CN105978673A - User distance based pilot frequency distribution method in large scale distributive antenna system - Google Patents

Abstract

The invention discloses a user distance based pilot frequency distribution method in a large scale distributive antenna system. The method is characterized in that after a user in a dominated state is selected as a key user, P-1 users that are most adjacent to the user is eliminated and the rest users is divided into P groups by adopting the distribution method in a recursive way; the optimal group and the user in the dominated state are arranged in one pilot frequency group and the distribution of the next pilot frequency group is performed, wherein P is the pilot frequency number. According to the invention, by adopting the employed algorithm, the estimation performance approximate to traverse optimal (performance upper limit) can be realized with comparatively low complexity.

Description

Pilot distribution method based on user distance in large-scale distributed antenna system

Technical field

The invention belongs to wireless communication technology field, particularly in a kind of large-scale distributed antenna system based on user The pilot tone dispatching algorithm of distance.

Background technology

Distributing antenna system is a kind of new wireless communication systems structure, it comprise multiple on geographical position dispersion but The antenna element being connected with a center processing unit by optical fiber or cable etc..Compared to centralized antenna system, it is in fall Low transmit power, improve area coverage and reduce the aspect such as outage probability and have a clear superiority in.Distributing antenna system starts most It is mainly used in improving the area coverage of indoor wireless communication and reducing outage probability, the most slowly develops into outdoor as outdoor A kind of main flow communication technology in the region such as stadium, city.At present, in conjunction with the cloud access technology (C-of distributing antenna system RAN) as a kind of new network architecture form, owing to having big advantage in terms of spectrum efficiency and energy efficiency, more come More by concern and the research of people.

As the one in multi-input multi-output system, in order to obtain space diversity gain and sky by precoding technique Between degree of freedom eliminate the common-channel interference between user, the acquisition of channel information is the most crucial in distributing antenna system.When Before channel estimation technique be broadly divided into two classes: estimation based on pilot tone, blind/semi-blind estimation based on subspace etc..Based on son The estimation in space need not send pilot frequency sequence, can be effectively improved running time-frequency resource utilization rate, but to reach the preferably property estimated Can have certain constraints to antenna configurations etc., current research is mainly for centralized antenna system.At spaced antenna In system, main or utilization estimation technique based on pilot tone carries out channel estimation.

Estimation technique based on pilot tone, needs to consume certain running time-frequency resource to send pilot frequency sequence.In order to ensure time-frequency The utilization rate of resource, the number of pilots that system allows is limited, therefore it is generally required to multiple user shares a pilot tone.Use same Interference (referred to as pilot pollution) can be produced so that systematic function is remarkably decreased between the user of pilot tone.How to be dispatched by pilot tone Make the pilot pollution problem the least be one of great value to study a question.Ergodic algorithm is to all possible scheduling scheme Compare, the scheduling scheme of optimum can be obtained, but complexity is the highest, is a np hard problem.In systems in practice, time Go through algorithm cannot use completely.Greedy algorithm complexity is relatively low, but performance is unsatisfactory.And, using greedy algorithm When being scheduling, the subscriber channel of the most late distribution estimates that performance can be the poorest, and this does not meets the principle of fairness.

Summary of the invention

Technical problem: in order to overcome the deficiency of existing pilot tone dispatching algorithm, the invention provides a kind of based on user's spacing From dispatching algorithm, can reach to approach, with relatively low complexity, the scheduling performance that traversal is optimum.

Technical scheme: found by analysis, uses least-mean-square error algorithm to carry out the situation of channel estimation at receiving terminal Under, when distance tends to infinity to the user distributing same pilot tone each other, mean square estimation difference will be close to zero.Based on this, This dispatching algorithm reduces the most greatly mean square estimation difference by making the spacing being assigned to often organize the user under pilot tone.Adjust The basic thought of degree: choose successively and be assigned to often organize the user under pilot tone；When each iteration, choose distance each other and to the greatest extent may be used While user that can be big so that remaining user disperses as far as possible.

