Symbol-level precoding auxiliary cluster index modulation method for millimeter wave communication system

Abstract

The invention discloses a symbol-level precoding auxiliary cluster index modulation method for a millimeter wave communication system. The method comprises the following steps: establishing a relation model among a transmitting signal, inter-cluster interference and a receiving signal according to symbol-level precoding; according to the relation model, constructing a constraint which is far away from a judgment threshold after superposition of a receiving signal of an expected activation cluster and inter-cluster interference; constructing a constraint that the received signal of the unexpected cluster is limited by a threshold value according to the relation model; establishing an optimization problem aiming at maximizing the detection performance according to the expected activation cluster constraint, the unexpected cluster constraint and the transmitting power constraint; solving to obtain a pre-coding matrix, and transmitting a pre-coded signal by a transmitting end; and a receiving end demodulates index information of the activation clusters and information of sending modulation symbols step by step according to the received signals, so that complete information is obtained. According to the scheme, the degree of freedom is higher during precoding design; on the premise of keeping the same transmitting power and complexity level, the transmission reliability and the spectrum efficiency can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically to a symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems. Background Technology

[0002] With the increasing demand for higher data rates and higher spectral efficiency, future wireless communication systems require new technologies and innovative approaches. Millimeter wave (mmWave) communication, with its abundant spectrum resources, high bandwidth, and high data rates, can meet the stringent requirements of 6G communication and is a promising technology for future wireless communication. However, due to the sparse scattering environment, millimeter wave signals suffer from significant path loss. To compensate for the impact of path loss, millimeter wave systems should deploy large-scale antenna arrays and utilize them in practical massive multiple-input multiple-output (mMIMO) communication systems to take advantage of beamforming gain.

[0003] Index modulation (IM) is a promising technique in millimeter-wave communication. It improves spectral efficiency by indexing building blocks, such as antenna arrays, paths, and subcarriers, at the transmitter to transmit additional information bits. Recently, researchers have proposed cluster index modulation (CIM) for millimeter-wave massive MIMO communication systems, which enhances system performance by transmitting additional bits through indexed spatial clusters in sparse millimeter-wave environments. Because clusters have good angular separation, the optimal paths selected from each cluster during index modulation are also separated and approximately orthogonal. Numerous computer simulations have confirmed the superiority of cluster index modulation schemes over traditional millimeter-wave communication. However, as the number of clusters in space increases, inter-cluster interference also intensifies, potentially affecting signal detection at the receiver. Precoding techniques are typically used to optimize signal transmission. However, the complex channels, multipath effects, and other uncertainties in real-world communication environments present traditional precoding methods with a series of challenges, including decreased transmission efficiency and unstable receiver performance.

[0004] To address these issues, researchers have proposed various symbol-level precoding-assisted reception methods in recent years. Existing research has shown that, given known channel state information, introducing symbol-level precoding techniques can effectively combat inter-antenna interference. By designing the precoding matrix, inter-antenna interference can be artificially controlled, ensuring that the signal on the intended receiving antenna, after being superimposed with the interference, moves far from the decision threshold, thus transforming the interference into a beneficial signal. However, existing millimeter-wave cluster index modulation schemes typically employ traditional block-level precoding techniques such as zero-forcing or minimum mean square error, with the core objective of indiscriminately eliminating all interference. While simple, this approach severely limits the design freedom of precoding and fails to utilize the potentially beneficial characteristics of interference, resulting in suboptimal system performance. Summary of the Invention

[0005] To address at least one of the shortcomings of existing technologies, this invention provides a symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems, in order to achieve better communication quality.

[0006] To achieve the objective of this invention, the symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems provided by this invention includes the following steps: A model of the relationship between transmitted signals, inter-cluster interference, and received signals is established based on symbol-level precoding. Based on the relational model, the constraint that the received signal of the expected activated cluster is far from the decision threshold after being superimposed with the inter-cluster interference is constructed, so as to ensure that the interference is beneficial to signal detection. The received signal of the unexpected cluster is constructed based on the relational model and is constrained by the energy threshold to ensure that it will not interfere with the detection of the expected activated cluster at the receiver. An optimization problem is established based on the expected activation cluster constraint, the unexpected activation cluster constraint, and the transmit power constraint, with the goal of maximizing detection performance. The receiving end demodulates the index information of the active cluster and the information of the transmitted modulation symbols step by step based on the received signal.

[0007] This application provides a symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems, specifically considering MIMO communication systems with multiple transmit and receive antennas, and introducing a scenario where multiple clusters are simultaneously activated to transmit signals. In this system, the transmitter and receiver obtain the channel state information (CSI) of each communication link through channel estimation and feedback, and both parties can share their CSI and system parameter information via optical fiber transmission.

[0008] Information transmission methods encompass two forms. One is the use of traditional symbol phase modulation, such as M-order Phase Shift Keying (PSK) modulation and Quadrature Amplitude Modulation (QAM). The other, as described in this application, is information transmission via the index of active clusters, i.e., cluster index modulation. For cluster index modulation at the receiver, given the known CSI, the transmitter performs symbol-level precoding to ensure that only a subset of active clusters can receive the modulated signal. Each cluster corresponds to a specific index, and the transmitter and receiver share the cluster index code table. After receiving the signal, the receiver employs a greedy maximum likelihood detection method, performing a two-stage detection: In the first stage, an amplitude detector is used for energy detection, measuring the received signal power from each cluster, detecting the clusters with the highest power, and decoding some information using the indices of these clusters. In the second stage, a maximum likelihood detector is used to detect the traditional modulation symbols and obtain another portion of the information. This method effectively improves the information transmission efficiency and system performance of millimeter-wave multi-antenna communication systems through the synergistic effect of symbol-level precoding and cluster index modulation, providing strong support for future high-capacity and high-reliability communication systems.

[0009] In the symbol-level precoding-assisted cluster index modulation method proposed in this application, the precoding matrix at the transmitter is carefully designed, and the steps are as follows: First, considering the case of known CSI, a relationship model is established between the transmitted signal, inter-cluster interference, and the received signal of each cluster. The transmitting end divides the information to be transmitted into two parts: one part is modulated in a conventional manner, and the other part is used to select the index of the expected active cluster; the remaining clusters are defined as unexpected clusters.

[0010] For the expected active cluster, a beneficial interference region is constructed based on the symbol-level precoding criterion (through precoding, the interfering signal arriving at the non-target receiver is constructively superimposed with the desired signal at the target receiver, thereby enhancing signal quality or expanding the decision region) and the modulation symbol constellation point type. The beneficial interference region refers to a special geometric region constructed in the receiver constellation diagram. When the signal and interference are superimposed in this region, it not only does not degrade detection performance but also enhances the noise immunity of the received signal. Within this region, the superposition of the expected signal and the interfering signal results in a larger actual received signal power, further away from the decision threshold, thus providing stronger anti-interference capability and achieving performance gain. The specific implementation is as follows... Figure 2 As shown, point A corresponds to a standard M-PSK constellation point, and its corresponding sector represents the beneficial interference region. Vector Represents the target signal, where Represents the signal amplitude after passing through a flat fading channel; vector Represents interference signal, vector This is the actual received signal superimposed from both. For example... Figure 2 When the conditions are met At that time, the actual received signal will fall within the beneficial interference area, thereby achieving performance gain.

[0011] For unexpected clusters, traditional methods typically design them with zero signal received power, i.e., no signal reception, to avoid adversely affecting the energy detection in the first stage at the receiver. However, the energy detection in the first stage at the receiver distinguishes between expected and unexpected clusters based on the magnitude of the received signal power. Zero power constraints are not necessary and may even limit the freedom of precoding design, affecting system performance. In the method proposed in this application, the signal on unexpected clusters is constrained within a certain range, such as... Figure 2 As shown, it is restricted to a radius of Inside the central circle.

[0012] Based on the established power constraints for expected and unexpected clusters, and combined with the actual system transmit power limitations, this invention constructs an optimization problem aimed at maximizing the energy difference between expected and unexpected clusters. This optimization problem aims to enhance the receiver's ability to identify target clusters and reduce false detection probability by improving the distinction between useful signals and interference noise. Mathematically, this optimization problem can be transformed into a convex optimization problem with linear and quadratic constraints. Specifically, by appropriately transforming constraints such as signal power and interference threshold, the optimization problem can be formalized into a standard second-order cone programming (SOCP) form. This type of problem has a good mathematical structure and theoretical properties, making it suitable for efficient numerical solutions. Benefiting from its convex optimization characteristics, this problem can be directly solved using existing efficient mathematical solvers (such as CVX and MOSEK), obtaining the globally optimal precoding matrix within a finite number of iterations. This not only ensures the theoretical reliability of the algorithm but also significantly improves the practicality and engineering feasibility of precoding design, making it very suitable for millimeter-wave communication scenarios with high real-time requirements.

