A kind of LTE network coverage optimization method based on Modified particle swarm optimization
Technical field
The present invention relates to a kind of LTE network coverage optimization method based on Modified particle swarm optimization in mobile communication field,
Belong to mobile communication network technology field.
Background technology
With the continuous promotion of mobile device quantity being continuously increased with user's QoS requirement, user is to the network coverage
The requirement of performance is continuously improved.By optimizing the antenna tilt of base station, the promotion of network covering property can be effectively obtained.So
And the Covering judgment criterion that existing antenna tilt optimization method uses only considers most the connecing by force from base station that user receives
It receives whether signal power is more than certain thresholding, does not consider the load state of base station and the rate requirement of user, although so as to cause
User can receive from the sufficiently strong received signal power of serving BS, but due to serving BS load too high, user's speed
Rate demand is unable to get satisfaction, and simultaneously, some low-load base stations of surrounding are unable to get the problem of efficiently using.Cause
This, it is contemplated that the above problem, the present invention propose that a kind of LTE network coverage optimization method based on improvement population, this method are examined
The load state for considering network obtains the significant increase of network covering property by optimizing antenna for base station inclination angle.
Invention content
The purpose of the present invention is under conditions of considering Network load status, propose a kind of based on Modified particle swarm optimization
LTE network coverage optimization method solves LTE network covering problem by optimizing antenna tilt, is ensureing user rate demand
Maximization network coverage rate simultaneously.
LTE network coverage optimization method proposed by the present invention based on Modified particle swarm optimization, includes the following steps:
Initialize network composition and parameter:Assuming that thering is N number of eNB, each eNB to have N in system modeltRoot antenna, in system
Shared M=NtN roots antenna and U user.Maximum iteration is tmax(can be set by operator), current iteration number t=0.
The first step:A variety of candidate antenna tilt set and antenna tilt adjustment scale set are set.Random initializtion p kinds are waited
Select antenna tilt set { ψ1(t), ψ2(t) ..., ψp(t) }, wherein the antenna tilt setIn elementIt is
The inclination angle of kth root antenna, ψ in n kind antenna tilt setminIt (can be set by antenna manufacturer for minimum angle-of-incidence workable for each antenna
It is fixed), ψmaxFor inclination maximum (can be by antenna manufacturers set).Random initializtion p kind antenna tilts adjust scale set { v1
(t), v2(t) ..., vp(t) } corresponding, wherein being n tested rotating platform scale set
In n antenna tilt set ψn(t), element is that n antenna tilt adjusts kth in scale set
The Inclination maneuver scale of root antenna, needs to meet
Second step:Calculate each antenna tilt set ψn(t) corresponding system utility.For current each antenna tilt set
ψn(t), user j (j ∈ [1, U]) calculates received come fromAntennaGinseng
Examine signal reception power (RSRP) PJ, i, k,
PJ, i, k=PiLJ, isjGJ, i, k, (1)
Wherein PiIt is the transmission power of eNB i, LJ, iIt is user's j to eNB i path losses, sjIt is the shadow fading of user j,
GJ, i, kIt is the antenna gain of the antenna k to user j of eNB i, with antenna tilt set ψn(t) related.Each user j is in all eNB
All antennas in selection RSRP be more than threshold value RSRPthrAnd the maximum eNB of RSRP and antenna combination (i, k) are associated with as it
ENB and antenna.If eNB and antenna combination (i, k) meet PJ, i, k> RSRPthrAnd (i, k) is in all eNB, all antennas
RSRP PJ, i, kMaximum combination, then user j be associated with (i, k), be denoted as uJ, i, k=1.What user j was received comes from eNB i days
The Signal to Interference plus Noise Ratio (SINR) of line k is
Wherein cnFor all adjacent interference eNB, i.e. c of eNB in≠ i, n0It is additive white Gaussian noise power.User j's
The bandwidth efficiency e obtained from eNB i antennas kJ, i, kFor
eJ, i, k=log2[1+γJ, i, k]。 (3)
In order to meet the data-rate requirements r of user jj, the Physical Resource Block for the eNB i antennas k that user j need to be occupied
(PRB) number is
Wherein BPRBFor the bandwidth of a PRB.The load for the eNB i antennas k that user j is occupied is
Wherein NPRBIt is the PRB number that each eNB possesses.The total load of eNB i is
ηi=∑J ∈ [1, U]uJ, i, kρJ, i, k。 (6)
To meet the data-rate requirements of user, the total load of each eNB should meet ηi≤ 1, claim ηi≤ 1 for eNB load about
Beam.The number of users n of eNB i antennas k coveringsI, kTo meet the sum of the number of users of Correlation Criteria and load restraint
System utility f (ψn(t)) it is the number of users being capped in system, i.e., meets Correlation Criteria and load restraint in system
The sum of all numbers of users
Third walks:Judge whether the candidate antenna tilt set for being unsatisfactory for load restraint.If in the presence of being unsatisfactory for loading
The candidate antenna tilt set of constraint then resets the antenna tilt collection merging computing system effectiveness for not being unsatisfactory for constraint, directly
Meet load restraint to all set;If being unsatisfactory for the set of load restraint, carry out in next step.
