CN109413749B - SCMA network capacity analysis and layered multicast resource allocation method - Google Patents
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Abstract
The invention discloses a SCMA network capacity analysis and layered multicast resource allocation method, which uses the advantages of SCMA in wireless multicast communication to expand the capacity of a multicast system, firstly, a formula is carried out on the capacity of the system, the layered multicast technology is adopted to be applied to the SCMA network, the layered coding technology is adopted to be applied to the SCMA network, so that the capacity of the system is not limited by the channel quality of the worst user in the multicast system, the information transmission efficiency and the channel utilization rate are improved, the user experience is provided, the resource allocation algorithm is adopted to maximize the capacity of the system, and in order to reduce the calculation complexity, a sub-optimization algorithm is also provided, and the sub-optimization algorithm is divided into two stages of power allocation and codebook allocation. Simulation results show the feasibility of the proposed algorithm in hierarchical multicast based SCMA networks and Orthogonal Frequency Division Multiplexing (OFDMA) networks.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a method for SCMA network capacity analysis and hierarchical multicast resource allocation.
Background
Compared with the OFDMA technology, the non-OFDMA technology can lead the system to obtain higher throughput and accommodate more users, and therefore, the system becomes one of the candidate technologies for 5G popularity. In the existing non-orthogonal multiple access technology, sparse code multiple access is a strategy of code domain. Unlike low density identification sequence techniques, SCMA can obtain the gain of a multidimensional constellation. In SCMA networks, the input bits are mapped directly onto sparse codewords, which are selected from a predefined codebook. Each codebook corresponds to a data stream, and the number of codebook sets requires more physical resources (e.g., subcarriers). Because of the nature of SCMA loading, each codebook may be used by multiple data streams, and therefore, a multi-user detection technique (MUD) is required at the receiving end.
Currently, many of the research in SCMA networks have focused on network analysis and SCMA codebook design. An iterative multi-user receiver that utilizes diversity gain and coding gain of SCMA is discussed. With the development of multicast broadcast technology within a cell, wireless multicast technology can send the same data to all members of the same multicast group. In conventional multicast transmission strategies, network capacity is limited by the channel quality of the worst users in the multicast group. In order to solve this problem, an opportunistic multicasting strategy based on hierarchical coding is proposed, in which, when hierarchical coding is adopted, original multicasting data is coded into a base layer and a plurality of enhancement layers, the base layer data needs to be correctly received by all users, and the enhancement layer data is provided to users with better channel conditions, and more enhancement layer data can be received. Thus, in a transmission strategy employing hierarchical coded opportunistic multicasting, higher system throughput can be achieved than with conventional multicasting strategies alone. However, in the past, research on SCMA networks has focused on unicast transmission, and it is not possible to meet the existing network transmission requirements.
Disclosure of Invention
In view of the above-mentioned drawbacks or shortcomings, an object of the present invention is to provide a SCMA network capacity analysis and hierarchical multicast resource allocation method.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a SCMA network capacity analysis and hierarchical multicast resource allocation method comprises the following steps:
1) Layering the original multicast data into base layer data and enhancement layer data; the base layer data is data which can be correctly received by all users in the multicast group; the enhancement layer data are data which are received in a differentiated mode according to users with different channel quality in the multicast group;
2) Performing codebook allocation and power allocation on the base layer data and the enhancement layer data;
3) After SCMA coding is carried out on the base layer data and the enhancement layer data after codebook allocation and power allocation, data transmission is carried out through a frequency selective channel, so that a receiving terminal recovers the original multicast data according to the allocation information of the codebook.
