting amplification and forwarding
The corresponding transfer signal is expressed as
Wherein
Representing the received noise, G representing the power normalization factor;
wherein, P BS Denotes the base station transmission power, h BSR Representing the transmission channel between the base station and the relay node,
representing received white gaussian noise at the relay node, y R Representing the signal received by the relay node during the first transmission phase, η representing the energy conversion efficiency, n R Representing white gaussian noise received at the base station,
representing noise generated by the circuit as the received signal goes from high frequency to low frequency;
the parameter obtaining and optimizing algorithm for maximizing the system energy efficiency specifically comprises the following steps:
s1: definition of Δ α 1 And Δ β are each a parameter α 1 And search step size of beta, initialization
Wherein, the first and the second end of the pipe are connected with each other,
which represents the average energy efficiency of the system,
represents the maximum system average energy efficiency;
s2: for arbitrary β = β 0 E (0,1), executeSteps S21-S23;
s21 for any alpha 1 = α ∈ (0.5,1), calculation
The result of (1);
if gamma is equal to U ≥R D Then calculate
If it is not
Then the current optimization parameter
And beta * ＝β 0 Is then updated
Otherwise, keeping the original optimized parameter value;
s22, updating alpha = alpha + delta alpha;
s23, updating beta 0 ＝β 0 +Δβ；
S3: from the formula
And obtaining a global optimal solution.
2. The transmission method for improving energy efficiency of a NOMA cooperative communication system according to claim 1, wherein: the relay node receives the signal as
3. A transmission method for improving energy efficiency of a NOMA cooperative communication system according to any of claims 1-2, wherein: the receiving signal-to-noise ratio of the first receiving end (U1) comprises the receiving signal-to-noise ratios of the first receiving end (U1) in a first transmission stage and a second transmission stage respectively, and the receiving signal-to-interference-and-noise ratio of the second receiving end (U2) comprises the receiving signal-to-interference-and-noise ratios of the second receiving end (U2) in the first transmission stage and the second transmission stage respectively.
4. The transmission method for improving energy efficiency of a NOMA cooperative communication system according to claim 3, wherein: in a first transmission phase, the received signal-to-noise ratio of the first receiving end (U1) is
The second receiving end (U2) detects the signal of the first receiving end (U1) firstly, and then decodes the signal required by the first receiving end, so that the second receiving end (U2) detects two signals x simultaneously 1 And x 2 Respectively have a signal to interference and noise ratio of
In a second transmission phase, the received signal-to-noise ratio of the first receiving end (U1) is
Since the second receiver (U2) uses successive interference cancellation, the second receiver (U2) successively decodes the transmission signal x 1 And x 2 Respectively expressed as
Wherein, eta represents the energy conversion efficiency,
which is indicative of the power of the noise,
representing the noise power at the first receiving end,
representing the noise power at the second receiving terminal, h RU1 Representing the transmission channel, h, between the relay node and the first receiver RU2 Representing the transmission channel, h, between the relay node and the second receiver BSU1 Representing the transmission channel, h, between the base station and the first receiver BSU2 Representing the transmission channel between the base station and the second receiving end.
5. The transmission method for improving energy efficiency of a NOMA cooperative communication system according to claim 1, wherein: when the achievable rates of the first receiving end (U1) and the second receiving end (U2) are lower than the target data rate r D When the information transmission is interrupted, the probability that the second receiver (U2) describes the interruption event is expressed as
Wherein
Representing the lowest receivable signal-to-interference-and-noise ratio, the first receiving end (U1) transmits a signal x 2 Direct decoding of the information x required for it, seen as noise 1 Thus, the first receiver (U1) has an outage probability of
Wherein the content of the first and second substances,
indicating the probability of interruption at the first receiver,
indicating the probability of interruption at the second receiver.
6. The transmission method for improving energy efficiency of the NOMA cooperative communication system according to claim 1, wherein the maximum calculation formula of the system energy efficiency is as follows;
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