CN113543259A - NOMA relay selection method, transmission method and system based on single-source optimal path - Google Patents
NOMA relay selection method, transmission method and system based on single-source optimal path Download PDFInfo
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Abstract
The invention provides a NOMA relay selection method, a transmission method and a system based on a single-source optimal path, which comprises the steps of broadcasting test signals to a predetermined target user and a predetermined relay user by taking a base station as a source node; the relay user preferentially selects a path with channel conditions meeting the set requirements to forward the broadcast test signal to a target user; after the test signal reaches the target user, the target user records the channel parameters and returns the channel parameters to the base station, and the base station configures path parameters according to the channel parameters returned by each target user; and if all path parameter configuration is finished, the base station selects a path with the optimal channel parameters, and all relay users on the path are determined as final relay users. The method of the invention broadcasts signals from the base station, when the signals reach the target node, the base station collects all accessible paths from the target node, and the best transmission path is selected quickly by comparing the channel parameters of each path.
Description
Technical scheme
The invention belongs to the technical field of non-orthogonal multiple access communication, and particularly relates to a NOMA relay selection method, a transmission method and a system based on a single-source optimal path.
Background
With the commercialization of the 5th Generation (5G), wireless data traffic has assumed exponential growth. The mobile phone user will no longer be satisfied with some simple data transmission such as audio chat and image-text information, and video and network live broadcast have become the main forms of mobile traffic, which both rely on the large bandwidth and low latency of 5G technology. However, in the case of a large number of users, the 5G system has problems of poor transmission quality and slow transmission rate.
Cooperative multicast technology was first introduced in the last 80 th century and was initially applied to computer networks, multicast being a point-to-multipoint communication. In the field of communications, multicasting is the transmission of information by a base station to multiple end users or end users to multiple end users. The technology can reduce the pressure of a single base station in the area, and the single base station can be shared by downlink users, and information transmission is realized by the base station or the terminal user in the downlink. Document [1] introduces a spectrum-shared relay communication based on a decode-and-Forward (DF) strategy. Document [2] introduces a relay selection strategy for map-forwarding type cooperative communication. For the node allocation problem, document [3] studies based on a fixed-order node scheduling algorithm, which can greatly reduce the computation time and obtain a near-optimal solution.
Unlike Orthogonal Frequency Division Multiplexing (OFDM) technology used in the fourth Generation mobile communication (4G), 5G uses Non-Orthogonal Multiple Access (NOMA) technology, and NOMA can improve the spectrum efficiency and user Access amount.
A model diagram of a conventional NOMA relay cooperative transmission system is shown in fig. 1, in which BS is a base station and the number of users in a cell is N. When the BS has no direct link to partial users, non-opportunistic NOMA cooperative transmission is adopted. Let R bei(i-1, 2 … …, m) constitutes a relay user group, R'd(d ═ 1,2 … …, N-m) constitutes a secondary group of users. The cooperative transmission is divided into two stages, the first stage is the cooperative transmission between relay users,the second phase is to select relay user RmTransmission to a secondary user. The relay users perform cooperative transmission by a Successive Interference Cancellation (SIC) technology, remove the signals after decoding to obtain the signals required by the relay users, transmit the rest signals to the next relay user, and finally transmit the last relay user RmAnd transmitting the signals required by the secondary users to the secondary users, and decoding the secondary users by SIC to obtain the required signals. However, in the current research of non-orthogonal multiple access relay communication, the relay users are selected randomly, and the difference of channel conditions among the relay users is not considered, so that the outage probability is increased, and the transmission reliability of the communication network needs to be improved.
Disclosure of Invention
The invention aims to provide a NOMA relay selection method, a transmission method and a system based on a single-source optimal path, aiming at the problems that the selection of relay users in the existing non-orthogonal multiple access relay communication is random and the difference of channel conditions among the relay users is not considered.
In order to achieve the technical purpose, the invention adopts the following technical scheme.
