CN106375258B - Multi-user bit likelihood ratio simplified calculation method based on table look-up method - Google Patents

Multi-user bit likelihood ratio simplified calculation method based on table look-up method Download PDF

Info

Publication number
CN106375258B
CN106375258B CN201610886892.9A CN201610886892A CN106375258B CN 106375258 B CN106375258 B CN 106375258B CN 201610886892 A CN201610886892 A CN 201610886892A CN 106375258 B CN106375258 B CN 106375258B
Authority
CN
China
Prior art keywords
user
likelihood ratio
bit likelihood
bit
exp
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201610886892.9A
Other languages
Chinese (zh)
Other versions
CN106375258A (en
Inventor
邓大椿
徐大专
戴晶晶
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing University of Aeronautics and Astronautics
Original Assignee
Nanjing University of Aeronautics and Astronautics
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Aeronautics and Astronautics filed Critical Nanjing University of Aeronautics and Astronautics
Priority to CN201610886892.9A priority Critical patent/CN106375258B/en
Publication of CN106375258A publication Critical patent/CN106375258A/en
Application granted granted Critical
Publication of CN106375258B publication Critical patent/CN106375258B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/345—Modifications of the signal space to allow the transmission of additional information
    • H04L27/3461—Modifications of the signal space to allow the transmission of additional information in order to transmit a subchannel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/3405—Modifications of the signal space to increase the efficiency of transmission, e.g. reduction of the bit error rate, bandwidth, or average power
    • H04L27/3411—Modifications of the signal space to increase the efficiency of transmission, e.g. reduction of the bit error rate, bandwidth, or average power reducing the peak to average power ratio or the mean power of the constellation; Arrangements for increasing the shape gain of a signal set
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/20—Control channels or signalling for resource management
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)

Abstract

The invention provides a multi-user bit likelihood ratio simplified calculation method based on a table look-up method.A base station needs MKThe calculated value of natural exponent item is set in table, when the bit likelihood ratio of some user needs to be calculated, the base station directly extracts the required exponent value from the table to make expn() Reducing the number of computations of an item to MKSecondly, exp is greatly reducedn() The calculation times of the method reduce the calculation complexity of the system and improve the acquisition efficiency of the bit likelihood ratio of each user.