The step 2) of performing codebook allocation and power allocation on the base layer data and the enhancement layer data specifically includes:
2.1, defining the multicast rate of the base layer data as:
wherein ,
indicating the rate at which the base layer data is required, h u,k Representing the channel gain of user u on subcarrier k, wherein +.>
η represents a path loss constant, d u Represents the distance from user u to the base station, alpha represents the path loss coefficient, ρ u,k Representing the Rayleigh fading of user u on subcarrier k, P b Representing the total power of the transmission base layer, which is equally distributed among LB codewords, delta 2 Representing noise power on a codebook in a broadcast channel; u= { 1..u..u..u., U } represents a group of multicast users, the multicast users of the group have the same QoS requirements, and each user employs a single antenna, the system bandwidth may be divided into a set of subcarriers, with k= {1, K, K represents that the system bandwidth may be divided into a set of subcarriers, c= { 1..c..c.. C } represents a codebook set, b= {1,..b,..and B } represents a codebook set allocated to base layer data;
2.2, defining the multicast rate of the enhancement layer data as:
wherein ,Pe Representing the total power of the transmission enhancement layer, which is equally distributed to LEIn the code word;
2.3, the capacity of the system is expressed as:
wherein the said
Representing the set of users meeting the enhancement layer minimum rate requirement,
the capacity maximization allocation of the system is as follows:
3.1, a capacity maximization allocation formula is as follows:
the method meets the following conditions:
P b +P e ≤P,P b ≥0,P e ≥0 (c)
the constraint (b) indicates that the same codebook in the codebook set C cannot be allocated to the base layer and enhancement layer data at the same time. P due to limited total transmission power b and Pe The constraint (c) needs to be satisfied. The constraint (d) represents a minimum rate of the base layer and the enhancement layer guaranteeing the user's needs;
and 3.2, obtaining a solution of the capacity maximization allocation formula of the optimization problem by adopting a sub-optimization fast algorithm (FSA).
The sub-optimal fast algorithm (FSA) is:
4.1, codebook allocation stage:
let the total power P of the base station be the equal power distributed to all codebooks, the codebook distribution problem formula is:
minB；
the method meets the following conditions:
/>
then calculating the multicast rate on each codebook and arranging it in descending order, selecting the codebooks in order from high to low, and calculating the sum rate until the base layer rate is met;
4.2, power distribution stage:
the power allocation can be formulated as:
minP b
the method meets the following conditions:
codebook set when assigned to base layer
After being determined, R B The re-formulation is:
the above equation is a logarithmic function and the function is monotonically increasing, so when
At the time P b Obtaining a minimum value;
4.3 finally, the power allocation problem is converted to solve P b The problem of the B-th order polynomial of (2) is expressed as:
wherein ,
is a constant;
solving for P using Matlab b Power P of enhancement layer e ＝P-P b . Thereafter, set up
ε,P b and Pe And the capacity of the system is obtained.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a SCMA network capacity analysis and layered multicast resource allocation method, which uses the advantages of SCMA to expand the capacity of a multicast system in wireless multicast communication, firstly, the capacity of the system is formulated, and the layered multicast technology is adopted to be applied to the SCMA network, and the layered coding technology is adopted to be applied to the SCMA network, so that the capacity of the system is not limited by the channel quality of the worst user in the multicast system, the information transmission efficiency and the channel utilization rate are improved, and the user experience is provided.
Furthermore, the invention adopts a resource allocation algorithm to maximize the capacity of the system, and in order to reduce the computational complexity, a sub-optimization algorithm is also provided, and the sub-optimization algorithm is divided into two stages of power allocation and codebook allocation. Simulation results show the feasibility of the proposed algorithm in hierarchical multicast based SCMA networks and Orthogonal Frequency Division Multiplexing (OFDMA) networks.
Drawings
FIG. 1 is a schematic diagram of a network model structure of the present invention;
FIG. 2 is a flow chart of the method of the present invention;
fig. 3 is a system block diagram based on a hierarchical multicast strategy in the SCMA network of the present invention;
FIG. 4 is a diagram of the number of users versus the system capacity of the present invention;
FIG. 5 is a graph of the number of users versus λ according to the present invention;
FIG. 6 is a graph of the number of users versus the average degradation probability of the present invention;
FIG. 7 is a plot of total base station power versus average degradation probability for the present invention;
FIG. 8 is a plot of total base station power versus system capacity for the present invention;
fig. 9 is a graph of minimum rate versus system capacity for the base layer requirements of the present invention.
