CN115102821A - Generalized orthogonal reflection modulation method combined with intelligent reflection surface grouping planning mapping - Google Patents
Generalized orthogonal reflection modulation method combined with intelligent reflection surface grouping planning mapping Download PDFInfo
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Abstract
The invention discloses a generalized orthogonal reflection modulation (JGD-GQRM) method combined with Intelligent Reflection Surface (IRS) grouping planning mapping and a system aiming at single Radio Frequency (RF) Multiple Input Multiple Output (MIMO). In JGD-GQRM, a limited number of IRS elements are spatially grouped and jointly mapped with the remaining spatial subset of IRS to improve the reliability of the system transmission. In addition, additional information bits are mapped by IRS total reflection passive beamforming to improve the Spectral Efficiency (SE) of the system. In addition to an optimal Maximum Likelihood (ML) detector with higher complexity, a low complexity sequential greedy detection method (SGD) for JGD-GQRM is proposed. Simulation results show that compared with the existing reflection modulation and joint mapping method, the modulation method has better Bit Error Rate (BER) performance.
Description
Technical Field
The invention relates to the technical field of communication, in particular to an IRS auxiliary MIMO system, index modulation, generalized orthogonal reflection modulation and IRS space grouping planning, which mainly improves the reliability and transmission rate of the system. In particular to a generalized orthogonal reflection modulation method combined with IRS grouping planning mapping.
Background
As the demand for wireless communication is higher and higher, wireless networks are developed to a larger scale and a higher frequency band, and various innovative wireless communication technologies are continuously appearing to meet the increasing demand for higher transmission rate, such as millimeter wave (mmWave) communication, Multiple Input Multiple Output (MIMO) system, Index Modulation (IM) technology, but they suffer from high hardware cost and power consumption, which makes them competitive in the development of the sixth generation mobile communication system (6G). In recent years, an Intelligent Reflective Surface (IRS) has attracted wide attention in the communication field, where the IRS is composed of a large number of low-cost passive reflective units, and transmission based on the IRS is completely different from existing MIMO, backscatter communication, and other technologies, and it can reflect an incident signal with a specific reflection coefficient and change the amplitude, phase, and the like of the incident signal, which makes it possible to improve communication performance in a greener manner.
In the last decades, Spatial Modulation (SM), a spatial multiplexing technique in MIMO systems, has been widely used, and has characteristics of high transmission efficiency and low power consumption by activating a radio frequency chain to transmit a constellation symbol and performing information transmission in each time slot using an index of an active antenna. Inspired by SM technology, some researchers have developed many variations of SM techniques to improve the spectral efficiency of SM, including Generalized Spatial Modulation (GSM), Quadrature Spatial Modulation (QSM), Receive Spatial Modulation (RSM), and so on. However, the spectrum leakage and hardware loss caused by the high-speed antenna switching mechanism still make SM and its variants face some challenges. Therefore, combining the challenges faced by SM with the advantages of IRS, studies of SM and related IM have begun to be applied to IRS, where information bits are mapped to reflection unit indices to invisibly convey messages, and index-based modulation and IRS-based modulation may highlight the advantages of IRS. Previous scholars considered that an IRS reflected an incident signal while carrying information bits with reflective elements in an on/off state, specifically grouping all the transmitting units on the IRS, and opening a group of reflective units by a group index to implement spatial modulation (IRS-SM), since a small number of IRS elements are used for reflection, so that the large-scale aperture gain inherent to the IRS is reduced. Researchers have subsequently proposed the concept of reflective mode modulation (RPM) that improves the performance gain of IRS-SM by grouping IRS and then selecting a group of off transmissions, in the same way as IRS-SM activates IRS, using a large number of reflective elements. It is worth mentioning that the power of the effective received signal and the signal-to-noise ratio of the received signal are limited because the on/off state of the reflective modulation does not make full use of the IRS reflective elements.
To overcome the above problems, researchers have proposed IRS-assisted orthogonal reflection modulation (IRS-QRM), which, unlike the above reflection modulation, divides the IRS into two subsets for reflecting the incident signal to two orthogonal directions, respectively, to increase the received signal power, but causes performance degradation due to high correlation between inter-channel interference (ICI) and adjacent combined IRS. On the basis of on/off reflection modulation, researchers put forward a concept of joint mapping reflection modulation (JRM), so that the method design of bit mapping is more flexible, and therefore the JRM is superior to other reflection modulation schemes. In addition, a large number of researchers also consider the SM based on IRS at the receiving end, and implement coherent superposition of reflected signals on the desired antenna by setting perfect reflected phase shift for IRS, so as to activate specific receiving antenna indexes to carry information and utilize the suboptimal detector with maximum energy to trade off between performance and complexity, and the performance loss is related to the number of IRS.
It can be seen that the utilization of IRS index to transmit information bits in the existing research to improve the system performance has been widely used, which provides more opportunities for new modulation schemes. It is worth noting that since IRS grouping affects both spectral efficiency SE and BER performance, little research has been done in the past on how to design IRS grouping and active reflection units. Furthermore, IRS enables the system to carry more information bits, however, as the number of bits increases, decoding of the receiver information is a significant challenge.