Description

Multi-user bit likelihood ratio simplified calculation method based on table look-up method
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a multi-user bit likelihood ratio simplified calculation method.
Background
It is assumed that K users transmit data to the same base station through different channels simultaneously, all users adopt the same M-order modulation mode (i.e., MPSK, MQAM, etc.), and the channel factors of each channel are (h)1,...,hk,...,hK)，(X0,...,XM-1) Is (0, 1, M-1) at M (M ═ 2)m) The constellation mapping corresponding to the modulation of order,
Figure BDA0001128361530000011
the superposition of information input for each user and noise signals at a base station, wherein w is equivalent noise signals of all channels, the mean value of w is 0, and the variance is sigma2Gaussian distribution of (2), XkIs a constellation mapping of user k input values.
The existing multi-user bit likelihood ratio calculation formula is
Figure BDA0001128361530000012
Where the set B { x |0 ≦ x<M and b m′0, x ∈ Z is the set A { x |0 ≦ x<Bit b of M, x ∈ Z m′0 subset, and bit bm′The subset of 1 is C-a-B. When the method is adopted to calculate the likelihood ratio, the likelihood ratio calculation of each user is mutually independent, so the system calculates the natural index item with the times of KMK. In practice, the natural index terms that need to be computed for the likelihood ratios of different users are the same, only if these index terms are atWhether the formula denominator is a numerator, and MKThe secondary natural index term calculation is sufficient to satisfy the requirement of likelihood ratio calculation for each user. When the number of users is small, the calculated amount of the natural index item can be accepted; however, when the number of users is large (for example, 30 users), KM is usedKMuch greater than MKThis seriously affects the efficiency of the base station in calculating the likelihood ratio of each user. In a big data era, the number of users communicating with the same base station at the same time is gradually increased, and the calculation of the traditional multi-user likelihood ratio will certainly influence the efficiency of system communication.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a multi-user bit likelihood ratio simplified calculation method based on a table look-up method, and a base station needs MKThe calculated value of natural exponent item is set in table, when the bit likelihood ratio of some user needs to be calculated, the base station directly extracts the required exponent value from the table to make expn() Reducing the number of computations of an item to MKSecondly, exp is greatly reducedn() The calculation times of the method reduce the calculation complexity of the system and improve the acquisition efficiency of the bit likelihood ratio of each user.
The technical solution for realizing the purpose of the invention is as follows:
a multi-user bit likelihood ratio simplified calculation method based on a table look-up method comprises the following steps:
step 1 Generation of 3 × (M)K+1) lookup table: the first row is an address column, and is K-bit M-system representation of a serial number column notation n, wherein n is a positive integer; the second row is the sequence number column, and the set { x |0 ≦ x<MKElements in x ∈ Z are placed sequentially in the 2 nd to M th rowsK+1 columns; third behavior expn() A fence; wherein M is 2mThe modulation order adopted by the system is m, which is a positive integer, and K is the number of system users;
step 2: updating a lookup table: when the base station receives the superposed symbol y, the channel attenuation factor (h) of the sub-channel corresponding to each user is determined according to the channel attenuation factor1,...,hk,...,hK) Updating expn() All elements in a column;
and step 3: calculating the bit likelihood ratio of each user by means of a lookup table;
and 4, step 4: and when the base station receives a new superposed symbol y, repeating the step 2 and the step 3.
Further, the simplified calculation method of the multi-user bit likelihood ratio based on the table look-up method of the present invention, the superposition symbol y in step 2 is:
Figure BDA0001128361530000021
wherein y represents the superposition of each user input information and noise signal in the base station, w is the equivalent noise signal of all channels, and w obeys mean value of 0 and variance of sigma2Gaussian distribution of (2), XkIs a constellation mapping of the input values of user k, where k represents the kth user.
Furthermore, the invention discloses a multi-user bit likelihood ratio simplified calculation method based on a table look-up method, and exp corresponding to the sequence number n in the step 1n() Column value calculation formula and updating exp in step 2n() The formula for all elements in the column is:
Figure BDA0001128361530000022
wherein h is1...hKChannel attenuation factor, σ, of subchannels corresponding to K users2For equivalent noise power spectral density of all channels, B1...BKSubscripts mapped for each user constellation.
Furthermore, the invention discloses a simplified calculation method of multi-user bit likelihood ratio based on table lookup, wherein the formula for calculating the bit likelihood ratio of the user in step 3 is as follows:
Figure BDA0001128361530000031
wherein, bm′The m ' th bit (m ' is more than or equal to 0 and less than or equal to m ') when the kth user is converted into a binary system, mod (x, y) represents that x is left over y, and b, i and j are transition variables and have no practical meaning.
Furthermore, the simplified calculation method of the multi-user bit likelihood ratio based on the table look-up method of the present invention can calculate the bit likelihood ratio of the user according to the address look-up mode in step 3, and the steps are as follows:
step 3-1: in set A: { x | 0. ltoreq. x<M, x ∈ Zm′Subset B of 0: { x | 0. ltoreq. x<M and b m′0, x ∈ Z, resulting in bit bm′The subset of 1 is C-a-B;
step 3-2: calculating the bit likelihood ratio of user k:
Figure BDA0001128361530000032
wherein x iskIs the input value of user k.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
the method of the invention can greatly reduce exp under the condition of more users by utilizing the lookup tablen() The calculation times of the method reduce the calculation complexity of the system and improve the acquisition efficiency of the bit likelihood ratio of each user.
Drawings
FIG. 1 shows that the K user of the present invention is at M (M ═ 2)m) A lookup table in a step modulation mode;
fig. 2 is a lookup table of the K user in the BPSK modulation scheme according to the present invention;
FIG. 3 is a lookup table of the K user of the present invention under 8-order (8QAM, 8PSK, etc.) modulation;
FIG. 4 is a lookup table of the K user of the present invention under a 16-order (16QAM, 16PSK, etc.) modulation scheme;
FIG. 5 is a lookup table of K users in 32-order (32QAM, 32PSK, etc.) modulation modes according to the present invention;
fig. 6 is a look-up table of the K user of the present invention in a 64-order (64QAM, 64PSK, etc.) modulation scheme.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention provides a multi-user bit likelihood ratio simplified calculation method based on a table look-up method, which specifically comprises the following steps as shown in figure 1:
step 1 Generation of 3 × (M)K+1) lookup table: the first row is an address column, and is K-bit M-system representation of a serial number column notation n, wherein n is a positive integer; the second row is the sequence number column, and the set { x |0 ≦ x<MKElements in x ∈ Z are placed sequentially in the 2 nd to M th rowsK+1 columns; third behavior expn() A fence; wherein M (M ═ 2)m) The modulation order adopted by the system is m, which is a positive integer, and K is the number of system users.
If n corresponds to the address bmbm-1…b1Then the address indicates that the input of user 1 at this time is bmThe input of user 2 is bm-1,.., the input of user k is b1Wherein b isiIs an M-system value; exp corresponding to the number nn() The column value is calculated by the formula:
Figure BDA0001128361530000041
wherein h is1...hKChannel attenuation factor, σ, of subchannels corresponding to K users2Noise power spectral density of an equivalent channel of K sub-channels, B1...BKSubscripts mapped for each user constellation.
Step 2: updating a lookup table: when the base station receives the superposed symbol y, the channel attenuation factor (h) of the sub-channel corresponding to each user is determined according to the channel attenuation factor1,...,hk,...,hK) Updating expn() All elements in a column.
Wherein, the superposition symbol y is:
Figure BDA0001128361530000042
wherein y represents the superposition of each user input information and noise signal in the base station, w is the equivalent noise signal of all channels, and w obeys mean value of 0 and variance of sigma2Gaussian distribution of (2), XkIs a constellation mapping of the input values of user k, where k represents the kth user.
Updating expn() The formula of the elements in the column adopts exp in step 1n() And (4) column value calculation formula.
And step 3: by means of a look-up table, the bit likelihood ratio of each user is calculated.
The formula for calculating the bit likelihood ratio of a user is:
Figure BDA0001128361530000043
wherein, bm′The m ' th bit (m ' is more than or equal to 0 and less than or equal to m ') when the kth user is converted into a binary system, mod (x, y) represents that x is left over y, and b, i and j are transition variables and have no practical meaning.
Namely: will look up bit b in the tablem′0 (b of user k)m′Bits) corresponding to all expn() The sum of (a) and (b)m′All exp corresponding to 1n() The ratio of the sum of (a) and (b) is taken from the natural logarithm. The formula aims at finding the bit b of user k in the look-up tablem′Respectively taking the values of all subscripts n of 0 and 1, and then directly acquiring corresponding exp according to the subscript serial numbern() Values to calculate likelihood ratios.
In addition, the invention also provides a method for searching and calculating the bit likelihood ratio of the user according to the address, which comprises the following steps:
step 3-1: in set A: { x | 0. ltoreq. x<M, x ∈ Zm′Subset B of 0: { x | 0. ltoreq. x<M and b m′0, x ∈ Z, resulting in bit bm′The subset of 1 is C-a-B;
step 3-2: calculating the bit likelihood ratio of user k:
Figure BDA0001128361530000051
wherein x iskIs an input value of user k, i.e. LL Rk,m′Exp corresponding to all addresses belonging to set B for the k-th bit value of an addressn() Exp of sum of terms corresponding to all addresses whose k-th bit belongs to set Cn() The natural logarithm of the sum ratio of the terms.
And 4, step 4: and when the base station receives a new superposed symbol y, repeating the step 2 and the step 3.
Fig. 2-6 are look-up tables for K users using BPSK, 8, 16, 32, and 64 modulation schemes, respectively.
The foregoing is directed to embodiments of the present invention and, more particularly, to a method and apparatus for controlling a power converter in a power converter, including a power converter, a power.