Detailed Description
The present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
As shown in fig. 1, the network model of the present invention is:
considering a downstream single cell SCMA network, the network model is shown in fig. 1, and a group of multicast users are represented as
The group of multicast users have the same QoS requirements and each user employs a single antenna. The system bandwidth can be divided into a group of subcarrier sets>
And (3) representing. At the base station side, each data stream with length log2 Mbit is directly mapped into a preset composite codebook with K dimension, wherein L (L<K) And non-zero sparse elements. With c= {1, c., where, C represents the set of codebooks, the number of codebooks is a function of a codebook length K, with L non-zero elements. Therefore, the mapping relationship between the codebook and the subcarriers can be expressed as follows:
f is a matrix of CxK, binary element a c,k Take a value of 0 or 1, if codebook c is used by subcarrier k, then a c,k And the value is 1, otherwise, 0 is taken. Here the sparse matrix F has L1 elements per row.
Each multicast data stream is mapped to a codebook c resulting in a sparse codeword vector x c After that, the processing unit is configured to, ||x c || 2 =k, all codebooks C are multiplexed onto K subcarriers. P (P) c Representing the power allocated on each codebook c and satisfying Σ c∈C P c And P, where P represents the total power of the base station. Thus, the signal received by user u can be expressed as:
where h is u ＝(h u,1 ,...h u,K ) Representing channel vectors, h u,k Representing the channel gain of user u on subcarrier k, where
η represents a path loss constant, d u Represents the distance from user u to the base station, alpha represents the path loss coefficient, ρ u,k Representing the rayleigh fading of user u on subcarrier k, n u Representing additive white gaussian noise for user u.
Due to the sparsity of the SCMA code words, a receiving end can adopt a Message Passing Algorithm (MPA) with lower complexity and a multi-user joint iteration method, thereby realizing the maximum likelihood decoding of approximate multi-users. SCMA is code domain non-orthogonal multiple access technology, and multiple data streams from one or more users are transmitted in the same time-frequency resource unit through code domain spread spectrum and non-orthogonal superposition; the receiving end separates out a plurality of data streams in the same time-frequency resource unit through linear despreading. Thus, codebooks from different data streams can be decoded while not interfering with each other. It is assumed that each user feeds back its instantaneous channel information to the base station via an error-free feedback channel. The repeated use condition of the non-multicast group user codebook is not considered, and the links of the multicast group are not interfered with each other.
A set of subcarriers using codebook c is represented. Thus, user u's signal-to-noise ratio on codebook cCan be expressed as:
P c,k representing the power loaded when codebook c is employed on subcarrier k,
representing the noise power on codebook c in the broadcast channel. Assuming that the noise power on each codebook is equal, for example: />
The rate of user u on codebook c in the broadcast channel is expressed as:
R u,c ＝log 2 (1+γ u,c )。
based on the above network model, as shown in fig. 2, the present invention provides a SCMA network capacity analysis and hierarchical multicast resource allocation method, which includes:
1) Layering the original multicast data into base layer data and enhancement layer data; the base layer data is data which can be correctly received by all users in the multicast group; the enhancement layer data are data which are received in a differentiated mode according to users with different channel quality in the multicast group;
as shown in fig. 3, a system block diagram based on a hierarchical multicast policy in an SCMA network. The original multicast data is first encoded into a base layer and a plurality of enhancement layers. The base layer data requires that all users in the multicast group be able to receive correctly, and the multicast group users can decode the subsequent data correctly as long as they receive the base layer data correctly. The enhancement layer data adopts a differential receiving mode according to users with different channel quality in the multicast group, that is, the users with good channel quality can receive more enhancement layer data, and the users can recover the original data with higher quality by receiving more enhancement layer data. Sufficient codebooks are first allocated to the base layer data and, if there are remaining codebooks, to the enhancement layer data. The original multicast data is restored at the receiving end according to the allocation information of the codebook.