The NOMA relay selection method based on the single-source optimal path comprises the following steps:
a base station is used as a source node to broadcast test signals to a predetermined target user and a preselected relay user;
the relay user preferentially selects a path with channel conditions meeting the set requirements to forward the broadcast test signal to a target user;
after the test signal reaches the target user, the target user records the channel parameters and returns the channel parameters to the base station, and the base station configures path parameters according to the channel parameters returned by each target user;
and if all path parameter configuration is finished, the base station selects a path with the optimal channel parameters among the relay users, and all the relay users on the path are determined as final relay users.
In a second aspect, the present invention provides a NOMA cooperative transmission method based on a single-source optimal path, including the following steps:
step 1: the base station synthesizes superposition codes for each relay user and a target user and sends the superposition codes to the relay users with given transmitting power;
step 2: the relay users successively and successfully receive the superposition codes and then adopt SIC technology to carry out cooperative decoding to obtain all sub-signals, the signals required by the relay users are removed, the rest signals are re-modulated into new superposition codes, the next relay user of the transmission channel receives the new superposition codes, the step 2 is repeated until the last relay user of the transmission channel is reached, the last relay user sends the decoded signals required by the target user to the target user,
and step 3: the target user decodes the received signal by using the SIC technology;
wherein, the relay user is determined by the NOMA relay selection method based on the single-source optimal path provided by the technical scheme.
In a third aspect, the present invention provides a NOMA cooperative transmission system based on a single-source optimal path, including a base station, a relay user and a target user, wherein: the base station is used as a source node to broadcast test signals to target users and all relay users, and configures path parameters according to channel parameters between the relay users returned by all the target users; and if all path parameter configuration is finished, the base station selects a path with the optimal channel parameters among the relay users, and all the relay users on the path are determined as final relay users.
The base station is also used for synthesizing superposition codes for each selected final relay user and target user in the relay users and sending the superposition codes to the relay users with given transmitting power.
The relay user is used for preferentially selecting a path with a channel condition meeting a set requirement and forwarding the received broadcast test signal to a target user; the selected final relay user in the relay users is used for successfully receiving the superposition codes in sequence and then performing cooperative decoding by adopting a SIC technology to obtain all sub-signals, eliminating the signals required by the final relay user, re-modulating the rest signals into a new superposition code, and receiving the new superposition code by the next relay user of the transmission channel; until reaching the last relay user of the transmission path; and the last relay user sends the decoded signal required by the target user to the target user.
And the target user is used for returning channel parameters to the base station after receiving the test signal, and is also used for decoding the received signal by adopting an SIC technology after receiving the superposition code sent by the base station.
The beneficial technical effects are as follows:
the method comprises the steps of taking channel conditions among relay users as path parameters, taking a base station as a source node, selecting a target node, searching a path from the source node, namely the path capable of being successfully transmitted, and taking all nodes on the path with the optimal path parameters as a set of relay users for cooperative transmission.
The application provides a NOMA cooperative transmission method and a NOMA cooperative transmission system based on a single-source optimal path. After the target node is determined, a path with the best channel parameters is found. The method broadcasts signals from a base station, and after the signals reach a target node, the base station collects all accessible paths from the target node, and quickly selects the best transmission path by comparing channel parameters of all the paths. The method and the device can ensure that poor channel conditions do not exist among the relay users, and reduce the interruption probability of the system on the whole, so that the interruption probability of the relay users is low, and the complexity of the system can be effectively reduced.
Drawings
Fig. 1 is a schematic diagram of a model of a conventional NOMA relay cooperative transmission system;
fig. 2 is a schematic flowchart of a relay selection method based on a single-source optimal path according to an embodiment of the present invention;
fig. 3 is a schematic flowchart of a NOMA cooperative transmission method based on a single-source optimal path according to an embodiment of the present invention;
FIG. 4 is a result of a comparative simulation experiment of relay user performance in an embodiment of the present invention;
FIG. 5 shows a simulation result of performance comparison of secondary users according to an embodiment of the present invention;
FIG. 6 shows a simulation result of system complexity comparison according to an embodiment of the present invention.
Detailed Description
The present application is further described with reference to the drawings and the detailed description below.