Claims (3)

1. A multi-user bit likelihood ratio simplified calculation method based on a table look-up method is characterized by comprising the following steps:
step 1 Generation of 3 × (M)K+1) lookup table: the first row is an address column, and is K-bit M-system representation of a serial number column notation n, wherein n is a positive integer; the second row is the sequence number column, and the set { x |0 ≦ x<MKElements in x ∈ Z are placed sequentially in the 2 nd to M th rowsK+1 columns; third behavior expn() A fence; wherein M is 2mThe modulation order adopted by the system is m, which is a positive integer, and K is the number of system users;
step 2: updating a lookup table: when the base station receives the superposed symbol y, the channel attenuation factor (h) of the sub-channel corresponding to each user is determined according to the channel attenuation factor1,...,hk,...,hK) Updating expn() All elements in a column;
and step 3: calculating the bit likelihood ratio of each user by means of a lookup table;
and 4, step 4: when the base station receives a new superposed symbol y, repeating the step 2 and the step 3;
the superposition symbol y in step 2 is:
Figure FDA0002336360230000011
wherein y represents the superposition of each user input information and noise signal in the base station, w is the equivalent noise signal of all channels, and w obeys mean value of 0 and variance of sigma2Gaussian distribution of (2), XkIs a constellation mapping of user k input values, where k represents the kth user;
exp corresponding to sequence number n in step 1n() Column value calculation formula and updating exp in step 2n() The formula for all elements in the column is:
Figure FDA0002336360230000012
wherein h is1...hKChannel attenuation factor, σ, of subchannels corresponding to K users2For equivalent noise power spectral density of all channels, B1...BKSubscripts mapped for each user constellation.
2. The simplified calculation method for multi-user bit likelihood ratio based on table lookup as claimed in claim 1, wherein the formula for calculating the bit likelihood ratio of the user in step 3 is:
Figure FDA0002336360230000013
wherein, bm′The m ' th bit (m ' is more than or equal to 0 and less than or equal to m ') when the kth user is converted into a binary system, mod (x, g) represents that x takes the remainder of g, and b, i and j are transition variables and have no practical meaning.
3. The simplified calculation method for multi-user bit likelihood ratio based on table lookup as claimed in claim 2, wherein in step 3, the bit likelihood ratio of the user can be calculated by address lookup, and the steps are:
step 3-1: in set A: { x | 0. ltoreq. x<M, x ∈ Zm′Subset B of 0: { x | 0. ltoreq. x<M and bm′0, x ∈ Z, resulting in bit bm′The subset of 1 is C-a-B;
step 3-2: calculating the bit likelihood ratio of user k:
Figure FDA0002336360230000021
wherein x iskIs the input value of user k.
CN201610886892.9A 2016-10-11 2016-10-11 Multi-user bit likelihood ratio simplified calculation method based on table look-up method Active CN106375258B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610886892.9A CN106375258B (en) 2016-10-11 2016-10-11 Multi-user bit likelihood ratio simplified calculation method based on table look-up method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610886892.9A CN106375258B (en) 2016-10-11 2016-10-11 Multi-user bit likelihood ratio simplified calculation method based on table look-up method