2) Performing codebook allocation and power allocation on the base layer data and the enhancement layer data;
the codebook allocation and power allocation for the base layer data and the enhancement layer data specifically include:
2.1, defining the multicast rate of the base layer data as:
wherein ,
indicating the rate at which the base layer data is required, h u,k Representing the channel gain of user u on subcarrier k, wherein +.>
η represents a path loss constant, d u Represents the distance from user u to the base station, alpha represents the path loss coefficient, ρ u,k Representing the Rayleigh fading of user u on subcarrier k, P b Representing the total power of the transmission base layer, which is equally distributed among LB codewords, delta 2 Representing noise power on a codebook in a broadcast channel; />
Representing a group of multicast users having the same QoS requirement and each employing a single antenna, the system bandwidth can be divided into a group of subcarrier sets with +.>
Meaning that the system bandwidth may be divided into a set of subcarriers, c= {1,..c., once again, C represents codebook set, ">
Representing a set of codebooks assigned to base layer data;
2.2, defining the multicast rate of the enhancement layer data as:
wherein ,Pe Representing the total power of the transmission enhancement layer, which is equally allocated to the LE codewords;
2.3, the capacity of the system is expressed as:
wherein the said
Representing the set of users meeting the enhancement layer minimum rate requirement,
/>
1. the capacity maximization allocation of the system is as follows:
3.1, a capacity maximization allocation formula is as follows:
the method meets the following conditions:
P b +P e ≤P,P b ≥0,P e ≥0 (c)
the constraint (b) indicates that the same codebook in the codebook set C cannot be allocated to the base layer and enhancement layer data at the same time. P due to limited total transmission power b and Pe The constraint (c) needs to be satisfied. The constraint (d) represents a minimum rate of the base layer and the enhancement layer guaranteeing the user's needs;
and 3.2, obtaining a solution of the capacity maximization allocation formula of the optimization problem by adopting a sub-optimization fast algorithm (FSA). The optimization problem is a hybrid combination problem. Although the best solution can be obtained by using the traversal search method, the computational complexity is high and is not suitable for the actual system, so in order to reduce the complexity, a sub-optimal fast algorithm (FSA) may be used. Thus, the invention provides a sub-optimal fast algorithm, which is divided into two stages of codebook allocation and power allocation.
4.1, codebook allocation stage:
in order to maximize system throughput, the codebook needs to be multi-allocated to the enhancement layer data. In the codebook allocation stage, the total power P of the base station is set to be equal power to be allocated to all codebooks, and the codebook allocation problem formula is as follows:
minB；
the method meets the following conditions:
then calculating the multicast rate on each codebook and arranging it in descending order, selecting the codebooks in order from high to low, and calculating the sum rate until the base layer rate is met;
the detailed codebook allocation procedure is as follows in algorithm 1:
4.2, power distribution stage:
the power allocation is performed after the codebook allocation is completed, and the purpose of the power allocation is to minimize P while preferentially guaranteeing QoS requirements of the base layer rates of all users b . The power allocation can be formulated as:
minP b
the method meets the following conditions:
codebook set when assigned to base layer
After being determined, R B The re-formulation is:
the above equation is a logarithmic function and the function is monotonically increasing, so when
At the time P b Obtaining a minimum value;
4.3 finally, the power allocation problem is converted to solve P b The problem of the B-th order polynomial of (2) is expressed as:
wherein ,
is a constant;
solving for P using Matlab b Power P of enhancement layer e ＝P-P b . Thereafter, set up
ε,P b and Pe And the capacity of the system is obtained.
3) After SCMA coding is carried out on the base layer data and the enhancement layer data after codebook allocation and power allocation, data transmission is carried out through a frequency selective channel, so that a receiving terminal recovers the original multicast data according to the allocation information of the codebook.
A hierarchical multicast strategy based on hierarchical coding is proposed in an SCMA network, and a capacity expression of the system is formulated. In order to further increase the system capacity, optimization problems are presented that maximize the system capacity based on resource constraints and guaranteed minimum base layer rate requirements. Consider that the optimization problem is a hybrid combination with high computational complexity. In order to reduce the computational complexity, therefore, a low-complexity sub-optimization algorithm is proposed.
Experimental simulation process:
as shown in fig. 4, the relationship between the number of multicast users and the system capacity is simulated. From simulations it can be seen that the system capacity when using a hierarchical multicast strategy increases with the number of users, the system capacity increases first and then decreases. However, the system capacity of an algorithm employing a hierarchical coding strategy is still higher than the system capacity (CM-SCMA or CM-OFDMA) employing a conventional multicast strategy for the same set of networks. This is because at the enhancement layer the user set
As the number of users in the multicast group increases, the number of users increases and then decreases, because of the increase in the number of bad users in the multicast group. Also, it is apparent that the multicast capacity of SCMA networks is higher than that of OFDMA networks. This also means that the FSA algorithm proposed by the present invention can achieve more system efficacy than using the epca algorithm.