Pilot distribution method based on user's spacing under a kind of large-scale distributed antenna system, it is characterised in that choosing Go out the user being in a disadvantageous position as key user after, get rid of P-1 the user closest with it, by remaining users recurrence use This distribution method is divided into P group, selects best one group and the user being in a disadvantageous position is assigned under same pilot group, under then carrying out The distribution of one group of pilot tone, wherein, P is pilot number.

The concrete steps of pilot tone distribution:

Step 1: choose key user u^key:

Step 2: distribution comprises key user u^keyA pilot group, concrete grammar is:

With u in eliminating U^keyP-1 closest user, by remaining P (K^pilot-1) individual user calls Recursive schedule calculation Method is divided into P group, often group (K^pilot-1) individual user (is i.e. P (K by total number of users^pilot-1), pilot number is that the situation of P is carried out point Joining, concrete recurrence performs step and sees below), it is designated asWherein, K^pilotFor often organizing the use of pilot tone distribution Amount；

Select optimum one groupWith u^keyIt is assigned to together under same group of pilot tone, constitutes

$U_P^{opt}=\left\{u^{key}\right\}\∪U_{g^{opt}}^{rem}$

Step 3: repeat step 1 and step 2, be sequentially completed the distribution of a pilot group.

The choosing method of key user is:

Step 1-1: distance threshold d is set^th, obtain user and gather the user bunch all corresponding to this threshold value in U, take wherein Bunch of C that number of users is most, if its number of users is K_C；

Step 1-2: if number of users K in bunch_CNot less than pilot number P, the central user choosing bunch C is key user u^key:

$u^{key}=\arg \underset{j}{\min }\left\{\underset{i}{\max }\right\{{\[D\left(C\right)\]}_{ij}\left\}\right\}$

In formula, D (C) is the distance matrix in user bunch C between user, [D (C)]_ijRepresent distance matrix the i-th row jth row first Element, i, j corresponding user respectively gathers in U i-th, j user；

Otherwise, choose whole user gathering the central user of U is key user u^key:

$u^{key}=\arg \underset{j}{\min }\left\{\underset{i}{\max }{\[D\left(U\right)\]}_{ij}\right\}$

Optimum one groupFor:

$g^{opt}=\arg \underset{g=1,\mathrm{...},P}{\min }M\left(\right\{u^{key}\}\∪U_g^{rem})$

M () represents mean square estimation difference when one group of user is assigned to same pilot group.

The execution step of described Recursive schedule algorithm is:

Often distribute two user (K under group pilot tone^pilot=2), time, comprise the concrete steps that:

A, select key user u according to step 1^key, get rid of P-1 the user closest with it, P user of residue In select best one with key user u^keyIt is assigned under same group of pilot tone；

B, get rid of allocated 2 users, remaining users is selected key user again, repeat step a until will be all User is distributed into P group；

Often distribute three user (K under group pilot tone^pilot=3), time, comprise the concrete steps that:

Key user u is selected according to step 1^key, get rid of P-1 the user closest with it, residue 2P user pressed According to K^pilotAssigning process when=2 is divided into P group, selects best one group and key user u^keyIt is assigned under same group of pilot tone；Row Except allocated user, repeat this process until all users are divided into P group.

……

Often distribute S user (K under group pilot tone^pilot=S) time, comprise the concrete steps that:

Key user u is selected according to step 1^key, get rid of P-1 the user closest with it, will residue (S-1) P use Family is according to K^pilotAssigning process during=S-1 is divided into P group；One group that selects optimum is assigned to same group of pilot tone with key user Under；Get rid of allocated user, repeat this process until all users are divided into P group.

It is optimum (in performance that the algorithm that pilot distribution method of the present invention uses can realize approaching traversal with relatively low complexity Limit) estimation performance.

Accompanying drawing explanation

Fig. 1. flow chart based on user's spacing dispatching algorithm.

Fig. 2. number of users is simulation result during pilot number integral multiple (K=12, P=4).

Fig. 3. number of users is not simulation result during pilot number integral multiple (K=14, P=4).

Poisson distribution and K=14, simulation result during P=4 are obeyed in Fig. 4 .RAU position.