In the first embodiment, as shown in fig. 1, the NOMA relay selection method based on a single-source optimal path includes the following steps:
step 1: select a set of secondary users R'jAs a target user;
step 2: is it determined whether the path parameter configuration is complete? If the configuration is not finished, performing step 3; otherwise go to step 6;
and step 3: base station synthesis test signal Uf(t) transmitting signals to all users in the area in a broadcasting mode, receiving the signals by all users, and enabling the base station to transmit the user R with better channel conditioniSelecting the relay user group;
and 4, step 4: the base station is used as a source node to broadcast to the selected target user and the relay user until the signal reaches the target user, the relay user preferentially selects a path with better channel condition, abandons the path with worse channel condition and determines the path as a useless path;
and 5: the target user records the channel parameters and transmits the channel parameters back to the base station, wherein the channel parameters comprise an optional path, a hop number s, a mean E and a variance lambda2The base station obtains the degree of the channel condition of each user and the base station through sequencing, configures path parameters and returns to the step 2;
step 6: relay user RiA plurality of paths are formed, and useless paths are removed;
and 7: the base station compares the channel parameters of all the channels and selects one channel with larger E and lambda2And (4) a path with small transmission hop number is adopted, and all relay users on the path carry out cooperative transmission.
On the premise of ensuring that all users can successfully receive the required signals, the algorithm selects part of users to establish the relay user group, and then finds out a plurality of relay users from the relay user group to carry out cooperative communication.
Optionally, the relay user preferentially selects a path with better channel conditions by using the ant colony algorithm, and abandons a useless path.
The embodiment of the application is a single-source optimal path algorithm improved by an ant colony algorithm. The channel condition between relay users is used as a path parameter, a base station is used as a source node, a target node (namely a target user) is selected, a path, namely a path capable of being successfully transmitted, is searched from the source node, and all nodes on the path with the optimal path parameter are used as a set of relay users for cooperative transmission.
Different from the traditional cooperative transmission mode, the algorithm provided by the application can eliminate the influence of the useless path. The useless paths are paths which cannot reach the target node, and the number of available paths with low quality is reduced along with the reduction of the number of the useless paths. The destination node will eventually receive the desired signal from the relay user.
In the process, the signal transmission hop number, the signal condition mean value and the variance are used for measuring the degree of the reachable path. Assuming that there is a path from the base station to the selected target user through s relay users, there are s +1 transmission hops in the process, and the channel condition between the relay users of each hop transmission is LijMean value of channel conditions E between relay users and variance of channel conditions λ between relay users2The following were used:
according to the formula (1) and the formula (2), the paths with larger channel condition mean, smaller channel condition variance and less hop count are sequentially selected in order.
The average value is larger, which indicates that the overall channel condition of the channel is better;
the variance is small, which indicates that the difference between the good and bad channel conditions of each section is not large, and the extreme situation is avoided, namely the whole channel condition is good, but the channel condition of a certain path is particularly bad, and even the interruption can occur;
the fewer the hops are, the fewer relay users pass through, and the system overhead and the transmission time can be reduced.
In a specific embodiment, the method for sequentially selecting the paths with larger mean, smaller variance and fewer hops in sequence may be: selecting paths with the mean value larger than a mean value threshold value from all paths to form a first alternative path set, and selecting paths with the variance smaller than a variance threshold value from the first alternative path set to form a second alternative path set; and selecting the path with the least hop number in the second alternative path set as the optimal path.
In a specific embodiment, the method for sequentially selecting the paths with larger mean, smaller variance and fewer hops in sequence may also be: sorting the channel condition mean values of all paths in all paths, and selecting a specific number of paths with larger mean values to form a first alternative path set; the channel condition means of the paths are sorted in the first alternative path, a specific number of paths with smaller channel condition variance are selected to form a second alternative path set, and the path with the least hop number is selected as the optimal path in the second alternative path set.