First define user collection
Is>
The ratio of->
Indicating how many users in the multicast group can achieve higher quality QoS. Fig. 5 simulates the relationship of the number of users to λ. From simulations it can be seen that λ will continuously decrease as the number of users in the multicast group increases. This is because the base layer data needs to be guaranteed to be received correctly by each multicast user first, and therefore the transmission of this part of data is guaranteed first in the resource allocation. When the number of users increases, more resources need to be allocated for transmitting the base layer data, and thus physical resources allocated for transmitting the enhancement layer data are correspondingly reduced, so that the number of users capable of obtaining the enhancement layer data is reduced.
Fig. 6 and 7 simulate the average degradation probability of the proposed algorithm as described above as a function of the number of users and the total power of the base station. Fig. 5 shows that as the number of users increases, both the physical layer resources consumed by the base layer and the average degradation probability increase. This is because as the number of users increases, the probability of poor users occurring increases, and thus more physical resources are required to be allocated to the base layer for transmission, and thus the physical resources used to transmit enhancement layer data decrease, and thus the average degradation probability increases. Fig. 7 shows that as the total power of the base station increases, the average degradation probability also decreases. This is because as the total power of the base station increases, fewer physical resources can be provided to meet the base layer rate requirements and thus more physical resources can be provided to the enhancement layer. Under the same conditions, the average degradation probability of the SCMA network is lower than that of the OFDMA network.
Fig. 8 simulates the total power of a base station versus system capacity. At a transmission power of 26dBm, the system capacity of the FSA-SCMA approaches that of the CMS-SCMA. This is because the worst user in multicast has not yet reached the rate requirement to receive base layer data and therefore no physical resources can be provided to the user to transmit enhancement layer data. Similar to fig. 5, the system capacity in SCMA networks is better than OFDMA networks, especially at higher base station transmit powers.
Fig. 9 simulates minimum rate versus system capacity for base layer requirements. When (when)
When added, the system requires more physical resources. Thus reducing the physical resources provided to the enhancement layer transmission and therefore reducing system capacity. At the same time, it can be seen that the channel quality of the worst user has a greater impact on the capacity of the system. In SCMA networks and OFDMA networks, when all physical resources are used to transport base layer data, the layered multicast strategy is reduced to the traditional multicast strategy, i.e. +.>
From the above simulations, SCMA networks are preferred over OFDMA networks in terms of multicast transmission techniques because SCMA networks have load characteristics and utilize frequency resources more efficiently than OFDMA networks.
It will be apparent to those skilled in the art that the foregoing is merely illustrative of the preferred embodiments of this invention, and that certain modifications and variations may be made in part of this invention by those skilled in the art, all of which are shown and described with the understanding that they are considered to be within the scope of this invention.
Claims (1)
1. A method for SCMA network capacity analysis and hierarchical multicast resource allocation, comprising:
1) Layering the original multicast data into base layer data and enhancement layer data; the base layer data is data which can be correctly received by all users in the multicast group; the enhancement layer data are data which are received in a differentiated mode according to users with different channel quality in the multicast group;
2) Performing codebook allocation and power allocation on the base layer data and the enhancement layer data;
3) SCMA coding is carried out on the base layer data and the enhancement layer data after codebook allocation and power allocation, and then a channel is selected through frequency;
the step 2) of performing codebook allocation and power allocation on the base layer data and the enhancement layer data specifically includes:
2.1, defining the multicast rate of the base layer data as:
wherein ,
indicating the rate at which the base layer data is required, h u,k Representing the channel gain of user u on subcarrier k, where
η represents a path loss constant, d u Represents the distance from user u to the base station, alpha represents the path loss coefficient, ρ u,k Representing the Rayleigh fading of user u on subcarrier k, P b Representing the total power of the transmission base layer, which is equally distributed among LB codewords, delta 2 Representing noise power on a codebook in a broadcast channel; />
Representing a group of multicast users having the same QoS requirement and each employing a single antenna, the system bandwidth can be divided into a group of subcarrier sets with +.>
Meaning that the system bandwidth may be divided into a set of subcarriers, c= {1,..c., once again, C } representation codeThis set (I) is (are) of->
Representing a set of codebooks assigned to base layer data;
2.2, defining the multicast rate of the enhancement layer data as:
wherein ,Pe Representing the total power of the transmission enhancement layer, which is equally allocated to the LE codewords;
2.3, the capacity of the system is expressed as:
wherein the said
Representing the set of users meeting the enhancement layer minimum rate requirement,
wherein ,
channel gain for each subcarrier;
the capacity maximization allocation of the system is as follows:
3.1, a capacity maximization allocation formula is as follows:
the method meets the following conditions:
/>
P b +P e ≤P,P b ≥0,P e ≥0 (c)
wherein, epsilon= {1, e.. The term, E } represents a set of codebooks allocated to enhancement layer data; the constraint (b) indicates that the same codebook in the codebook set C cannot be allocated to the base layer and enhancement layer data at the same time; p due to limited total transmission power b and Pe The constraint (c) needs to be satisfied; the constraint (d) represents a minimum rate of the base layer and the enhancement layer guaranteeing the user's needs;
3.2, obtaining a solution of an optimization problem capacity maximization allocation formula by adopting a sub-optimization fast algorithm (FSA);
the sub-optimal fast algorithm (FSA) is:
4.1, codebook allocation stage:
let the total power P of the base station be the equal power distributed to all codebooks, the codebook distribution problem formula is:
minB；
the method meets the following conditions:
then calculating the multicast rate on each codebook and arranging it in descending order, selecting the codebooks in order from high to low, and calculating the sum rate until the base layer rate is met;
4.2, power distribution stage:
the power allocation can be formulated as:
minP b
the method meets the following conditions:
codebook set when assigned to base layer
After being determined, R B The re-formulation is:
the above equation is a logarithmic function and the function is monotonically increasing, so when
At the time P b Obtaining a minimum value;
4.3 finally, the power allocation problem is converted to solve P b The problem of the B-th order polynomial of (2) is expressed as:
wherein ,
is a constant;
solving for P using Matlab b Power P of enhancement layer e ＝P-P b The method comprises the steps of carrying out a first treatment on the surface of the Thereafter, set up
ε,P b and Pe And the capacity of the system is obtained. />
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|---|---|---|---|---|
| CN103051980A (en) * | 2012-06-29 | 2013-04-17 | 南京大学 | Method for carrying out resource distribution on OFDM (Orthogonal Frequency Division Multiplexing) system by adopting scalable video coding |
| CN103138892A (en) * | 2013-01-31 | 2013-06-05 | 西安电子科技大学 | Self-adaption relay communication method based on ladder modulation |
| CN106507485A (en) * | 2016-12-09 | 2017-03-15 | 北京邮电大学 | A kind of wireless layered multicast transfer resource distribution method of service-oriented quality |
| CN107873127A (en) * | 2015-07-10 | 2018-04-03 | 高通股份有限公司 | For reference signal and Signalling Designing of the legacy User Equipment as the non-orthogonal multiple of Primary layer |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150282185A1 (en) * | 2014-03-28 | 2015-10-01 | Futurewei Technologies, Inc. | Multi-user, multiple access, systems, methods, and devices |
| US10117120B2 (en) * | 2014-10-28 | 2018-10-30 | Qualcomm Incorporated | Channel feedback for non-orthogonal multiple access systems |
-
2018
- 2018-12-04 CN CN201811473236.1A patent/CN109413749B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103051980A (en) * | 2012-06-29 | 2013-04-17 | 南京大学 | Method for carrying out resource distribution on OFDM (Orthogonal Frequency Division Multiplexing) system by adopting scalable video coding |
| CN103138892A (en) * | 2013-01-31 | 2013-06-05 | 西安电子科技大学 | Self-adaption relay communication method based on ladder modulation |
| CN107873127A (en) * | 2015-07-10 | 2018-04-03 | 高通股份有限公司 | For reference signal and Signalling Designing of the legacy User Equipment as the non-orthogonal multiple of Primary layer |
| CN106507485A (en) * | 2016-12-09 | 2017-03-15 | 北京邮电大学 | A kind of wireless layered multicast transfer resource distribution method of service-oriented quality |
Non-Patent Citations (2)
| Title |
|---|
| A Mapping Scheme of Users to SCMA Layers for D2D Communications;Yanping Liu;《2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)》;20160707;全文 * |
| 稀疏码多址中多用户检测算法研究;马新迎;《信息科技辑》;20180815;全文 * |
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