Detailed description of the invention

Below in conjunction with the accompanying drawings and instantiation, it is further elucidated with the present invention, it should be understood that this example is merely to illustrate the present invention Rather than restriction the scope of the present invention, after having read the present invention, the those skilled in the art's various equivalences to the present invention The amendment of form all falls within the application claims limited range.

First following description is done: in distributed extensive mimo system, total K single-antenna subscriber, constitute set U, The each RAU of base station end is also equipped with single antenna, and RAU number is M.E_PRepresent pilot power,Represent Pth pilot frequency sequence, and meeth_k∈C^M×1Represent the kth user channel vector to base station end, Y ∈C^M×τIt is to receive signal matrix, N ∈ C^M×τIt it is noise matrix.

The system model in uplink channel estimation stage:

$Y=\underset{p=1}{\overset{P}{\Σ}}\underset{k\∈U_p}{\Σ}\sqrt{E_p}{h}_k{s}_p^T+N$

At receiving terminal, reception signal is done relevant to known pilot frequency sequence, and defines Mutually orthogonal in view of different pilot frequency sequences, then have

$\begin{array}{c}{y}_p=\underset{k\∈U_p}{\Σ}{h}_k+n_p\\ =h_{k_p}+\underset{k\∈U_p/k_p}{\Σ}{h}_k+n_p\end{array}$

WhereinThe estimated value obtained by MMSE estimation and the mean square estimation difference of correspondence are

${\hat{h}}_{k_p}=R_{k_p}{(\underset{k\∈U_p}{\Σ}+\frac{{\mathrm{\σ}}_n^2}{E_P}I)}^{-1}{y}_p$

$M_{k_p}=tr\{R_{k_p}-R_{k_p}^2{(\underset{k\∈U_p}{\Σ}{R}_k+\frac{{\mathrm{\σ}}_n^2}{E_P}I)}^{-1}\}$

It is i-th element r on diagonal matrix, and diagonal_k,iRepresent the user k that i-th RAU receives Mean power.Our research has a problem in that the user that how to distribute in U is to different pilot group { U_p, so that overall Mean square estimation difference is minimum, and mathematical notation is

$\{U_1^{opt},U_2^{opt},...,U_P^{opt}\}=\arg \underset{U_1,U_2,\mathrm{...}{U}_P}{\min }\underset{p=1}{\overset{P}{\Σ}}\underset{k_p\∈U_p}{\Σ}{M}_{k_p}$

Distance matrix D (U)=[d of U is collected based on user_ij]_i,j∈UDefine two class users:

It is in the user of center:

$u^{center}=\arg \underset{j}{\min }\left\{\underset{i}{\max }{\[D\left(U\right)\]}_{ij}\right\}$

Owing to there is no the positional information of user, it is contemplated that compare boundary user and be in user and other users of center Ultimate range can be less, therefore had the definition of above central user based on distance.

User bunch.Set a distance threshold d^th, it is such a collection for one group of user U, user bunch C thereon In conjunction bunch, the distance between any two user u and u ' is not more than threshold value d^th, bunch outer any user with bunch at least one Distance between user is more than threshold value d^th.Mathematical notation is

$\left\{\begin{array}{c}\underset{u,u^{\′}\∈C}{\max }d(d,u^{\′})\≤d^{th}\\ \underset{u\∈C}{\max }d(u,u^{\′\′})>d^{th},\∀u^{\′\′}\∈U-C\end{array}\right.$

Our algorithm chooses the user's group being assigned to often organize under pilot tone successively.For the user bunch that number of users is more, should In avoiding as far as possible bunch, user is assigned to same pilot group, therefore in the presence of such bunch, and the center that we preferentially select bunch User, and select the one group user distant with it to be assigned to same pilot group.And on whole user's collection to be allocated Central user, owing to the number of users distant with it comparatively speaking can be fewer, when there is not the user bunch of relatively multi-user Also should pay the utmost attention to.

First introducing the situation that number of users K=| U | is pilot number P integral multiple, the most often group pilot tone distributes same number K^pilot= The user of K/P.For general situation, need only the most slightly improve, after have specific description.

Number of users is pilot tone allocation step during pilot number integral multiple, as shown in Figure 1:

Step 1: obtain the Distance matrix D (U) between user, and p=1 is set；

Step 2: cluster.Distance threshold d is set^th, obtain user and gather the user bunch all corresponding to this threshold value in U, Take bunch of C that wherein number of users is most, if its number of users is K_C。

Step 3: choose key user u^key.Selection standard:

If number of users K in bunch_CNot less than pilot number P, the central user choosing bunch C is key user u^key:

$u^{key}=\arg \underset{j}{\min }\left\{\underset{i}{\max }{\[D\left(C\right)\]}_{ij}\right\}$

Otherwise, choose whole user gathering the central user of U is key user u^key:

$u^{key}=\arg \underset{j}{\min }\left\{\underset{i}{\max }{\[D\left(U\right)\]}_{ij}\right\}$

Step 4: select one group of user the most distant and u^keyIt is assigned under same pilot group.Get rid of in U With u^keyP-1 closest user, by remaining P (K^pilot-1) individual this dispatching algorithm of user's recursive call is divided into P group, often Group (K^pilot-1) individual user, is designated as(note: if there is multiple number of users in step 2 more than pilot tone Number bunch, then in addition to selected bunch C, these bunches remaining can progressively be spread out in this step)

Select optimum one group and u^keyIt is assigned to together under pth group pilot tone, constitutes

$i^{opt}=\arg \underset{i=1,\mathrm{...},P}{\min }M\left(\right\{u^{key}\}\∪U_i^{rem})$

$U_P^{opt}=\left\{u^{key}\right\}\∪U_{i^{opt}}^{rem}$

M () represents mean square estimation difference when one group of user is assigned to same pilot group.

Step 5: gather from user and get rid of the most the allocated user UUnallocated pilot number P=P- 1, remaining users number K=K-K^pilot, reacquire Distance matrix D (U), repeat step 2 to 5 and carry out next group pilot tone p=p+1 Distribution.

In a practical situation, number of users K may not be the integral multiple of number of pilots P.When this happens, may be used To be scheduling as follows:

Step 1: takeThen there is P₁ +P₂=P,

Step 2: distribution P₂Individual containThe pilot group of individual user:

A, acquisition user gather the user u being in border in U^border:

$u^{border}=\arg \underset{j}{\max }\left\{\underset{i}{\max }{\[D\left(U\right)\]}_{ij}\right\}$

With u in B, eliminating U^borderClosest P₂-1 user, by remainingIndividual user is by the tune of a upper trifle Degree algorithm is divided into P group, often groupIndividual user, is designated as

C, select from P group user obtained in the previous step optimum one group and u^borderConstitute together

$i^{opt}=\arg \underset{i=1,\mathrm{...},P}{\min }M\left(\right\{u^{border}\}\∪U_i^{rem})$

$U_p^{opt}=\left\{u^{border}\right\}\∪U_i^{rem}$

Delete user gather in U withCorresponding user, repeats step A, B, C until distributing P₂Group user

Step 3: remaining user is divided into P by the dispatching algorithm of a upper trifle₁Group, often groupIndividual user.

Actual range between user may be not readily available, and the concept of our definition " interference distance " is in order to substitute.Examine Consider two users and share the mean square estimation difference of one of them user under a pilot tone situation:

$M_1=tr\{R_1-R_1^2{(R_1+R_2+\frac{{\mathrm{\σ}}_n^2}{E_P}I)}^{-1}\}$

Accordingly, the mean square estimation difference when not having pilot pollution to only have noise is

$M_1^{no\mathrm{int}}=tr\{R_1-R_1^2{(R_1+\frac{{\mathrm{\σ}}_n^2}{E_P}I)}^{-1}\}$

The impact that analysis pilot pollution causes:

$\begin{array}{c}{M}_1-M_1^{no\mathrm{int}}=tr\{R_1^2{(R_1+\frac{{\mathrm{\σ}}_n^2}{E_P})}^{-1}-R_1^2{(R_1+R_2+\frac{{\mathrm{\σ}}_n^2}{E_p}I)}^{-1}\}\\ \≤\underset{n}{\Σ}\frac{r_{1,n}^2}{\frac{{\mathrm{\σ}}_n^2}{E_P}+r_{1,n}}-\frac{r_{1,n}^2}{\frac{{\mathrm{\σ}}_n^2}{E_P}+r_{1,n}+r_{2,n}}\\ \≤\underset{n}{\Σ}\frac{r_{1,n}^2{r}_{2,n}}{r_{1,n}(r_{1,n}+r_{2,n})}\\ =\underset{n}{\Σ}\frac{r_{1,n}{r}_{2,n}}{r_{1,n}+r_{2,n}}\end{array}$

Likewise it is possible to obtain the impact that another user is caused by pilot pollution

DefinitionWhat we can approximate thinks, Δ I₁₂The least, the pilot pollution between user 1,2 is asked Topic will be the least.Definition interference distance

$d_{ij}^{\mathrm{int}}\stackrel{\mathrm{\Δ}}{=}\frac{1}{{\mathrm{\ΔI}}_{ij}}={\left(\underset{n}{\Σ}\frac{r_{i,n}{r}_{j,n}}{r_{i,n}+r_{j,n}}\right)}^{-1}$

So interference distance is the biggest, and the pilot pollution problem between user will be the least, and between user, actual range is dirty to pilot tone As the impact of metachromia energy.

At K=14, during P=4,2 groups of pilot tones are had to distribute 4 users, 2 groups of pilot tone 3 users of distribution.First distribution is containing 4 The pilot group of user:

Step 1: obtain user and gather the user u being in border in U^border:

$u^{border}=\arg \underset{j}{\max }\left\{\underset{i}{\max }{\[D\left(U\right)\]}_{ij}\right\}$

Step 2: with u in eliminating U^border1 closest user, by remaining 12 users by the tune of a upper trifle Degree algorithm is divided into 4 groups, and often 3 users of group, are designated asCalculate this four groups of users and u respectively^borderGroup The mean square estimation difference being combined, select corresponding mean square estimation difference minimum one group and u^borderDistribute together at first group Under pilot tone；

Step 3: get rid of allocated user, selects the user u being in border in 10 users of residue^border2, equally will Remain 9 users and be divided into 3 groups, select best one group and boundary user u^border2It is assigned to together under second group of pilot tone；

Then it is divided into two groups by remaining 6 users, often 3 users of group.

Step 4: select the key user u in 6 users^key, get rid of a user nearest with it, and 4 use will be remained K is pressed at family^pilotAllocation algorithm when=2 is divided into 2 groups.Calculate this two groups of users and u respectively^keyThe mean square estimation combined is by mistake Difference, selects less one group and u^keyIt is assigned under the 3rd group of pilot tone；Remaining 3 users are assigned under the 4th group of pilot tone.

Emulate the distributing antenna system being equipped with single antenna based on each RAU end.Base station end 100 single antenna of configuration RAU, each RAU are uniformly distributed on geographical position, neighbouring 4 RAU constitute one between square, and adjacent R AU away from From for 100m, customer location stochastic generation.

It is simulation result during pilot number integral multiple (K=12, P=4) that Fig. 2 gives number of users.Fig. 2 (a), 2 (b) are respectively Give channel estimation errors and average relation between user rate and signal to noise ratio.In figure, " Best " represents traversal optimum and calculates Method, be take after the mean square estimation difference that all possible pilot allocation scheme travels through and compares different schemes the most equal Estimation difference minimum a kind of in side's obtains, and this is the higher limit of performance；" Worst " represents and travels through worst algorithm, under performance Limit value；" Greedy " represents greedy algorithm；" Loc " represents dispatching algorithm based on distance in this paper；" random " represents Random schedule.It can be seen that whether channel estimation errors or average user speed, algorithm performance in this paper is the most permissible Approach traversal optimal performance, and be better than greedy algorithm and Randomized scheduling algorithm.