The embodiment II is a NOMA cooperative transmission method based on a single-source optimal path, which comprises the following steps:
step 1: the base station synthesizes superposition codes for each relay user and a target user and sends the superposition codes to the relay users with given transmitting power;
step 2: after successfully receiving the superposition codes in sequence, the relay users adopt the SIC technology to perform cooperative decoding to obtain all sub-signals, remove self required signals, remodulate the rest signals into new superposition codes, receive the new superposition codes by the next relay user of the transmission channel, repeat the step 2 until the last relay user of the transmission channel is reached, and send the decoded signals required by the target user to the target user by the last relay user;
and step 3: the target user decodes the received signal by using the SIC technology;
wherein the relay is usedFamily RiThe method for determining the NOMA relay selection based on the single-source optimal path provided by the above embodiment is adopted.
In this embodiment, the NOMA cooperative transmission method based on the single-source optimal path specifically includes:
step 1: a base station sends a test signal in a broadcast mode, and a relay selection method based on a single-source optimal path algorithm is adopted to search a transmission channel consisting of relay users;
step 2: the base station is used for each relay user RiModulating the desired signal Ui(t) all secondary user signals are combined into U0(t) synthesizing with relay user signal to superposition code UB(t) transmitting at a given transmission power, the superposition code being received by a next relay user of the transmission path;
and step 3: relay user RiSuccessfully receiving superposition code UB(t), using SIC technique to carry out cooperative decoding to obtain all sub-signals, and eliminating the signal U required by the relay useri(t) re-modulating the remaining signals into a new superposition code, receiving the new superposition code by a next relay user of the transmission path, and repeating the step 3 until the last relay user of the transmission path is reached;
and 4, step 4: the last relay user decodes the signal needed by itself and the signal U needed by the secondary user0(t) mixing U0(t) sending the data to the secondary user selected as the target user, and the secondary user adopts SIC technology to the U0And (t) decoding.
A flowchart of the NOMA cooperative transmission method based on the single-source optimal path provided in this embodiment is shown in fig. 3.
The NOMA-specific power multiplexing and successive interference cancellation techniques and cooperative communications are extremely fault tolerant, so this embodiment combines NOMA and cooperative communications. NOMA can decide the value of power distribution factor of each user signal in power domain, and modulate the user signal into superposition code. The NOMA cooperative communication network is adaptive, since different parameter allocations can cope with different channel conditions. The key of serial interference elimination is that the superposed code needs to be subjected to power judgment before decoding, and decoding is carried out according to the sequence of distributed power of user signals from large to small.
The system model based on the NOMA cooperative transmission method based on the single-source optimal path provided by the present embodiment is analyzed below.
Suppose relay user R1The useful signal to be received is Um(t) encoding and combining the N-m secondary user signals into one signal code U0(t) of (d). By adopting the NOMA transmission mode, the power distribution is carried out on the sending signals, the better the channel condition is, the smaller the obtained transmitting power is, namely, the larger transmitting power is used for making up the poorer channel condition. Suppose that the noise of the transmission channel is mean 0 and variance σ2Is expressed as n (t)0). The whole transmission process has m +1 time slots, and t is setqIs the qth slot. In time slot t0Superposed code U constructed by base stationB(t0) The following were used:
wherein, PBIs UB(t0) A transmission power ofi(t0) Is a time slot t0The power distribution coefficients are distributed in the order from big to small, and
the first stage is the process of cooperative transmission and decoding of relay users, and the total number of the slots is m. In time slot t0To relay user R1Demodulation of superposition codes U by SICB(t0) To obtain the signal U required by oneselfm(t0) And then rejects the signal. According to Shannon's theorem, obtain R1Decoding Ui(t0) The signal-to-noise ratio of (c) is:
wherein, gB,iFor base station to relay user R in cooperative transmission processiThe channel condition of (2). In time slot tq-1A is represented by RqDemodulation of superposition codes U by SICB(tq-1) To obtain the signal U required by oneselfm-q+1(tq-1) And eliminating the signal, and constructing superposition code U from the residual signalB(tq) Forward to Rq+1，UB(tq) Is represented as follows:
wherein, PqIs UB(tq) A transmission power ofi(tq) Is a time slot tqThe power distribution coefficients are distributed in the order from big to small, and
in time slot tqTo relay user Rq+1Decoding U by SICB(tq) To obtain Um-q(tq) This signal is the desired signal for the user. According to Shannon's theorem, obtain Rq+1Decoding signal Ui(tq) The signal-to-noise ratio of (c) is:
wherein li,jFor relay user RiAnd RjThe channel conditions in between.