Disclosure of Invention
Aiming at the defects in the background technology, the invention provides an IRS (inter-range communication) grouping planning method based on a maximized minimum Hamming distance and a minimized activation probability inequality and a joint mapping codebook screening method based on a maximized Euclidean distance, and finally, a generalized orthogonal reflection modulation method for joint IRS grouping planning mapping is obtained.
The invention is realized by adopting the following technical scheme:
a generalized orthogonal reflection modulation (JGD-GQRM) method combined with IRS grouping planning mapping is realized based on a system with a single transmitting antenna and a root receiving antenna assisted by N Intelligent Reflection Surface (IRS) units, and the modulation method comprises the following steps:
1) grouping input bit streams of JGD-GQRM, each group being B bits, where B ═ B 1 +B 2 ，B 1 ＝log 2 N r Bit bits for selecting N r Root receive antenna index and N r The power of N of 2 must be satisfied,
bit bits for selecting a joint mapping codebook x m Wherein
Q is the number of IRS generalized orthogonal reflection modes, M is the number of M-QAM constellation symbols,
indicating a rounding down.
2) Dividing N reflective elements of an IRS into adjacent N g Groups of N/N g A number of reflecting units (assuming that N can be defined by N) g Integer division) from N g In the group, K is activated, 1 & ltK & ltN g Group IRS elements for producing in-phase signals, the remaining N g -K sets for generating orthogonal signals, in common
A subset of space
Wherein
Denotes a binomial coefficient, r' q From K1 and N g -K j,1 indicating the set of IRS elements for in-phase reflection, j indicating the set of IRS elements reflection phase clockwise rotation
Namely, it is
Representing the coefficients of a binomial expression. Generalized orthogonal reflection mode of a system
May be defined by a spatial subset r q ' carrying out N/N g Obtained by fractional expansion, e.g. r' ═ 1, j,1] T ，N/N g ＝2， r q ＝[1,1,j,j,1,1] T ，q＝1,2,…,Q。
3) From
A subset of space
Selecting Q space subsets for information transmission; and (3) screening Q space subsets which meet the requirement from all possible space subsets based on the inequalities of the maximum minimum Hamming distance and the minimum activation probability:
first, all possible spatial subsets are obtained by permutation and combination
Then selecting t groups of candidate combinations to be recorded as
Each group of candidate combinations
Require a reaction from R all In the process, Q is selected t One spatial subset r' and Hamming (r) must be satisfied between any two spatial subsets i ′,r j ') ≧ h, (i ≠ j) where Hamming (· denotes the Hamming distance between two vectors, Q t Is a variable related to t, h represents the minimum hamming distance between any two r's between IRS spatial subsets, h is 2,4, …, 2K; in determining Hamming distance threshold h and corresponding candidate combination
Then, obtaining an optimal group of space sets through a constraint condition of a minimum activation probability inequality and recording the optimal group of space sets as R opt ；
4) To R opt In each spatial subset to perform N/N g Partial expansion to obtain generalized orthogonal reflection mode set
5) Constructing a joint mapping codebook x l ＝s i ·r q 1,2, …, Q.M, where s i For a power normalized constellation symbol, i ═ 1,2, …, M, satisfies E [ | s i | 2 ]＝1；r q The epsilon R is the optimal generalized orthogonal reflection mode after IRS grouping planning, all reflection modes participate in mapping, and the limitation that Q must be 2 in the traditional mapping is eliminated. Joint mapping of codebook x in JGD-GQRM l The upper bound of BER of can be expressed as:
wherein, the first and the second end of the pipe are connected with each other,
denotes x m And
the number of erroneous bits of the corresponding binary bit,
the pair-wise error probability of x is represented,
can be expressed as:
wherein Q (-) represents the right tail function of a standard normal distribution,
indicating that under known channel conditions, both codebooks are at a distance, observing equation (11) reveals that the upper bound on BER can be increased
Is used to reduce, i.e. maximize, the minimum inter-codebook euclidean distance.
6) Screening out Q.M combined mapping codebooks based on maximized minimum Euclidean distance
Transmitting the optimal codebooks;
7) considering that the transmission path of the transmitting end and the receiving end is blocked by the obstacle, the links of the transmitting end-IRS and the IRS-receiving end are respectively
And
each element thereof
All have zero mean and independent unit variance and obey Gaussian distribution CN (0,1), alpha n And beta k,n Is the amplitude of the channel and is,
and phi k,n Is the channel phase, k is 1,2, …, N r N is 1,2, …, N, generalized orthogonal reflection pattern r q Each element in (1) is denoted as r i 1, 2. Assuming that the receiving end activates the kth antenna, the snr of the signal received by the antenna can be expressed as:
in order to maximize the signal-to-noise ratio of the kth receiving antenna, the invention adopts a direct phase cancellation mode to optimize the beam forming phase, namely
The IRS phase matrix may be represented as
8) Receiving a signal assuming that the channel state information is completely known
Can be expressed as:
y＝Gdiag(Θ)diag(r q )Hs i +v (12)
where diag (-) represents the diagonal matrix of elements on the main diagonal,
is additive white Gaussian noise AWGN, which follows the distribution CN (0, N) 0 I Nr ) Wherein, I Nr Representing the identity matrix, N 0 Is the complex noise variance;
9) the receiver restores the signal to the original information bits.