Publications (2)

Publication Number Publication Date
CN106375258A CN106375258A (en) 2017-02-01
CN106375258B true CN106375258B (en) 2020-07-24

Family

ID=57895391

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610886892.9A Active CN106375258B (en) 2016-10-11 2016-10-11 Multi-user bit likelihood ratio simplified calculation method based on table look-up method

Country Status (1)

Country Link
CN (1) CN106375258B (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7457367B2 (en) * 2004-07-07 2008-11-25 University Of Utah Research Foundation Detector and method for estimating data probability in a multi-channel receiver
CN104184552A (en) * 2014-08-12 2014-12-03 中国科学院计算技术研究所 Soft demodulation method and soft demodulation system applicable to QAM (Quadrature Amplitude Modulation) of Gray mapping

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7457367B2 (en) * 2004-07-07 2008-11-25 University Of Utah Research Foundation Detector and method for estimating data probability in a multi-channel receiver
CN104184552A (en) * 2014-08-12 2014-12-03 中国科学院计算技术研究所 Soft demodulation method and soft demodulation system applicable to QAM (Quadrature Amplitude Modulation) of Gray mapping

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Efficient Demodulation of General APSK Constellations;Magnus Sandell,Filippo Tosato,Amr Ismail;《IEEE Signal Processing Letters》;IEEE;20160428;第23卷(第6期);868-871 *

Also Published As

Publication number Publication date
CN106375258A (en) 2017-02-01

Similar Documents

Publication Publication Date Title
CN106576024B (en) System and method for generating codebook with small projections in each complex dimension and application thereof
CN104769875B (en) It is transmitted using the spectral efficient of Orthogonal Frequency Division Multiplexing
CN107948113B (en) The method and system for reducing ofdm system peak-to-average power ratio are inserted into based on three dimensional signal
CN112532351B (en) Interleaving transmission method for weighted fractional Fourier transform frequency domain two-component signal
CN108476550A (en) The communication of the specific control information of user in wireless network
CN105723673B (en) A kind of high order modulation, demodulating equipment, method and system
CN107222293A (en) A kind of information transferring method, device, electronic equipment and storage medium
US20060156087A1 (en) Bit distributor for multicarrier communication systems employing adaptive bit loading for multiple spatial streams and methods
CN112491774B (en) Orthogonal frequency division multiplexing method and system based on multi-dimensional signal index modulation
CN105141563A (en) Space frequency combined modulation design scheme used for MIMO-OFDM system
CN107438047A (en) The phase noise based on decision-feedback corrects compensation method certainly in a kind of single-carrier frequency domain equalization system
CN111865383A (en) Spatial constellation design system in spatial modulation system
CN107508657A (en) A kind of SCMA multi-user test methods based on weight factor message transmission
CN104956636B (en) The method and apparatus that frequency orthogonal amplitude modulation is supported in wireless communication system
CN107995139A (en) A kind of Orthogonal Frequency Division Multiplexing index modulation transmission method of efficient, high-performance and low complex degree
CN105743617A (en) Hybrid spatial modulation method based on Euclidean distance and antenna selection
Ibraheem et al. PTS method with combined partitioning schemes for improved PAPR reduction in OFDM system
CN112929057A (en) Dual generalized spatial modulation method and system
WO2017129128A1 (en) Information modulation method and apparatus
CN106375258B (en) Multi-user bit likelihood ratio simplified calculation method based on table look-up method
CN101971587B (en) Method for accelerating the precoding and pre-decoding of symbols in OFDM systems
CN110381003B (en) Multi-user signal detection method aiming at peak-to-average ratio suppression in SCMA-OFDM system
CN112702298A (en) OFDM signal transmission method for expanding mixed carrier wave precoding
CN111865384A (en) Generalized spatial modulation system based on multidimensional index and improvement method of modulation constellation thereof
CN101971588B (en) Techniques for multiple-subcarrier joint precoding

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant