CN112152766B - Pilot frequency distribution method - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0058—Allocation criteria
- H04L5/006—Quality of the received signal, e.g. BER, SNR, water filling
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
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- H04L5/0064—Rate requirement of the data, e.g. scalable bandwidth, data priority
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Abstract
The invention discloses a pilot frequency distribution method, which divides the cell service priority into four priorities of A, B, C and D, different service priorities are distributed to different pilot frequency sets, the higher the orthogonality of the pilot frequency sets distributed by the cell is, the lower the probability of pilot frequency multiplexing between users in the cell and other cell users is. In order to measure the influence of pilot multiplexing on a system when a single user generates pilot multiplexing, pilot pollution strength is introduced. After the pilot frequency set is distributed, the pilot frequency pollution intensity of each cell user is calculated again, and the pilot frequency is redistributed to the users with larger pilot frequency pollution intensity. The invention introduces the channel estimation technology based on the pilot frequency in the pilot frequency distribution, and the technology can accurately estimate the current channel state so as to judge whether the cell users are polluted by the pilot frequency. By applying the scheme provided by the embodiment of the invention, the actual requirements of each cell can be considered, the average reachable rate of a Massive MIMO system user is improved, and the pilot pollution is reduced to a greater extent.
Description
Technical Field
The invention relates to a wireless communication technology, in particular to a pilot frequency distribution method suitable for a Massive MIMO system.
Background
Massive MIMO, as a key technology of 5G, will play a crucial role in the development of 5G. Massive MIMO, also known as large-scale antenna system, has as few as tens, as many as hundreds, or even thousands of base station antennas, and has advantages over conventional MIMO. However, due to the limitation of pilot resources, there must be pilot multiplexing between users, which results in that the base station cannot correctly identify the pilot from multiple cells and multiple users, and thus cannot perform accurate channel estimation on the uplink channel, i.e. a pilot pollution phenomenon is generated, which seriously hinders the normal transmission of user signals, and when the number of users is more, the pilot pollution phenomenon is more serious. Therefore, the pilot pollution phenomenon becomes a bottleneck for further development of Massive MIMO.
The conventional pilot pollution suppression methods are many and roughly divided into two categories: one is based on a channel estimation method; one is a resource allocation based approach.
The pilot pollution suppression method based on channel estimation is mainly classified into a channel estimation method requiring a pilot sequence and a channel estimation method not requiring a pilot sequence. The pilot-based channel estimation method refers to that a user sends a pilot sequence to a base station, and the base station performs channel estimation by adopting a related detection algorithm after receiving the pilot sequence, so as to obtain uplink channel state information, wherein the common pilot-based channel estimation methods include four methods, namely a Maximum Likelihood (ML) estimation algorithm, a Least Square (LS) channel estimation algorithm, a Minimum Mean Square Error (MMSE) channel estimation algorithm and a Compressed Sensing (CS) channel estimation algorithm; the channel estimation method without the pilot sequence is not limited by the number of orthogonal pilots, greatly improves the spectrum efficiency, has the advantages of small load and the like, but extracts the statistical characteristics by needing a large number of received signals, and has overhigh operation complexity.
The pilot frequency pollution suppression method based on resource allocation mainly redesigns a pilot frequency structure on a time domain or a frequency domain, selects a pilot frequency sending mode and optimizes a pilot frequency allocation scheme, thereby reducing the pilot frequency pollution. This method can be subdivided into the following: time-shifted pilot, pilot allocation, pilot power control, and the like.
The core idea of the time-shifting pilot frequency is to set a specific transmission mechanism, stagger the pilot frequency sending time without users, suppress the pilot frequency pollution by destroying the 'simultaneity' generated by the pilot frequency pollution, divide a coherent time into two stages, perform uplink pilot frequency transmission in a certain group of cells, perform downlink channel transmission in other groups of cells, and rotate in turn until all the cells send the pilot frequency, thereby reducing the pilot frequency pollution.