In the above technical solution, further, in step 3): screening Q space subsets which meet the requirement from all possible space subsets based on the maximum minimum Hamming distance and the minimum activation probability inequality, specifically:
3.1) obtaining all possible spatial subsets by permutation and combination
Randomly generating an index value
And creates an empty set U and an empty set
R is to be all The second ind element
Put in a set U, Q t 1 is used for representing the number of space subsets stored in the set U, and a minimum Hamming distance threshold value h is set;
3.2) according to R all Sequentially carrying out Hamming distance judgment on the spatial subsets in the current set U from small to large indexes of the intermediate spatial subsets
j＝1,2,...,Q t If it is, if
If all the space subsets in the current set U meet the Hamming distance requirement, the set U will be used
Store in the set U, Q t Plus 1 for the number of spatial subsets in the recording set U.
3.3) will traverse one pass R all Of screening
Is stored in
In the step (3), after repeating the steps from the step (3.1) to the step (3.2) t times,
3.4) since the difference of the randomly generated index values in step 3.1) will affect the difference of the final sets U in step 3.3), the threshold h and the corresponding candidate set are determined
Then, assemble the
An optimal set of spatial subsets is screened from the t sets of candidate sets by equation (9),
at the minimum, it represents
The spatial subset combination in (1) is optimal, and formula (9) is as follows:
wherein, the first and the second end of the pipe are connected with each other,
to represent
Middle ith space subset, | · | | non-woven phosphor 1 Represents a norm of 1 when
Is shown as
With equal probability for each set of IRS elements used to generate the in-phase and quadrature signals.
3.5) will be optimalA group of
Is denoted by R opt The number of the groups is Q,
Q＝Q p 。
further, the step 6) is specifically as follows:
6.1) generating all candidate joint mapping codebook vector sets by using constellation symbols and the screened space subsets
The number of codebooks to be rejected is N re ＝Q·M-N c Calculating X all The Euclidean distance between any two codebooks is recorded as
Wherein | · | charging F Represents Frobenius norm, V d The values of (c) and the index tuples (i, j) of the two corresponding codebooks are respectively stored into an empty set X value And X index In (1).
6.2) to X value Sorting the elements in the set from small to large to obtain sorted index value set I, such as X before sorting value ＝[3,5,1]After sorting X value ＝[1,3,5]The sorted index set I ═ 3,1,2]。
6.3) index with the elements in set I index Reordering, e.g. X before ordering value ＝[8,6,4]，X index ＝[(1,2),(1,3),(2,3)]，I＝[3,1,2]After sorting X index ＝[(2,3),(1,2),(1,3)]。
6.4) from sorted X index Intercepting the first half of tuples (i, j) in the set, counting the total frequency of two codebook indexes in each tuple, and sequencing from large to small; and if the number of the elements in the set is an odd number, rounding up the decimal of which the half number is intercepted.
6.5) advancing codebook index frequency by N re Personal codeFrom X all Removing and recording the rest codebook set as
Further, in step 9), the receiver may recover the initial information bits using a maximum likelihood detection method:
wherein, theta k Indicating the beamforming phase matrix corresponding to the kth receiving antenna,
and
respectively representing the information bit index corresponding to the joint mapping codebook restored by the ML detection method and the information bit index corresponding to the receiving antenna.
The receiver restores the initial information bits by using an SGD detection method, which specifically comprises the following steps:
a)Λ＝(Λ out ,Λ in ) Given number of iterations, Λ, as a continuous greedy detector (SGD) out 、Λ in ∈{1,2,…,N r Denotes detection B respectively 1 Number of iterations of bit and detection B 2 Bit time new vector
With new channel matrix
Of (c) is calculated. The receive antenna indices are sorted by energy size using a greedy detector:
wherein the content of the first and second substances,
representing the ordering of element values from large to small and returning their index values,
indexes ordered for y, e.g.
b) Selecting
Front Λ out Front Λ in The front antennas are indexed and used respectively
And
as a new receiving antenna index set and a detection dimension index set.
c) Redefining receiver vectors
i＝1,2,…,Λ out And channel matrix
j＝1,2,…,Λ in SGD detection is:
the complexity of the ML detector in the multiplication operation is according to equation (14):
the complexity of the SSD detector in the multiplication operation according to equation (16) is:
the invention principle of the invention is as follows:
in order to improve the signal-to-noise ratio of a received signal, the IRS is wholly divided into two subsets to respectively generate in-phase and orthogonal signals, each subset comprises a plurality of groups of IRS elements, all IRS space subsets are screened under the constraint condition based on the maximized minimum Hamming distance and the minimized probability, and the optimal reflection mode combination meeting the requirements is obtained to reduce the correlation between the IRS generalized orthogonal reflection modes. All the optimal reflection modes participate in codebook mapping so as to efficiently screen the joint mapping codebook based on the minimum Euclidean distance between the maximized codebooks and improve the reliability of transmission. In order to optimize the calculation complexity of the detector, after the receiver measures the power of the receiving antennas, the receiving antenna indexes are sorted according to the energy, and the detection times of the receiving end indexes and the dimensionality of the detection matrix operation are respectively reduced through the sorted antenna indexes.
The invention has the advantages and beneficial effects that:
the invention provides a generalized orthogonal reflection modulation method combining IRS grouping planning mapping, wherein a transmitter and an IRS jointly map a group of information bits, and the IRS performs total reflection to maximize received signal power and spectral efficiency when used for information transmission. The reliability of system transmission is improved by spatially grouping a limited number of IRS elements and performing joint mapping by using the remaining IRS spatial subsets, so that the method is not only suitable for generalized orthogonal reflection modulation, but also suitable for generalized spatial reflection modulation, and simulation results show that the JGD-GQRM is superior to the existing reflection modulation scheme. In addition, the invention also provides a low-complexity detection method, which reduces the process of exhaustive search and provides BER performance close to the optimal detector while keeping lower computation complexity.
Drawings
Fig. 1 is a schematic diagram of an embodiment of a generalized orthogonal reflection modulation transmission method of joint IRS packet planning mapping according to the present invention;
fig. 2 is a comparison of generalized orthogonal reflection modulation with joint IRS block-wise planning mapping proposed according to the present invention with other existing reflection modulation schemes under the same parameter configuration;
fig. 3 is a bit error rate performance comparison between a continuous greedy detector proposed according to the invention and an optimal Maximum Likelihood (ML) detector and a conventional Greedy (GD) detector, respectively, under different parameter configurations.
Detailed Description
Referring to fig. 1, which is a schematic diagram of a generalized ofdm transmission system combining IRS packet planning mapping according to the present invention, an uplink wireless communication system model is considered that consists of an rf source S and an ofdm signal with N r The destination D of the root receiving antenna. Since there is an obstacle between S and D and there is no direct-view transmission path, an IRS composed of N reflection units is deployed to assist information transmission from S to D. Where H denotes the channel link from S to IRS and G denotes the channel link from IRS to D.
A generalized orthogonal reflection modulation method combining IRS grouping planning mapping is based on a single transmitting antenna assisted by an IRS unit with N Intelligent Reflection Surfaces (IRS) and N r The system for receiving antennas is modulated using an M-QAM constellation. The modulation method specifically comprises the following steps:
1) grouping input bit streams of JGD-GQRM, each group being B bits, where B ═ B 1 +B 2 ，B 1 ＝log 2 N r Bit bits for selecting N r Root receive antenna index and N r The power of N of 2 must be satisfied,
bit bits for selecting a joint mapping codebook x m Wherein
Q is IRSThe number of generalized orthogonal reflection modes, M is the number of M-QAM constellation symbols,
meaning rounding down.
2) Dividing N reflecting elements of IRS into adjacent N g Groups of N/N g A number of reflecting units (assuming that N can be defined by N) g Integer division) from N g In the group, K is activated, 1 < K < N g Group IRS elements for producing in-phase signals, the remaining N g -K sets for generating orthogonal signals, in common
A subset of space
Wherein
Denotes a binomial coefficient, r' q From K1 and N g -K j,1 indicating the set of IRS elements for in-phase reflection, j indicating the set of IRS elements reflection phase clockwise rotation
Generalized orthogonal reflection mode of a system
May be defined by a spatial subset r q ' carry out N/N g Obtained by fractional expansion, e.g. r' ═ 1, j,1] T ，N/N g ＝2，r q ＝[1,1,j,j,1,1] T ，q＝1,2,…,Q。
3) Assuming that a total of Q spatial subsets are adopted for information transmission, Q spatial subsets meeting requirements are screened out from all possible spatial subsets based on the inequalities of maximizing minimum Hamming distance and minimizing activation probability:
first, all possible spatial subsets are obtained by permutation and combination
Then selecting t groups of candidate combinations to be recorded as
Each group of candidate combinations
Require a reaction from R all In the process, Q is selected t One spatial subset r' and any two spatial subsets must satisfy Hamming (r) i ′,r j ') ≧ h, (i ≠ j) where Hamming (·,) represents the Hamming distance between two vectors, Q t Is a variable related to t, h represents the minimum hamming distance between any two r's in the IRS space subset, h is 2,4, …, 2K. In determining the Hamming distance threshold h and corresponding candidate combinations
Then, obtaining an optimal group of space sets by minimizing the constraint condition of the activation probability inequality as R opt 。
Screening out the Q space subsets which meet the requirements specifically comprises the following steps:
3.1) obtaining all possible spatial subsets by permutation and combination
Randomly generating an index value
And creates an empty set U and an empty set
R is to be all Element of middle ind
Put into the set U, Q t 1 is used to represent the number of space subsets stored in the set U, and a minimum hamming distance threshold h is set.
3.2) according to R all Sequentially carrying out Hamming distance judgment on the spatial subsets in the current set U from small to large indexes of the middle spatial subsets
j＝1,2,...,Q t If it is, if
If the space subset in the current set U meets the requirement of Hamming distance, the space subset is determined to be the same as the space subset in the current set U
Into the set U, Q t Plus 1 for the number of spatial subsets in the recording set U.
3.3) to filter through
Is stored in
After repeating the steps 3.1) to 3.2) t times,
3.4) since the difference of the randomly generated index values in step 3.1) will affect the difference of the final set U in step 3.3), the threshold h and the corresponding candidate set are determined
Then, assemble the
An optimal set of spatial subsets is selected from the t sets of candidate sets by equation (19),
at the minimum, it represents
In the space ofSet combination is optimal, and equation (19) is as follows:
wherein, the first and the second end of the pipe are connected with each other,
represent
Middle ith space subset, | · | | non-woven phosphor 1 Represents a norm of 1 when
Is shown as
With equal probability for each set of IRS elements used to generate the in-phase and quadrature signals.
1.6) grouping the optimal groups
Is denoted by R opt The number of the groups is Q,
Q＝Q p 。
4) to R opt In each spatial subset to perform N/N g Partial expansion to obtain generalized orthogonal reflection mode set
5) Constructing a joint mapping codebook x l ＝s i ·r q 1,2, …, Q.M, wherein s i For power normalized constellation symbols, i ═ 1,2, …, M, satisfying E [ | s i | 2 ]＝1；r q E R is the optimal generalized orthogonal reflection mode after IRS grouping planning, Q is 1,2, … and Q, all reflection modes participate in the mapping, and the method gets rid of the situation that Q must be 2 in the traditional mappingThe nth power constraint, the joint mapping codebook is shown in table 1, where Q is 3 and M is 4. Joint mapping of codebook x in JGD-GQRM l The upper bound of BER of can be expressed as:
wherein the content of the first and second substances,
denotes x m And
the number of erroneous bits of the corresponding binary bit,
the pair-wise error probability of x is expressed,
can be expressed as:
wherein Q (-) represents the right tail function of a standard normal distribution,
representing the distance between two codebooks under known channel conditions, observing equation (21) reveals that the upper bound on BER can be increased
Is used to reduce, i.e. maximize, the minimum inter-codebook euclidean distance.
6) Screening out Q.M combined mapping codebooks based on maximized minimum Euclidean distance
The optimal codebook is transmitted, specifically:
6.1) generating all candidate joint mapping codebook vector sets by using constellation symbols and the screened spatial subsets
The number of codebooks to be rejected is N re ＝Q·M-N c Calculating X all The Euclidean distance between any two codebooks is recorded as
Wherein | · | purple F Represents Frobenius norm, V d Two corresponding codebook indices (i, j) are stored in the empty set X value And X index In (1).
2.2) to X value Sorting the elements in the set from small to large to obtain sorted index value set I, such as X before sorting value ＝[3,5,1]After sorting X value ＝[1,3,5]The sorted index set I ═ 3,1,2]。
2.3) index with the elements in set I index Reordering, e.g. X before ordering value ＝[8,6,4]，X index ＝[(1,2),(1,3),(2,3)]，I＝[3,1,2]After sorting X index ＝[(2,3),(1,2),(1,3)]。
2.4) from sorted X index Intercepting the first half of tuples (i, j) in the set, counting the total frequency of two codebook indexes in each tuple, and sequencing from large to small; and if the number of the elements in the set is an odd number, rounding up the decimal of the intercepted half number.
2.5) advancing codebook index frequency by N re From the codebook X all Removing and recording the rest codebook set as
7) Considering that the transmission path of the transmitting end and the receiving end is blocked by the obstacle, the links of the transmitting end-IRS and the IRS-receiving end are respectively
And
each element thereof
All have zero mean and independent unit variance and obey Gaussian distribution CN (0,1), alpha n And beta k,n Is the amplitude of the channel and is,
and phi k,n Is the channel phase, k is 1,2, …, N r N is 1,2, …, N, generalized orthogonal reflection mode r q Each element in (1) is represented as r i 1, 2. Assuming that the receiving end activates the kth antenna, the snr of the signal received by the antenna can be expressed as:
in order to maximize the signal-to-noise ratio of the kth receiving antenna, the invention adopts a direct phase cancellation mode to optimize the beam forming phase, namely
The IRS phase matrix can be expressed as
8) Receiving a signal assuming that the channel state information is completely known
Can be expressed as:
y＝Gdiag(Θ)diag(r q )Hs i +v (23)
where diag (-) represents a diagonal matrix of elements on the main diagonal,
is additive white Gaussian noise AWGN, which follows the distribution CN (0, N) 0 I Nr ) Wherein, I Nr Represents a unit matrix, N 0 Is the complex noise variance;
9) the receiver recovers the original information bits.
The receiver can recover the original information bits using a maximum likelihood detection method:
wherein, theta k Represents the beamforming phase matrix corresponding to the kth receiving antenna,
and
respectively representing the information bit index corresponding to the joint mapping codebook restored by the ML detection method and the information bit index corresponding to the receiving antenna.
The receiver adopts an SGD detection method to restore the initial information bits, and the method specifically comprises the following steps:
a)Λ＝(Λ out ,Λ in ) Given number of iterations as a continuous greedy detector, Λ out 、Λ in ∈{1,2,…,N r Denotes detection B respectively 1 Number of iterations of bit and detection B 2 Bit bits time new vector
With new channel matrix
Of (c) is calculated. The receive antenna indices are ordered by energy size using a greedy detector:
wherein the content of the first and second substances,
meaning that vector element values are sorted from large to small (or small to large) and their index values are returned,
the indexes sorted for y. For example
b) Selecting
Front Λ out And front Λ in The front antennas are indexed and used respectively
And
and representing the antenna index set and the detection dimension index set as a new receiving antenna index set and a new detection dimension index set.
c) Redefining receiver vectors
i＝1,2,…,Λ out And channel matrix
j＝1,2,…,Λ in SGD detection is:
the complexity of the ML detector in the multiplication operation is according to equation (24):
the complexity of the SSD detector in the multiply operation according to equation (26) is:
specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In order to prove the superiority of the proposed JGD-GQRM scheme, the simulation result of fig. 2 is used to evaluate the BER performance of the modulation scheme, the JGD-GQRM scheme is compared with the existing reflection modulation scheme under an ML detector, and for fair comparison, the total number N of IRS is set to 64, and transmitting antennas N are set t 1, receiving antenna N r Each constellation symbol uses 16-QAM, and the spectral efficiency B is 10bit/s/Hz, and additionally (N) is used g K, Q, B) to represent the parameter configuration of the simulation. In the JGD-GQRM system, the IRS grouping planning parameter is h-4, f (R) opt ) The signal-to-noise ratio (SNR) ranges from-20 dB to 5dB, 0.
As can be seen from fig. 2, the IRS grouping planning scheme is not only applicable to the generalized orthogonal reflection modulation, but also applicable to the generalized spatial reflection modulation, and under the same parameter configuration of the conventional independent mapping scheme, the generalized spatial modulation based on the IRS grouping planning (IRS-GDGSM) and the orthogonal reflection modulation based on the IRS grouping planning (IRS-GDQRM) are respectively improved by about 3dB compared with the IRS-GSM and the IRS-QRM, which is due to BER performance improvement caused by reducing correlation between reflection modes after the IRS grouping planning. On the basis of IRS-GDQRM, JGD-GQRM carries out combined mapping by utilizing a redundant reflection mode existing after IRS planning, which can be improved by 5dB compared with IRS-GDQRM, and the performance difference mainly comes from a modulation method of combined mapping information bits, which is more flexible, and meanwhile, the performance gain brought by total reflection enables JGD-GQRM to be improved by 3dB compared with the existing JRM scheme of combined mapping. It is clear that JGD-GQRM also outperforms existing IRS-SM and IRS-RPM modulation schemes.
Finally, the process is carried out in a closed loop,fig. 3 shows a comparison of the error rate performance of the ML detector and the SGD detector of the JGD-GQRM system. (N) r N, M and B) represent the configuration parameters of simulation, QAM is adopted for constellation symbols, and detailed analysis is carried out on the lambda parameter configuration of different scenes. In N g Among the parameters 8, K, h, 4, and Q, 14, (8,40,16,8) error due to random fluctuation of channel gain under high snr conditions dominates, resulting in erroneous level detection of GD. The conventional approach improves by increasing the number of IRS elements N, but with a limited IRS number, the SGD detector can be improved by increasing Λ out That is, the parameter Λ ═ 2,8, achieves almost the same BER performance as the ML detector and improves the effect of bit-error floor, while the SGD detector complexity is 25% of the ML detector. In N g Among the parameters, Λ ═ 10, K ═ 5, h ═ 6, Q ═ 6, (16,80,4,8), the SGD detector achieves a BER performance very close to the ML detector with a complexity of about 12.5% of the ML detector complexity, and in order to further reduce the detector multiplication dimension, the SGD detector with Λ ═ 2,14 can achieve a BER performance very close to the ML detector, while the number of multiplications calculated is reduced by about one order of magnitude, with a complexity of only 10.9% of the ML detector.
While the present invention has been described in detail with reference to the specific embodiments thereof, the present invention is not limited to the above-described embodiments, and various modifications or alterations can be made by those skilled in the art without departing from the spirit and scope of the claims of the present application.
TABLE 1 Joint IRS Block plan mapping codebook schematic
While the present invention has been described in detail with reference to the specific embodiments thereof, the present invention is not limited to the above-described embodiments, and various modifications or alterations can be made by those skilled in the art without departing from the spirit and scope of the claims of the present application.
Claims (4)
1. A generalized orthogonal reflection modulation method combined with intelligent reflection surface grouping planning mapping is characterized in that the method is based on a single transmitting antenna assisted by N intelligent reflection surface IRS units and N r The method is realized according to a system of receiving antennas, the system adopts M-QAM constellation modulation, and the modulation method comprises the following steps:
1) grouping input bit streams of generalized orthogonal reflection modulation JGD-GQRM mapped by grouping and planning on joint intelligent reflection surface, wherein each group is B bits, and B is B 1 +B 2 ，B 1 ＝log 2 N r Bit bits for selecting N r Root receive antenna index and N r The power of N of 2 must be satisfied,
bit bits for selecting a joint mapping codebook x m Wherein
Q is the number of IRS generalized orthogonal reflection modes, M is the number of M-QAM constellation symbols,
represents rounding down;
2) dividing N reflecting elements of IRS into adjacent N g Groups of N/N g A reflection unit, N can be N g Integer division from N g In the group, K groups of IRS elements are activated to generate in-phase signals, 1 & ltK & ltN g And the rest of N g -K sets for generating orthogonal signals, in common
A subset of space
Wherein r' q From K1 and N g -K j,1 denoting the set of IRS elements for in-phase reflection, j denoting the set of IRS elements reflection phase orderHour hand rotation
Namely, it is
(ii) representing binomial coefficients; generalized orthogonal reflection mode of a system
From a spatial subset r q ' carry out N/N g Share expansion to get, Q ═ 1,2, …, Q;
3) from
A subset of space
Selecting Q space subsets for information transmission; and (3) screening Q space subsets which meet the requirement from all possible space subsets based on the inequalities of the maximum minimum Hamming distance and the minimum activation probability:
first, all possible spatial subsets are obtained by permutation and combination
Then selecting t groups of candidate combinations to be recorded as
Each group of candidate combinations
Require a reaction from R all Select Q t One spatial subset r' and Hamming (r) must be satisfied between any two spatial subsets i ′,r j ') ≧ h, (i ≠ j) where Hamming (· denotes the Hamming distance between two vectors, Q t Is a variable related to t, and h represents the minimum between any two r's between subsets of the IRS spaceHamming distance, h ═ 2,4, …, 2K; in determining Hamming distance threshold h and corresponding candidate combination
Then, obtaining an optimal group of space sets by minimizing the constraint condition of the activation probability inequality and recording the optimal group of space sets as R opt ；
4) To R is opt In each spatial subset to perform N/N g Partial expansion to obtain generalized orthogonal reflection mode set
5) Constructing a joint mapping codebook x l ＝s i ·r q 1,2, …, Q.M, wherein s i For the power normalized constellation symbol, i ═ 1,2, …, M and satisfies the power normalization E [ | s i | 2 ]＝1；r q The element R is an optimal generalized orthogonal reflection mode after IRS grouping planning, and all reflection modes participate in mapping; joint mapping of codebook x in JGD-GQRM l The upper bound of BER is expressed as:
wherein the content of the first and second substances,
denotes x m And
the number of erroneous bits of the corresponding binary bit,
indicating when the source node transmits x m And the sink node decodes as
A pair-wise error probability of;
expressed as:
wherein Q (-) represents the right tail function of a standard normal distribution,
representing the euclidean distance between the two codebooks under known channel conditions;
6) screening out Q.M combined mapping codebooks based on maximized minimum Euclidean distance
Transmitting the optimal codebooks;
7) considering that the transmission path of the transmitting end and the receiving end is blocked by the barrier, the links of the transmitting end-IRS and the IRS-receiving end are respectively
And
each element thereof
All have zero mean and independent unit variance and obey Gaussian distribution CN (0,1), alpha n And beta k,n Is the amplitude of the channel and is,
and phi k,n Is the channel phase, k is 1,2, …, N r N is 1,2, …, N, GuangdongQuadrature reflection mode r q Each element in (1) is denoted as r i 1,2, ·, N; assuming that the receiving end activates the kth antenna, the signal-to-noise ratio of the signal received by the antenna is expressed as:
in order to maximize the signal-to-noise ratio of the kth receiving antenna, a beam forming phase is optimized by adopting a direct phase cancellation mode, namely the phase of the ith reflecting unit
IRS phase matrix is represented as
8) Receiving a signal assuming that the channel state information is completely known
Expressed as:
y＝Gdiag(Θ)diag(r q )Hs i +v (4)
where diag (-) represents the diagonal matrix of elements on the main diagonal,
is additive white Gaussian noise AWGN, which follows the distribution CN (0, N) 0 I Nr ) Wherein, I Nr Representing the identity matrix, N 0 Is the complex noise variance;
9) the receiver recovers the original information bits from the received signal.
2. The generalized orthogonal reflection modulation method combining intelligent reflection surface grouping planning mapping according to claim 1, wherein the step 3) specifically comprises:
3.1) obtaining all of them by permutation and combinationSubset of possible spaces
Randomly generating an index value
And creates an empty set U and an empty set
R is to be all The second ind element
Put in a set U, Q t 1, setting a minimum Hamming distance threshold value h, wherein the minimum Hamming distance threshold value h is used for representing the number of space subsets stored in a set U;
3.2) according to R all Sequentially carrying out Hamming distance judgment on the index values of the middle space subsets and each space subset in the current set U from small to large
j＝1,2,...,Q t If it is, if
If all the space subsets in the current set U meet the Hamming distance requirement, the set U will be used
Into the set U, Q t Adding 1 for recording the number of spatial subsets in the set U;
3.3) will traverse one pass R all Of screening
Is stored in
In step (3.1) to step (b) are repeatedAfter the step 3.2) is carried out t times,
3.4) aggregating
An optimal set of spatial subsets is selected from the t sets of candidate sets by equation (5),
at the minimum, it represents
The spatial subset combination in (3) is optimal, and formula (5) is as follows:
wherein the content of the first and second substances,
to represent
Middle ith space subset, | · | | non-woven phosphor 1 Represents a norm of 1 when
Is shown as
Wherein the probability that each set of IRS reflection modes is used to generate in-phase and quadrature signals is equal;
3.5) grouping the optimal groups
Is denoted by R opt ，
Q＝Q p 。
3. The generalized orthogonal reflection modulation method combining intelligent reflection surface grouping planning mapping according to claim 1, wherein the step 6) specifically comprises:
6.1) generating all candidate joint mapping codebook vector sets by using the constellation symbols and the screened space subsets
The number of codebooks to be eliminated is N re ＝Q·M-N c Calculating X all The Euclidean distance between any two codebooks is recorded as
Wherein | · | charging F Represents Frobenius norm, V d (i,j ) The values of (c) and the index tuples (i, j) of the two corresponding codebooks are respectively stored into an empty set X value And X index The preparation method comprises the following steps of (1) performing;
6.2) to X value Sorting the elements in the set from small to large to obtain a sorting index value set I;
6.3) index with the elements in set I index Reordering;
6.4) from sorted X index Intercepting the first half of tuples (i, j) in the set, counting the total frequency of two codebook indexes in each tuple, and sequencing from large to small; if the number of elements in the set is odd, rounding up the decimal with half number;
6.5) advancing codebook index frequency by N re From one codebook to X all Removing and recording the rest codebook set as
4. The generalized orthogonal reflection modulation method combined with intelligent reflection surface packet-programming mapping according to claim 1, wherein in the step 9), the receiver recovers the initial information bits using a maximum likelihood detection (ML) method or a Sequence Greedy Detection (SGD) method;
the receiver restores the initial information bits by using a maximum likelihood detection method, which specifically comprises the following steps:
wherein, theta k Represents the beamforming phase matrix corresponding to the kth receiving antenna,
and
respectively representing information bit indexes corresponding to the joint mapping codebook restored by the ML detection method and information bit indexes corresponding to the receiving antennas;
the receiver restores the initial information bits by using an SGD detection method, which specifically comprises the following steps:
a)Λ＝(Λ out ,Λ in ) Given number of iterations of the detector, Λ out 、Λ in ∈{1,2,…,N r Denotes detection B respectively 1 Number of iterations and detection of bit B 2 Bit-time new vector
With new channel matrix
Dimension (d); first, the receive antenna indices are sorted by energy size using a greedy detector:
wherein the content of the first and second substances,
representing the ordering of element values from large to small and returning their index values,
indexes sorted for y;
b) selecting
Middle front Λ out And front Λ in The front antennas are indexed and used respectively
And
as a new receive antenna index set and detection dimension index set representation;
c) redefining receiver vectors
And channel matrix
SGD tests show that:
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| CN116016074A (en) * | 2022-12-14 | 2023-04-25 | 东华大学 | Intelligent reflecting surface phase shift design method based on cosine similarity |
| CN116260502A (en) * | 2023-05-15 | 2023-06-13 | 浙江香农通信科技有限公司 | Double-domain index modulation communication method based on reconfigurable intelligent surface |
| CN116318311A (en) * | 2023-05-15 | 2023-06-23 | 浙江香农通信科技有限公司 | Transmission method based on reconfigurable intelligent surface anti-phase index modulation |
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| CN116016074A (en) * | 2022-12-14 | 2023-04-25 | 东华大学 | Intelligent reflecting surface phase shift design method based on cosine similarity |
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| CN116318311A (en) * | 2023-05-15 | 2023-06-23 | 浙江香农通信科技有限公司 | Transmission method based on reconfigurable intelligent surface anti-phase index modulation |
| CN116260502B (en) * | 2023-05-15 | 2023-08-18 | 浙江香农通信科技有限公司 | Double-domain index modulation communication method based on reconfigurable intelligent surface |
| CN116318311B (en) * | 2023-05-15 | 2023-08-22 | 浙江香农通信科技有限公司 | Transmission method based on reconfigurable intelligent surface anti-phase index modulation |
| CN117560048A (en) * | 2024-01-12 | 2024-02-13 | 浙江香农通信科技有限公司 | Multiple access transmission method and device based on reconfigurable intelligent surface |
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