Rq+1Decoding signal UB(tq) The total signal-to-noise ratio of (c) is:
wherein G [ x ]1,x2…,xm]Signal synthesis scheme for maximum combining ratio:
the second phase is to select relay user RmProcedure for transmission and decoding to a secondary user, RmWill U0(tm) Sending to secondary user, setting Sj(tm) Is secondary user R'jDesired signal, U0(tm) Is represented as follows:
wherein, PmIs U0(tm) A transmission power ofj(tm) Is a time slot tmThe power distribution coefficients are distributed in the order from big to small, and
secondary user R'jIn a transmission time slot tmProcess decoding Sj(tm) The signal-to-noise ratio of (c) is:
wherein s ism,jFor relay user RmTo secondary user R'jChannel condition of hB,jIs BS to secondary user R'jThe channel condition of (2).
Secondary user R'jIn a transmission time slot tmProcess decoding U0(tm) The total signal-to-noise ratio of (c) is:
(1) reliability analysis of relay users
Setting relaysUser RiSignal to noise ratio of the decoded signal of
The threshold value of the signal-to-noise ratio of the received signal is tauiInterruption probability of relay user
Is represented as follows:
this can be derived from equation (12):
with the relay selection strategy shown in fig. 2, when the system is interrupted, it can be considered that only the last user successfully receiving the signal is interrupted (because the latter user has no effect on the system). From equation (13) one can deduce:
as can be seen from equation (14), the interruption probability of the relay user
There is an upper bound.
When the channel is interrupted, the channel gain plays a negative role. Suppose the channel gain threshold of the BS and the relay user channel is epsiloniThe channel gain threshold of the channel between the relay users is deltaij，ΩfAnd ΩijAre respectively gB,iAnd li,jIs measured. According to the ordering and probability statistics theory, the upper bound of each part factor of equation (13) can be obtained:
from equations (14), (15) and (16), it can be derived:
the diversity gain of the relay user is N as obtained from equation (17).
(2) Reliability analysis of secondary users
Let secondary user R'dSignal to noise ratio of the decoded signal of
The threshold value of the signal-to-noise ratio of the received signal is taudInterruption probability of secondary user
Is represented as follows:
after the relay user sends a signal to the secondary user, only the base station and the relay user in the NOMA cooperative transmission system influence the secondary user. Suppose the channel gain threshold of the BS and the secondary user is psidThe channel gain threshold between the relay user and the secondary user is psir，ΩrAnd ΩhAre respectively sB,rAnd hB,dIs measured. Secondary user R'dProbability of interruption of
Comprises the following steps:
from the formula (19) can be derived
The diversity gain of the secondary user is m, as obtained from equation (20).
At present, a relay selection mode is random relay selection, but in the method, a single-source optimal path-based NOMA relay selection strategy is adopted to find a channel with better channel parameters, and each user obtains a required signal through SIC decoding, so that reliable transmission of NOMA cooperative communication is realized. The system complexity analysis of the strategy proposed in this application is as follows:
(1) communication overhead
The base station sends the test signal for 1 time, each relay user broadcasts the signal for N times, and the relay user receives other relay signals and processes the signals for N times. The second stage of cooperative transmission has two pre-selection schemes of parallel transmission and serial transmission. If the parallel transmission is adopted, the secondary user receives the selected relay user signal for N-m times; if serial transmission is adopted, the signals transmitted by the relay user and the secondary user are selected to be N-m times, and the signals received by the secondary user are N-m times.
Parallel transmission is superior to serial transmission, so parallel transmission is adopted in the method, and the system communication overhead is 3N-m + 1.
(2) Computing overhead
The cost of each relay user for setting the quality parameter of the cooperative network channel is N, the cost of the base station for searching the optimal path through the preset parameters is N, and the secondary user does not calculate the cost, so the system calculation cost is 2N.
(3) Overhead of signal processing
After an optimal path is selected, the first relay user decodes n times by using the SIC, where n is m, that is, the number of decoded signals and the number of relays are kept consistent, and then each relay user is sequentially reduced by one, so that the total signal processing overhead of the relay user is n (n + 1)/2; in the second stage of cooperative transmission, in order to reduce the complexity of the communication system, cooperative transmission is not used, the first secondary user decodes the required signal for N-N times by using SIC, and the subsequent secondary users are reduced by 1 time in sequence, so that the total signal processing overhead of the secondary users is (N-N) (N-N +1)/2, wherein N-N < N/2.
From the above analysis, the system complexity of the single-source optimal path algorithm is:
and carrying out simulation analysis on the application. The channel model adopted by simulation selects Rayleigh fading channels for frequency, power distribution coefficients are 0.8 and 0.2 respectively according to fixed power distribution, channel conditions between a base station and users are randomly generated according to a descending order, the users are uniformly distributed in a closed area, the loss coefficients are related to the distance, and the carrier conditions are the same. The simulation parameters are shown in table 1.
TABLE 1 System simulation parameters
Fig. 4 is a relationship between a relay user interruption probability and an overall signal-to-noise ratio in a NOMA relay cooperation method (i.e., a NOMA relay transmission method based on a single-source optimal path-based NOMA relay selection method provided by the present application). As can be seen from fig. 4, in the case of the same N and m, the interruption probability curve of the algorithm proposed in the present application decreases faster as the signal-to-noise ratio increases. Compared with the NOMA relay transmission based on AF, the relay user interruption probability of the algorithm is smaller. The reason is that the algorithm provided by the application can ensure that poor channel conditions do not exist among relay users, and the interruption probability of the system is reduced as a whole. As can be seen from fig. 4, the curve for the 4-user 3 relay trends down faster than the curve for the 4-user 2 relay. Under the condition that the total number of users is the same, along with the increase of the number of relays, the system performance of the NOMA relay cooperation method is better, and the interruption probability of relay users is greatly reduced.
Fig. 5 is a relationship between a secondary user outage probability and an overall signal-to-noise ratio in the NOMA relay cooperation method. As can be seen from fig. 5, in the case of the same N and m, the interruption probability curve of the algorithm proposed in the present application decreases more rapidly as the signal-to-noise ratio increases. Compared with the NOMA relay transmission based on AF, the secondary user interruption probability of the algorithm provided by the application is smaller. This is because the secondary user cannot successfully receive the signal transmitted by the base station, and therefore, the relay user performs transmission, and the interruption probability of the secondary user is reduced while ensuring that the interruption probability of the relay user is reduced. As can be seen from fig. 5, the 4-user 3 relay curve trends faster than the 4-user 2 relay curve. Under the condition that the total number of users is the same, along with the increase of the number of relays, the system performance of the NOMA relay cooperation method is better, and the interruption probability of secondary users is obviously reduced.
Fig. 6 is a relationship between system complexity and the number of relay users based on the NOMA relay cooperation method. As can be seen from fig. 6, as the number of relay users increases, the algorithm complexity of the algorithm proposed in the present application is more advantageous than the NOMA relay transmission based on AF. When the relay number reaches 80, the algorithm complexity of the algorithm provided by the application is reduced by 47.2% compared with the NOMA relay transmission based on AF. Therefore, under the condition that the number of users is large, the algorithm provided by the application can effectively reduce the complexity of the system.
The method and the system research the optimization problem of relay user path selection based on the system model of the NOMA relay cooperation method. The NOMA relay selection strategy based on the single-source optimal path is provided, the path selection efficiency is improved, and the system complexity is reduced. The strategy takes the channel condition as a channel parameter and finds an optimal path based on the channel parameter. Useless paths are eliminated in the path selection process, so that the number of available paths with low quality is reduced, and the path selection efficiency is improved. The channel conditions among all users on the selected path are better, and the reliability of the NOMA relay cooperation method is improved. Simulation results show that the interruption probability of the relay users and the secondary users is reduced and the complexity of the system is reduced on the premise that the maximum diversity gain is met by the scheme, and the overall performance of the system is further improved along with the increase of the number of the relay users.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. The NOMA relay selection method based on the single-source optimal path is characterized by comprising the following steps:
a base station is used as a source node to broadcast test signals to a predetermined target user and a preselected relay user;
the relay user preferentially selects a path with channel conditions meeting the set requirements to forward the broadcast test signal to a target user;
after the test signal reaches the target user, the target user records the channel parameters and returns the channel parameters to the base station, and the base station configures path parameters according to the channel parameters returned by each target user;
and if all path parameter configuration is finished, the base station selects a path with the optimal channel parameters among the relay users, and all the relay users on the path are determined as final relay users.
2. The single-source optimal path-based NOMA relay selection method of claim 1, wherein the channel parameters comprise transmission hop count, mean channel condition between relay users transmitting per hop, and/or variance channel condition between relay users transmitting per hop.
3. The single-source optimal path-based NOMA relay selection method of claim 2, wherein the mean of channel conditions between relay users of each hop transmission and the variance of channel conditions between relay users of each hop transmission are calculated as follows:
where E is the average of the channel conditions, λ, between relay users for each hop transmission2Variance of channel conditions between relayed users for each hop transmission, LijAnd s is the number of the relay users for the channel condition between the relay users of each hop transmission.
4. The NOMA relay selection method based on the single-source optimal path as claimed in claim 1, wherein the specific method for the base station to select the path with the optimal channel parameters is as follows:
selecting paths with the channel condition mean value between the relay users of each hop transmission larger than a mean threshold value from all paths to form a first alternative path set, and selecting paths with the channel condition variance between the relay users of each hop transmission smaller than a variance threshold value from the first alternative path set to form a second alternative path set; and selecting the path with the least hop number in the second alternative path set as the optimal path.
5. The NOMA relay selection method based on the single-source optimal path as claimed in claim 1, wherein the relay user uses an ant colony algorithm to preferentially select the path whose channel condition meets the set requirement and forward the broadcast test signal to the target user.
6. The NOMA cooperative transmission method based on the single-source optimal path is characterized by comprising the following steps:
step 1: the base station synthesizes superposition codes for each relay user and a target user and sends the superposition codes to the relay users with given transmitting power;
step 2: after successfully receiving the superposition codes in sequence, the relay users adopt the SIC technology to perform cooperative decoding to obtain all sub-signals, remove self-required signals, remodulate the rest signals into new superposition codes, receive the new superposition codes by the next relay user of the transmission channel, and repeat the step 2 until the last relay user of the transmission channel is reached; the last relay user sends the decoded signal required by the target user to the target user,
and step 3: the target user decodes the received signal by using the SIC technology; the relay user is determined by the NOMA relay selection method based on the single-source optimal path according to any claim 1-5.
7. The NOMA cooperative transmission system based on the single-source optimal path is characterized by comprising a base station, a relay user and a target user, wherein:
the base station is used as a source node for broadcasting test signals to a target user and all relay users; configuring path parameters according to channel parameters returned by each target user; and if all path parameter configuration is finished, the base station selects a path with the optimal channel parameters among the relay users, and all the relay users on the path are determined as final relay users.
The base station is also used for synthesizing superposition codes for each selected final relay user and target user in the relay users and sending the superposition codes to the final relay users with given transmitting power.
The relay user is used for preferentially selecting a path with a channel condition meeting a set requirement and forwarding the received broadcast test signal to a target user; successively and successfully receiving the superposition codes by the selected final relay user in the relay users, then performing cooperative decoding by using a SIC technology to obtain all sub-signals, eliminating self-required signals, re-modulating the rest signals into new superposition codes, and receiving the new superposition codes by the next relay user of the transmission channel until the last relay user of the transmission channel is reached; and the last relay user sends the decoded signal required by the target user to the target user.
The target user is used for receiving the test signal and then returning the channel parameter to the base station, and the target user is also used for receiving the superposition code sent by the base station and then decoding the received signal by adopting the SIC technology.
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