The pilot frequency allocation is based on various factors such as user position, user power, channel second-order statistical information, large-scale fading factors and the like, a special pilot frequency allocation scheme is set, different optimization targets are determined according to different influence factors, and optimization effects can be quantitatively expressed by related indexes, such as channel mean square error and reachable sum rate, so that pilot frequency pollution is reduced.
The core idea of pilot power control is to set a pilot control scheme, where the pilot transmission power of each user is generally equal, but some users need to increase or decrease the pilot transmission power in a proper amount due to different requirements of different users and the influence of different factors, so that the pilot power transmission value of some users is dynamically changed by setting the pilot power control scheme, which can also reduce pilot pollution and improve the overall performance of the system.
The traditional pilot pollution mitigation algorithms do not consider the traffic information, but in practice, the traffic is different and the demand is different. For example, telephone service requires a small delay, while mail service requires a low fault tolerance, and thus, the requirements of each cell are different.
In order to overcome the defects well, a pilot frequency allocation algorithm based on user service priority is provided, a multi-cell multi-user scene model is established, four pilot frequency sets with different spans are designed, different pilot frequency sets are allocated according to different user service priorities, in order to better balance whether a current user is polluted by the pilot frequency, an LS channel estimation algorithm is introduced to estimate a channel, the concept of pilot frequency pollution intensity is introduced, whether the current user is more easily influenced by the pilot frequency pollution is measured, special pilot frequency is allocated, the actual requirement of each cell user is considered, the pilot frequency pollution is effectively reduced, and the comprehensive performance of the system is improved.
Disclosure of Invention
The invention provides a pilot frequency distribution method based on user service priority, which takes different service requirements of different users into consideration, classifies the services according to priority, and the services with different priorities can distribute pilot frequency sets with different orthogonality, introduces pilot frequency pollution intensity, and distributes special pilot frequency again for a single user distributed with a pilot frequency set cell if the pilot frequency pollution intensity is too large. The specific technical scheme is as follows:
in order to reduce pilot pollution, the embodiment of the invention adopts two steps: the allocation of the pilot frequency set and the pilot frequency reallocation of the special users, the allocation of the pilot frequency set is specific to a cell, and the pilot frequency reallocation is specific to a single user (which must be located in the cell to which the pilot frequency set is allocated), thereby ensuring that the comprehensive performance of the system is improved and the pilot frequency pollution is reduced. Here, further, by adopting a modularized concept, the whole system is divided into four parts:
(1) and the transmitting module is mainly used for generating and modulating signals.
(2) The scene module is relatively complex and comprises four small modules, namely a cell scene design module, an orthogonal pilot frequency design module, a channel estimation module and a pilot frequency distribution module, wherein the pilot frequency distribution module comprises four parts, namely cell service grade division, pilot frequency set design, pilot frequency pollution intensity calculation and special user pilot frequency distribution, and the core is the design of the pilot frequency distribution module.
(3) And the receiving module is mainly used for receiving and demodulating signals.
(4) And the calculation module is mainly divided into two parts, namely, the calculation of the channel mean square error and the calculation of the system reachable sum rate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a modularized scenario provided by an embodiment of the present invention, where different modules perform different functions.
Fig. 2 is a multi-cell multi-user scenario provided by an embodiment of the present invention.
Fig. 3 is a flowchart of a pilot allocation algorithm according to an embodiment of the present invention, which completes the allocation of pilots.
Detailed Description
In order to make the technical solution of the present invention clearer, the following first describes in detail a pilot allocation method based on user service priority according to the present invention with reference to the accompanying drawings and specific embodiments.
The novel pilot frequency allocation algorithm provided by the embodiment of the invention is mainly applied to a Massive MIMO system and can be further expanded to wireless communication.
Referring to fig. 1, a pilot allocation method provided in the embodiment of the present invention may include the following steps:
step 001: and generating and modulating a signal, modulating the 01 sequence by adopting a proper modulation mode, and transmitting the signal through an antenna.
Step 002: the embodiment of the invention completes the establishment of the scene through four parts.
And step 003, receiving and demodulating the signal, wherein the receiving module is mainly responsible for receiving and demodulating the signal (corresponding to the 4QAM modulation of the transmitting module).
Step 004, evaluating system performance, in the embodiment of the invention, the mean square error is used as a judgment basis for judging whether a single user is polluted by pilot frequency, and the reachable rate is used as a measurement index of the overall system performance. The channel estimation accuracy is usually expressed by mean square error (MMSE), and the smaller the mean square error is, the higher the channel estimation accuracy is, and the lighter the pilot pollution is. The sum rate refers to the maximum bit number which can be transmitted on a unit bandwidth channel in unit time, the unit is bit/s/Hz, the larger the sum rate is, the smaller the pilot frequency pollution degree is, and the effect of different pilot frequency allocation is reflected by comparing the size of the sum rate.
Step 002 is the core, and the embodiment of the present invention completes the establishment of the scene through four parts.
The first step is to establish a multi-cell multi-user scenario, wherein the core of the multi-cell multi-user scenario lies in the establishment of a channel model and the setting of corresponding parameters of a cell.
In order to accurately represent the cell channel model, the embodiment of the invention analyzes the channel model in detail.
A Massive MIMO channel belongs to a wireless channel, where fading in the wireless channel can be divided into large-scale fading and small-scale fading: large-scale fading refers to a fading phenomenon caused when a mobile station moves in a longer distance range, and is slow fading, the fading can be divided into path loss and shadow fading, the size of the path loss mainly depends on the channel characteristics and the transmission distance between a transmitting end and a receiving end, and the size of the shadow fading depends on the attributes of obstacles (buildings, plants and intermediate terrains) between the transmitting end and the receiving end; small-scale fading refers to signal fluctuation caused by superposition of signals on a receiving end through different paths when a mobile station moves in a short-distance range, and can be increased, reduced or unchanged, and is generally used for describing instantaneous characteristics of the signalsthIf B is smaller than BthFrequency selective fading, otherwise flatType fading. The time-varying fading is divided into slow fading and fast fading, which depend on the transmission symbol period T and the coherence time T of the channelthIf T is less than TthSlow fading is the case, otherwise fast fading is the case. According to the embodiment of the invention, a lognormal shadow fading model is adopted for large-scale fading, and a Rayleigh distribution model is adopted for small-scale fading.
On the basis of a traditional free space propagation model, a lognormal shadow fading model introduces a path loss exponent n, and simultaneously introduces a Gaussian random variable gamma with a mean value of 0 and a variance of sigma to adapt to a more real environment, namely, the lognormal shadow fading model meets the following requirements:
PL(r)＝PLF(r0)+10n log(r/r0)+Γ (1)
wherein P (r) represents the power of the receiving end, P (r)0) Representing reference point power, usually the transmitting end power, r0Denotes the reference distance, different environment, r0And n is a path loss exponent, the formula (1) leads to different path losses of the receiving end under the same distance r by introducing a random variable Γ, and can control the fluctuation size of the random variable Γ through a variance σ, the path loss can change along with the change of the random shading variable Γ, and the model is suitable for a more real environment. The larger the variance σ, the larger the variation width of the path loss, and in the embodiment of the present invention, the variance σ may take the most appropriate value according to the worst of the actual environment.
The Rayleigh distribution model refers to a distribution form of a signal envelope value of a receiving end, wherein the signal reaches the receiving end through multipath propagation, a direct path does not exist in the transmission process, and the probability density function of the distribution form satisfies the following conditions:
wherein, r and sigma respectively represent the envelope amplitude and the root mean square of the received signal, when r is more than or equal to 0, the probability density function obeys Rayleigh distribution, when r is less than 0, the probability density function is zero.
On the basis of the two channel models, the embodiment of the invention further designs a multi-cell and multi-user scene, which is shown in fig. 2.
The number of the cells is L, the base station is positioned in the center of each regular hexagon cell, the number of the antennas of the base station is M, and the number of the users of each cell is K. Each cell comprises 1 base station (M antennas) and K users (single antenna), and the system works in TDD mode.
Wherein, the channel model from the user k of the cell j to the cell i base station is as follows:
hj,k,ia small scale fading matrix of N x K is represented, each element of the matrix obeying an independent uncorrelated standard normal distribution. Beta is aj,k,iRepresents a large-scale fading factor as shown in equation (4).
Wherein r isj,k,iRefers to the path loss, i.e. the distance value from user k of cell j to base station of cell i, where α is the path loss fading coefficient, zj,k,iIs a shadow fade.
The embodiment of the invention designs a pilot frequency set
S is composed of p pilot sequences, each of which has a length τ such that it satisfies formula (5).
Wherein, i, k is not more than p, the pilot symbol received by the ith base station is:
the information symbol received by the ith base station is:
wherein p isrFor uplink pilot transmission power, NiEach element n ofiAll obey a standard normal distribution. p is a radical ofuFor the transmission power of the uplink information symbols, xj,kAnd the uplink transmission information symbol of the user k of the cell j is shown.
The parameter design of the cell mainly comprises the number of the cells, the number of users and distribution positions of the cells, the number of base station antennas, the radius of the cells, path loss factors, shadow fading variances and the like, and the parameters can be set according to actual conditions as long as the parameters are within a reasonable range. Usually, the path loss factor is mainly dependent on the propagation environment, the variation range is 2-6, and the larger the path loss factor is, the more complicated the environment is represented. The cell radius is usually between 500-2000m, even if the number of base station antennas is small, the number is hundreds.
And secondly, designing orthogonal pilot frequency, wherein in order to ensure that the pilot frequency in each pilot frequency set is orthogonal to each other, the embodiment of the invention adopts a Walsh function and a Hadamard matrix to realize the design of the orthogonal pilot frequency.
The walsh function is a subset of a set of walsh functions, which is a set of orthogonal functions but different from the set of orthogonal functions consisting of sine and cosine functions, which is composed of walsh functions (walsh sequences) whose amplitudes are binary +1 and-1, and has completeness. The set of walsh functions of order N generally includes N walsh functions, which can be expressed as:
{Wj(t)；t∈(0,T),j＝0,1,...,N-1} (8)
Wj(T) takes values in the set { +1, -1} and within the interval {0, T }, WjThe value of index j is consistent with the change of amplitude and is different from Wj(t) are orthogonal and embodiments of the present invention utilize Hadamard matrices to generate walsh sequences.
The Hadamard matrix is an orthogonal matrixThat is, each row (column) is orthogonal to the other, and the square of the 2-norm of each row (column) is the same as its order, and if A is an n-th-order square matrix consisting of +1 and-1, if AA is satisfiedT＝nInThen a is an nth order Hadamard matrix and the lowest order Hadamard matrix is second order and can be expressed as:
the higher order Hadamard matrix is shown in equation (10).
Wherein N is 2mFor example, a 4 th walsh sequence can be represented by a Hadamard matrix as:
it can be seen that row 1 of the matrix has undergone 0 change, denoted as W0(t) the 2 nd row of the matrix has undergone 3 changes, denoted W3(t) 1 change, denoted W, in row 3 of the matrix1(t) the 4 th row of the matrix has changed 2 times and is denoted as W2(t) of (d). Each row (or column) of the Hadamard matrix is actually a walsh sequence, but the row (or column) number is associated with WjThe subscript j of (t) is inconsistent.
In the embodiment of the invention, a 32-order Hadamard matrix is used for generating a Walsh sequence with the length of 32, each Walsh sequence is modulated by 4QAM and then is changed into a complex sequence with the length of 16, and the orthogonality cannot be changed through normalization processing, so that orthogonal pilot frequency is generated and is used as the internal pilot frequency of a pilot frequency set.
And thirdly, channel estimation is carried out to judge whether the cell user is polluted by the pilot frequency, the embodiment of the invention adopts the following mode as the basis for judging whether the cell user channel is polluted by the pilot frequency, and the specific analysis is as follows.
The number of users in each cell is K, the number of antennas configured in the base station is M, and the pilot frequency P belongs to CK×τWith a transmission power of
The equivalent channel matrix (Rayleigh fading matrix combined with large-scale fading factor) is H' epsilon CM×KThe channel noise is N ∈ CM×τAnd the signal of the receiving end is Y, which satisfies the following conditions:
Y＝H'P+N (12)
for channel estimation matrices
Expressing, constructing a cost function:
determining the minimum value of equation (13) in relation to
The partial derivative of (d) is equal to zero, one obtains:
can obtain
The solution of the channel estimate is then:
assuming perfect orthogonality of the pilots between users, PPHThen, the unit diagonal matrix I is changed, and:
since the previous assumptions are available, the mean square error of the channel estimate is:
in the embodiment of the invention, for whether the current single user channel is polluted by the pilot frequency, the formula (16) is adopted for channel estimation, and the formula (17) is adopted as a calculation mode of the mean square error of the channel, so that the larger the mean square error of the channel is, the more serious the pilot frequency pollution of the user channel is.
Fourthly, the pilot frequency allocation scheme, the embodiment of the invention further analyzes the signal-to-interference ratio of a single user and the reachable rate of the system, and then completes the allocation of the cell pilot frequency set and the pilot frequency reallocation of the single user on the basis.
The embodiment of the invention carries out LS estimation on the channel, and can obtain the following results:
here, the first and second liquid crystal display panels are,
representing equivalent noise.
After the pilot frequency transmission is completed, the user k of the cell i performs linear detection on the received signal, and the following results are obtained:
the first term of formula (19) represents the effective signal, the second term represents the interference signal of the same user in different cells, and the third term δi,kRepresenting cell interference signals and uncorrelated noise.
As can be seen from the Rayleigh fading channel characteristics, when the number M of base station antennas is larger and larger, the channel matrix vectors approach to orthogonality, that is, the increase rate of the inner product of the desired user channel vector and the interfering user channel vector is much smaller than the increase rate of the inner product of the desired user channel vector itself, and equation (21) is satisfied.
Wherein, IMIs an M-th order identity matrix, and therefore:
namely:
it can be seen that the uplink signal to interference plus noise ratio of user k in cell i is shown in equation (24).
When the number M of antennas of the cell base station is close to infinity, the third term of equation (19) is averaged out and can be ignored, and then the magnitude of the equivalent signal to interference plus noise ratio is mainly determined by β as can be known from equation (24).
And by combining with a shannon formula, the sum rate of all users in all cells of the system approximately meets the following requirements:
and averaging the sum rate R to obtain the average sum rate of the users.
The embodiment of the invention analyzes the signal-to-interference ratio of the user and the reachable rate of the system, and further provides a pilot frequency allocation algorithm, and the specific analysis is as follows.
Firstly, dividing the service grade of a cell into A, B, C grades and D grades from high to low, wherein the grade A has the highest priority and generally refers to various conversation and live broadcast services, and the like, and the service has the advantages of small time delay and high accuracy; the priority of the level B is lower than that of the level A, and generally refers to some online operation services and the like, such as remote login, payment and other services; the priority of the level C is lower than that of the level B, and the level C generally refers to various browsing query services and the like; level D has the lowest priority and is typically referred to various mail services, as shown in table 1.
Table 1 cell service ranking
| Service class | Degree of priority | Type of service |
| A | Highest point of the design | Various sessions, live broadcast services, etc |
| B | Is higher than | On-line operation business, etc |
| C | Is lower than | Browse query services and the like |
| D | Lowest level of | Mail service, etc |
In the embodiment of the invention, four pilot sets are designed, namely S1, S2, S3 and S4.
Where, p is K, the number of vectors in the pilot sets S1, S2, S3 and S4 are all the same, each element vector is τ × 1 dimension, τ is the pilot sequence length, and here, τ is 16. The pilot vectors in each pilot set are orthogonal, and due to the limitation of pilot resources, the pilot vectors in different pilot sets are multiplexed. However, the difference between the 4 pilot sets is that the pilot set S1 has a larger span and the pilot sequence is represented by the number symbols 1,2, 3.. et al, and in the pilot set S1, there are 15 number symbols in total, but the number symbols are not all between 1 and 15, and the interval length thereof is larger, and may be between 1 and 25, so that p non-repeating number symbols are randomly taken between the intervals [1, 25], so that the probability that each number symbol is different by a larger value is increased. Similarly, there are 15 number symbols in the pilot set S2, but the interval length cell may be [1, 20], so that the probability that each number symbol is different by a larger value is smaller than that in the pilot set S1, and so on, the interval length in the pilot set S4 is the smallest and each number symbol is not different by a larger value. The design is aimed at two points: firstly, ensuring that the user has no intra-cell interference because each pilot frequency vector in the pilot frequency set of each cell is not repeated; secondly, considering the requirement of the service level, different pilot frequency sets can be applied to different service levels, and the comprehensive performance of the system is improved, and the allocation mode adopted by the embodiment of the invention is shown in table 2.
Table 2 cell traffic pilot set allocation
| Service class | Degree of priority | Pilot allocation | Orthogonality |
| A | Highest point of the design | S1 | Highest point of the design |
| B | Is higher than | S2 | Is higher than |
| C | Is lower than | S3 | Is lower than |
| D | Lowest level of | S4 | Lowest level of |
After the pilot frequency sets with different orthogonality are distributed to the cells with different services, in order to further reduce the influence caused by pilot frequency pollution, the embodiment of the invention further processes the single user of the cell equipped with the pilot frequency set. In the multi-cell to which the pilot frequency set has been allocated, although the orthogonality of the pilot frequency of each user with a high service level is certainly greater than the orthogonality of the pilot frequency of each user with a low service level, there is a probability that a certain user has serious pilot frequency multiplexing, but the probability is relatively low, and if the pilot frequency pollution just suffered by the user is serious, serious interference will be caused to transmission. To avoid this phenomenon, it is necessary to find a "degree" that can measure the pilot pollution between different cell users, and as can be seen from the previous derivation, the average sum rate of the cell users and the large-scale fading system factor β are closely related, and the pilot pollution strength can be defined with all the large-scale fading system factors β known:
ωi,k,j,kindicating the magnitude of the pilot pollution intensity between cell i user k and cell j user k is a scalar, and therefore, the index, ω, is traded offi,k,j,kAnd ωj,k,i,kThe values of (c) are the same. Looking at equation (27) in detail, it is found that when i and j have the same value, ω isi,k,j,kIt is always a positive number, but as can be seen from the foregoing pilot allocation algorithm, all users in the same cell are allocated mutually orthogonal pilots, there is no pilot multiplexing in the cell, and therefore pilot pollution is not mentioned, which contradicts the result of equation (27), and in order to avoid this, it is specified that equation (27) exists under the precondition that i ≠ j, as shown in equation (28).
Defining the threshold value of the pilot pollution intensity as omegathIf the pilot pollution intensity ωi,k,j,k＜ωthAt this time, the pilot pollution level is considered to be small, if the pilot pollution intensity is omegai,k,j,k≥ωthIf the pilot pollution intensity is larger, then the serious pilot pollution exists between the cell i user k and the cell j user k, and the pilots need to be reallocated to the users of the two different cells. Because of the limitation of pilot resources, the paper mainly reduces the intensity of pilot pollution from large to smallThe first 20 ranked users perform pilot reallocation, which can reduce the pilot pollution phenomenon well.
Referring to fig. 3, the pilot allocation algorithm provided in the embodiment of the present invention first determines the number of cells and the service type according to the input parameters, performs pilot set allocation by referring to a designed pilot set allocation table, calculates the pilot pollution intensity of each user in the cell again after the pilot set is allocated, and performs pilot reallocation for a single user with a large pilot pollution intensity, where the process mainly includes the following steps:
step 1: inputting a service type _ server and a cell type _ zone;
step 2: judging whether the type _ server is one of A, B, C and D, if not, executing the step 8; if yes, executing step 3;
and step 3: judging whether the type _ server is A, if so, configuring a pilot frequency S1, then calculating the pilot frequency pollution intensity of each user of the cell, executing step 7, and if not, executing step 4;
and 4, step 4: judging whether the type _ server is B, if so, configuring a pilot set S2, then calculating the pilot pollution intensity of each user of the cell, executing step 7, and if not, executing step 5;
and 5: judging whether the type _ server is C, if so, configuring a pilot set S3, then calculating the pilot pollution intensity of each user of the cell, executing step 7, and if not, executing step 6;
step 6: configuring a pilot frequency set S4, calculating the pilot frequency pollution intensity of each user in the cell, and executing step 7;
and 7: calculating whether the pilot frequency pollution intensity of each user in the cell is greater than a threshold value, if the pilot frequency pollution intensity of a certain user is greater than the threshold value, recording the type _ zone and the type _ user of the current user, reallocating the pilot frequency for the user, and then executing the step 8; if the pilot frequency pollution intensity of the user is not larger than the threshold value, directly executing the step 8;
and 8: and outputting the pilot matrix P.
Claims (5)
1. A method for pilot allocation, the method comprising:
(1) establishing a channel model, namely selecting a proper channel model in a Massive MIMO system;
(2) establishing a multi-cell multi-user scene, including the design of cell parameters and cell user channels;
(3) designing a pilot frequency distribution scheme, wherein in consideration of different service requirements of different users, services are classified according to priority, different priority services can be distributed with pilot frequency sets with different orthogonality, pilot frequency pollution intensity is introduced for a single user distributed with a pilot frequency set cell, if the pilot frequency pollution intensity is too large, pilot frequency redistribution of a special user is carried out, the pilot frequency set distribution is specific to the cell, the pilot frequency redistribution is specific to the single user, and the single user must be located in the cell distributed with the pilot frequency set;
(4) index evaluation and system performance evaluation.
2. The method of claim 1, wherein the step (1) establishes a channel model of Massive MIMO, and the channel model of Massive MIMO mainly comprises:
the large-scale fading model mainly takes a lognormal shadow fading model, and the small-scale model mainly takes a Rayleigh distribution model.
3. The method of claim 1, wherein the step (2) of establishing the multi-cell multi-user scenario mainly comprises:
the number of cells, the number of users of the cells, the number of antennas of the base station, the radius of the cells, the path loss factor, the average transmitting power and a cell user channel model.
4. The method of claim 1, wherein the pilot allocation scheme design of step (3) mainly comprises:
(1) design of orthogonal pilots
Designing by means of a Walsh function and a Hadamard matrix, and generating an orthogonal pilot sequence with the length of 16 by adopting a 4QAM modulation mode;
(2) implementation of channel estimation
The channel estimation is used for measuring whether the pilot frequency multiplexing occurs to a single user channel of the current cell or not, and the channel estimation is carried out by adopting a least square method;
(3) allocation of cell pilot sets
Designing four pilot frequency sets, S1, S2, S3 and S4, wherein the orthogonality sequentially goes from high to low, the pilot frequency in each pilot frequency set is orthogonal, the cell service is divided into four types of A, B, C and D, different pilot frequency sets are allocated to cells of different services, and the pilot frequency in each pilot frequency set is orthogonal, so that pilot frequency multiplexing cannot occur among users in the same cell, and the higher the orthogonality of the pilot frequency sets is, the lower the probability of pilot frequency multiplexing between the users in the cell and other cells is;
(4) pilot reallocation for individual users of a cell
And carrying out pilot frequency redistribution on a single user for the cell which is distributed with the pilot frequency set, defining the pilot frequency pollution intensity, taking the pilot frequency pollution intensity as the basis of calculation, and carrying out the redistribution of the pilot frequency for the user of which the pilot frequency pollution intensity is greater than the threshold value.
5. The method of claim 1, wherein the index evaluation of the pilot allocation scheme in step (4) mainly comprises:
the channel mean square error and the user reachable rate are used for measuring whether the cell user channel has pilot pollution or not, and the user reachable rate is used for measuring the overall pilot pollution degree of the system.
Priority Applications (1)
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