It is not simulation result during pilot number integral multiple (K=14, P=4) that Fig. 3 gives number of users.In this case, Greedy algorithm is also pilot group and the pilot group of 2 groups of 3 users that all users are divided into 2 groups of 4 users, and first distributes 4 The pilot group of 3 users is distributed after the pilot group of user.Owing to ergodic algorithm is the most complicated, corresponding emulation knot Fruit is not given.It will be seen that location-based dispatching algorithm estimation difference performance when high s/n ratio is still substantially better than greedy Greedy algorithm.

Fig. 4 gives the simulation result during obedience Poisson distribution of RAU position, it can be seen that algorithm performance in this paper depends on It is so optimum.

Claims (7)

1. pilot distribution method based on user's spacing under a large-scale distributed antenna system, it is characterised in that select After the user being in a disadvantageous position is as key user, gets rid of P-1 the user closest with it, remaining users recurrence is used this Distribution method is divided into P group, selects best one group and the user being in a disadvantageous position is assigned under same pilot group, then carry out next The distribution of group pilot tone, wherein, P is pilot number.

Pilot distribution method the most according to claim 1, it is characterised in that the concrete steps of pilot tone distribution:

Step 1: choose key user u^key:

Step 2: distribution comprises key user u^keyA pilot group, concrete grammar is:

With u in eliminating U^keyP-1 closest user, by remaining P (K^pilot-1) individual this dispatching algorithm of user's recursive call It is divided into P group (concrete recurrence performs step and sees claim 7), often group (K^pilot-1) individual user, is designated asWherein, K^pilotFor often organizing the number of users of pilot tone distribution；

Select optimum one groupWith u^keyIt is assigned to together under same group of pilot tone, constitutes

Step 3: repeat step 1 and step 2, be sequentially completed the distribution of a pilot group.

Pilot distribution method the most according to claim 2, it is characterised in that the choosing method of key user is: step 1- 1: distance threshold d is set^th, obtain user and gather the user bunch all corresponding to this threshold value in U, take that wherein number of users is most one Individual bunch of C, if its number of users is K_C；

Step 1-2: if number of users K in bunch_CNot less than pilot number P, the central user choosing bunch C is key user u^key:

In formula, D (C) is the distance matrix in user bunch C between user, [D (C)]_ijRepresent distance matrix the i-th row jth column element, i, J corresponding user respectively gathers in U i-th, j user；

Otherwise, choose whole user gathering the central user of U is key user u^key:

Pilot distribution method the most according to claim 3, it is characterised in that described Distance matrix D (U)=[d_ij], wherein d_ijRepresent that user gathers the distance in U between i-th user and jth user.

Pilot distribution method the most according to claim 3, it is characterised in that described distance matrix available interference distance matrixSubstitute,Represent the interference distance between i-th user and jth user in U, be defined as

Wherein, r_i,n,r_j,nRepresent that the n-th antenna element receives i-th respectively, the mean power of j user.

Pilot distribution method the most according to claim 2, it is characterised in that optimum one groupFor:

M () represents mean square estimation difference when one group of user is assigned to same pilot group.

Pilot distribution method the most according to claim 2, it is characterised in that the execution step of described Recursive schedule algorithm It is:

Often distribute two user (K under group pilot tone^pilot=2), time, comprise the concrete steps that:

A, select key user u according to step 1^key, get rid of P-1 the user closest with it, select in P user of residue Go out best one and key user u^keyIt is assigned under same group of pilot tone；

B, get rid of allocated 2 users, remaining users is selected key user again, repeat step a until by all users It is distributed into P group；

Often distribute three user (K under group pilot tone^pilot=3), time, comprise the concrete steps that:

Key user u is selected according to step 1^key, get rid of P-1 the user closest with it, will 2P user of residue according to K^pilotAssigning process when=2 is divided into P group, selects best one group and key user u^keyIt is assigned under same group of pilot tone；Get rid of Allocated user, repeats this process until all users are divided into P group；

……

Often distribute S user (K under group pilot tone^pilot=S) time, comprise the concrete steps that:

Key user u is selected according to step 1^key, get rid of P-1 the user closest with it, residue (S-1) P user pressed According to K^pilotAssigning process during=S-1 is divided into P group, selects optimum one group and is assigned under same group of pilot tone with key user；Row Except allocated user, repeat this process until all users are divided into P group.