[0013] Compared with the prior art, the present invention has the following advantages and significant effects: In processing the expected active clusters, this scheme uses symbol-level precoding technology to transform interference traditionally considered harmful into beneficial signals, effectively improving the overall system performance without increasing transmit power. By constructing beneficial interference regions, the signals on the expected clusters can maintain a high received signal-to-noise ratio even under interference superposition, significantly enhancing demodulation reliability. This strategy not only optimizes power utilization efficiency but also provides a new technical path for improving the performance of millimeter-wave multi-antenna systems.

[0014] Compared to existing methods, this scheme breaks through the strict zero-power constraint on unexpected cluster signals in the precoding design, instead employing a flexible threshold-controllable constraint mechanism, significantly expanding the feasible solution space of the precoding matrix. This increased design freedom allows the system to better adapt to the rapid changes and uncertainties in millimeter-wave channels, enhancing its robustness in different communication scenarios. Simultaneously, it provides more possibilities for the coordinated optimization of system parameters, helping to fully realize the potential performance of millimeter-wave multi-antenna systems.

[0015] This invention improves system performance without introducing significant implementation complexity, demonstrating good engineering feasibility and application prospects. The proposed precoding framework has a clear structure, is easy to integrate with existing communication systems, and provides strong support for the practical development of millimeter-wave communication technology.

[0016] In summary, this invention demonstrates significant advantages in both performance optimization and design flexibility. It not only provides an efficient and reliable solution for millimeter-wave cluster index modulation systems but also points to a new direction for the development of precoding technology in future wireless communication systems. Attached Figure Description

[0017] Figure 1 A flowchart of a symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems is provided in this application embodiment; Figure 2 A schematic diagram of the beneficial interference region for M-PSK signals; Figure 3 A schematic diagram of the beneficial interference region for 16-QAM signals; Figure 4 A schematic diagram of an implementation model provided in this application; Figure 5 The figure shows the MATLAB simulation results of an embodiment of this application. Detailed Implementation

[0018] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0019] Please refer to Figure 4 This invention provides a millimeter-wave multi-antenna cluster index modulation communication system supporting multi-cluster activation. The system is equipped with [equipment / devices] at both the transmitting and receiving ends. root antenna and A series of antennas form a large-scale MIMO transmission architecture. The transmitter can accurately obtain channel state information and design a symbol-level precoding matrix based on this to precisely control the interference distribution between different clusters and optimize the received signal quality. The receiver knows all possible cluster index combinations from the transmitter and can transmit additional information bits by detecting the index of the activated cluster, effectively improving spectral efficiency.

[0020] Under this architecture, embodiments of the present invention significantly improve the design freedom of the precoding matrix by relaxing the strict zero-interference constraint in traditional precoding design and instead adopting a threshold-based interference management mechanism. This improvement enables the system to further optimize the signal energy gap between expected and unexpected clusters while maintaining the existing transmit power and complexity, thereby comprehensively improving the system's reliability and transmission efficiency.

[0021] The following is combined Figure 2 The following details the process steps for implementing this invention: Step 1: Set system parameters and channel state information, and establish a relationship model between transmitted signals, inter-cluster interference and received signals based on symbol-level precoding.

[0022] Assuming there is in the communication environment Each cluster comprises multiple paths whose arrival angles (AoA) or departure angles (AoD) are uniformly distributed within a predefined interval. This embodiment of the invention assumes that these clusters have non-overlapping angular coverage and are therefore sufficiently separated from each other. Assuming the system is activated... ( Transmission is performed by clusters, i.e., through a channel. A data symbol, defined as , To send the symbol vector, For the first Data symbols on a cluster, superscript This represents transpose. Then, sending a complete symbol requires [number of bits]. ,in Cluster index bits: Then a total of Cluster index combinations; for Meta-modulated data bits: The Saleh–Valenzuela (SV) model is used to characterize millimeter-wave non-line-of-sight channels in indoor environments. Channel matrix. Represented as:

[0023] in, Indicates the first The th cluster The gain of each path follows distributed; It is the first The number of available paths in each cluster; and These are the responses of the receiving and transmitting antenna arrays, respectively. and They are the first The th cluster The azimuth arrival angle and azimuth departure angle corresponding to each path, superscript Indicates conjugate transpose; The number of antennas equipped for the transmitting end. The number of antennas provided for the receiving end.

[0024] Considering that both the transmitter and receiver are equipped with uniform linear arrays, the array response... and They are defined as follows: , . in, , ,in and These are the distances between the transmitting and receiving antenna elements, respectively. This is the signal wavelength. The spacing between antenna elements is half a wavelength, i.e. The received signal vector after passing through the analog synthesizer, i.e., the established relational model, is as follows: , in, For symbol-level precoding matrices, Is with the first Pre-encoded vectors associated with each index cluster Is with the first Precoded vectors associated with each index cluster; For the simulated beamforming vectors containing all clusters, Cluster Beamforming vector; For the simulated composite vector containing all clusters, Cluster The simulated composite vector; It has a variance of The noise vector of a circularly symmetric complex Gaussian distribution, i.e. .

[0025] ,in It is after the analog synthesizer from the first The signals received on an index cluster can be represented as follows:

[0026] It represents the complex field, which is the set of all complex numbers. It is an abbreviation for Circularly Symmetric Complex Gaussian Distribution, which is the most core and commonly used probability distribution in wireless communication channel modeling.

[0027] Step 2: Construct a constraint based on the relational model that the received signal of the expected active cluster is superimposed with the inter-cluster interference and is far from the decision threshold, so as to ensure that the interference is beneficial to signal detection.

[0028] The decision threshold is a decision boundary used by the receiver to demodulate the received signal. For example, as can be seen from the constellation diagram of QPSK, its decision threshold is two coordinate axes (real axis and imaginary axis).

[0029] In one embodiment, QPSK modulation is employed, from Figure 2 It can be seen that as long as the actual received signal falls within the beneficial interference area, that is, when This ensures that the interference is beneficial. Therefore, the constraint for constructing the beneficial interference region is:

[0030]

[0031]

[0032] in, This represents the angle between the original signal and the interference signal of the expected cluster; and These represent the real and imaginary parts of the function, respectively. represent Figure 2 The original signal in The digit is a real number, representing the amplitude of the original signal. Represents the modulated signal; The complex number represents the amplitude and phase changes from the original signal to the final received signal. This represents the actual received signal; It represents the order of the modulation symbol.

[0033] Step 3: Construct the received signal of the unexpected cluster based on the relational model, which is constrained by the energy threshold.

[0034] Unlike existing methods that constrain zero signals for unexpected clusters, this invention constrains the received signals of unexpected clusters within a central circle, where the energy threshold of the received signals of the unexpected clusters is the radius of this central circle. It is also an optimization parameter: , in, Representing the Simulated composite vectors of several unexpected clusters, Representative and the Pre-encoded vectors associated with unexpected clusters Represents the set of all cluster indexes. The first one selected by the transmitter A number of expected cluster index combinations and , Represents clustered index combinations (from) Cluster selection The number of combinations formed by individual clusters, ,so A set of indexes representing all unexpected clusters.

[0035] Step 4: Based on the expected activation cluster constraints, unexpected activation cluster constraints, and transmit power constraints, establish an optimization problem with the goal of maximizing detection performance.

[0036] The transmission power of this invention embodiment is limited, that is... ,in Represents the second norm, Represents the analog beamforming vector. Represents the symbol-level precoding matrix. Indicates the transmitted symbol vector. This represents the transmit power. Since the receiver distinguishes between expected and unexpected clusters based on energy, the objective function of the optimization problem can be set as maximizing the difference between the received signal energy (amplitude) of the expected cluster and the maximum received signal energy of the unexpected cluster:

[0037] st , , , , , . in, The first one selected by the transmitter One expected cluster index combination, Represents the first in the current cluster index combination Cluster-related pre-coded vectors Represents the first in the current cluster index combination Simulated composite vectors of clusters, This represents the amplitude of the original signal; It is a complex number, representing the amplitude and phase changes from the original signal to the final actual received signal.

[0038] Step 5: Solve the optimization problem to obtain the precoding matrix. Energy threshold of unexpected cluster received signals Send symbol vector After pre-encoder (multiplied by matrix) The pre-coded signal is obtained and then transmitted to the wireless channel through the radio frequency front-end and antenna array.

[0039] Mathematically, the optimization problem can be transformed into a convex optimization problem with linear and quadratic constraints, which can be normalized to a standard second-order cone programming form (this transformation and normalization are known and readily available, and will not be elaborated upon here). Benefiting from its convex optimization characteristics, the optimization problem can be solved directly using existing efficient mathematical solvers (such as CVX, MOSEK, etc.), and the globally optimal precoding matrix can be obtained within a finite number of iterations. and the energy threshold of the optimal unexpected cluster received signal .

[0040] Step 6: The receiving end demodulates the index information of the active clusters and the information of the transmitted modulation symbols step by step based on the received signal. The complete information is stored in the cluster index and modulation symbols, respectively.

[0041] After receiving the signal, the receiver uses a greedy maximum likelihood detection method to perform two-stage detection.

[0042] In one embodiment, a greedy maximum likelihood detection method is used, and demodulation is divided into two steps:

[0043] in , Representing the One expected cluster index combination, This represents the received signal vector on the cluster corresponding to the index combination; an index combination contains There are index values, so Represents the first in the index combination n One index value, Represents the first norm, An index representing the combination of cluster indexes obtained from demodulation. This represents the data symbols obtained from demodulation. Representing all possible modulation symbols, This indicates that a symbol vector is accepted.

[0044] Formula (1) represents energy detection. The receiver detects the index of the active cluster based on the energy level of the received signal, and then demodulates the corresponding information through the index code table. Formula (2) is traditional signal demodulation. The received signal on the cluster detected by Formula (1) is demodulated to obtain the remaining information and complete the information transmission.

[0045] The method of this invention is also applicable to transmitting QAM modulation symbols; in one embodiment, 16-QAM is used as an example. Figure 3 As shown, under 16-QAM, constellation points can be divided into three types, each corresponding to three different beneficial interference regions: The first type is the constellation points closest to the origin (marked in red). These constellation points (marked as...) The symbol is surrounded by its decision boundary, meaning that any disturbance will negatively impact symbol detection. Therefore, there is no disturbance region. Based on this, we obtain the following expression:

[0046] Indicates sending a signal. It indicates that it is actually part of the department. Indicates the first The first cluster index combination in the nth cluster index combination Clusters, Representing the The first cluster index combination in the nth cluster index combination Received signals on each cluster It represents the actual department. This represents its virtual part.

[0047] The second type is constellation points (marked in blue) located at a moderate distance in the constellation chart. These constellation points (denoted as...) The decision boundary along the real axis (defined as...) ) or imaginary axis (defined as Furthermore, beneficial interference only occurs when the interference pushes the received signal perpendicularly away from the coordinate axis. Therefore, the beneficial interference region is ray-shaped. Based on this, the following expression is obtained:

[0048] The third type is the constellation point (marked in green) farthest from the origin in the constellation chart. Similar to QPSK, these constellation points (denoted as...) The decision boundary of the region is defined by two coordinate axes, therefore the beneficial interference region is a sector. Based on this, the following expression is obtained:

[0049] Therefore, similar to QPSK, in 16-QAM, the energy threshold of the received signal from the unexpected cluster is solved. and symbol-level precoding matrix The optimization problems can be represented as follows:

[0050] st , , (3)-(5). Among them, (3)-(5) contain the above three types of beneficial interference construction region constraints, and the corresponding expression needs to be selected according to the constellation point type to which the current symbol belongs. Note that the modulation symbols in the embodiments of the present invention can be extended to higher-order QAM symbols, such as 64-QAM, and the constellation points are also divided into three types, each type corresponding to three different beneficial interference regions. The first type is the constellation point located in the outer layer of the constellation diagram, and its constraint condition is the same as (3); the second type is the constellation point located in the outer layer of the constellation diagram, and its constraint condition (4) is the same; the third type is the four constellation points located in the outer corner of the constellation diagram, and its constraint condition (5) is the same.

[0051] The optimization problem in this embodiment is also a convex optimization problem, which can be solved directly by calling existing efficient mathematical solvers (such as CVX, MOSEK, etc.). The other steps are the same as in the previous embodiment.

[0052] In the above embodiments, the performance of the embodiments is as follows, based on simulation experiments. Figure 5 As shown, regardless of whether QPSK or 16-QAM is used, symbol-level precoding achieves superior bit error rate performance compared to cluster index modulation systems using traditional zero-forcing precoding. This invention can adapt to different types of modulation symbols without changing the network structure, thus having better practical applications.

[0053] Compared with existing millimeter-wave cluster index modulation schemes, this scheme adopts a flexible power constraint strategy, which allows for greater freedom in precoding design. While maintaining the same transmit power and complexity level, this scheme effectively improves transmission reliability and spectral efficiency, thereby achieving better overall communication performance, which is of great significance to improving the communication quality of millimeter-wave systems.

[0054] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined in this invention may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems, characterized in that, Includes the following steps: A model of the relationship between transmitted signals, inter-cluster interference, and received signals is established based on symbol-level precoding. Based on the relational model, the constraint is constructed that the received signal of the expected activated cluster is far from the decision threshold after being superimposed with the inter-cluster interference; The received signal of the unexpected cluster constructed according to the relational model is constrained by the energy threshold. An optimization problem is established based on the expected activation cluster constraint, the unexpected activation cluster constraint, and the transmit power constraint, with the goal of maximizing detection performance. The precoding matrix is ​​obtained by solving the optimization problem, and the transmitter sends the precoded signal. The receiving end demodulates the index information of the active cluster and the information of the transmitted modulation symbols step by step based on the received signal.

2. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, relational model Represented as: In the formula, For the simulated composite vector containing all clusters, the superscript... This indicates the conjugate transpose. For the channel matrix, For the simulated beamforming vector that includes all clusters, For symbol-level precoding matrices, To send the symbol vector, It is a noise vector.

3. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, The received signal of the unexpected cluster constructed according to the relational model is constrained by an energy threshold. The received signal of the unexpected cluster is constrained within a central circle, and the energy threshold of the received signal of the unexpected cluster is the radius of this central circle. The constraint is expressed as follows: ， in, Representing the Simulated composite vectors of several unexpected clusters, with superscripts This indicates the conjugate transpose. For the channel matrix, For the simulated beamforming vector that includes all clusters, Representative and the Pre-encoded vectors associated with unexpected clusters Represents the set of all cluster indexes. The first one selected by the transmitter One expected cluster index combination, and , This indicates the number of cluster index combinations, where a cluster index combination is... Cluster selection Formed by clusters, A set of indexes representing all unexpected clusters. The energy threshold for signals received by unexpected clusters.

4. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, In the constraint that the received signal of the expected active cluster, after being superimposed with inter-cluster interference, is far from the decision threshold according to the relational model, QPSK modulation is used, and the constraint of the constructed beneficial interference region is as follows: In the formula, This represents the angle between the original signal and the interference signal of the expected cluster. and These represent the real and imaginary parts of the function, respectively. The amplitude of the original signal. Represents the modulated signal; This represents the amplitude and phase changes from the original signal to the final received signal. Indicates the order of the modulation symbol.

5. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, In the constraint that the received signal of the expected activated cluster is far from the decision threshold after being superimposed with inter-cluster interference according to the relational model, QAM adjustment is used to construct the constraint of the beneficial interference region as follows: In the formula, and These represent the real and imaginary parts of the function, respectively. Representing the The first cluster index combination in the nth cluster index combination Received signals on each cluster , This indicates the number of cluster index combinations, where a cluster index combination is... Cluster selection Formed by clusters, It represents the real part. This represents the virtual part. Represents the first norm, An index representing the cluster index combination obtained from demodulation. The amplitude of the original signal. This represents the amplitude and phase changes from the original signal to the final received signal. Represents the modulated signal. It is the constellation point closest to the origin in the constellation chart. For constellation points located at medium distances in the constellation diagram, the decision boundary is defined along the real axis. The decision boundary along the imaginary axis represents constellation points at medium distances in the constellation diagram. The constellation point furthest from the origin in a constellation chart.

6. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, The transmit power must satisfy the following constraints: In the formula, Represents the analog beamforming vector. Represents the symbol-level precoding matrix. Indicates the transmitted symbol vector. Represents transmission power. Represents the second norm, The energy threshold for signals received by unexpected clusters.

7. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, The objective function of the optimization problem is set as maximizing the difference between the received signal energy of the expected cluster and the maximum received signal energy of the unexpected cluster, expressed as: In the formula, Represents the modulated signal. This represents the amplitude and phase changes from the original signal to the final received signal. For symbol-level precoding matrices, The energy threshold for signals received by unexpected clusters.

8. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 1, characterized in that, After transforming the optimization problem into a convex optimization problem with linear and quadratic constraints, the mathematical solver is called to solve it.

9. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to any one of claims 1-8, characterized in that, After receiving the signal, the receiver uses a greedy maximum likelihood detection method to perform two-stage detection.

10. The symbol-level precoding-assisted cluster index modulation method for millimeter-wave communication systems according to claim 9, characterized in that, The greedy maximum likelihood detection method involves two steps in demodulation: in , Representing the One expected cluster index combination, This represents the received signal on the cluster corresponding to the index combination; Represents the first in the index combination n One index value, Represents the first norm, An index representing the cluster index combination obtained from demodulation. This represents the data symbols obtained from demodulation.

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