4th step:Record itself and global optimum's antenna tilt set.It, will current each antenna tilt set conduct if t=0
It is corresponding to be denoted as all antenna tilt set more obtained in the previous step for itself optimal set
The maximum set of system utility is gathered as current global optimum, is denoted as ψ by system utilityg(0), if t ≠ 0, by each antenna tilt aggregation system effectiveness obtained in the previous step with
Itself and the global optimum's system utility that last iteration obtains compare, if right
Then update itself optimal antenna inclination angle set otherwise,If
Then update global optimum's antenna tilt set otherwise ψg(t)=ψg(t-1).'s
The same formula of computational methods (8), by by the ψ in formula (8)n(t) it replaces with to obtain.
5th step:Update iterations t=t+1.
6th step:Update antenna tilt adjustment scale and candidate antenna tilt set.Calculate new antenna tilt adjustment ruler
Spend set vn(t) and candidate antenna tilt set ψn(t),
ψn(t)=ψn(t-1)+vn(t), (10)
Wherein, it rule of thumb studies, inertia weight ω (t)=ωmax-t(ωmax-ωmin)/tmax, ωmax=0.4, ωmin
=1, ξ, χ are the random number in [0,1] section, accelerator coefficient c1、c2Take 1.49.
7th step:Judge iteration termination condition.If t < tmax, then second step is returned to, each newer candidate antenna is calculated and inclines
Gather corresponding system utility and update itself and global optimum's antenna tilt set in angle;Otherwise, the 8th step is carried out.
8th step:Stop, the antenna tilt of each eNB is set according to obtained global optimum's antenna tilt set.
Compared with prior art, the present invention haing the following advantages:
It, can be in the condition for considering network load constraint by the eNB antenna tilt methods of adjustment based on particle group optimizing
The lower promotion for obtaining the network coverage, avoids the user rate demand that serving BS load too high is brought from being unable to get asking for satisfaction
Topic.It is carried out by minizone cooperation mode, and considers that network load constrains, can ensure that the antenna obtained inclines in practical applications
The reliability of angle set.
Description of the drawings
Fig. 1 is the LTE network coverage optimization method entire flow based on Modified particle swarm optimization of the present invention.
Specific implementation mode
The LTE network coverage optimization method based on Modified particle swarm optimization of the present invention.
A kind of embodiment is provided by taking LTE system as an example:
As shown in Figure 1, the LTE network coverage optimization method includes the following steps:
The first step:A variety of candidate antenna tilt set and antenna tilt adjustment scale set are set.Random initializtion p kinds are waited
Select antenna tilt set { ψ1(t), ψ2(t) ..., ψp(t) }, wherein the antenna tilt setIn elementIt is
The inclination angle of kth root antenna, ψ in n kind antenna tilt setminFor minimum angle-of-incidence, ψ workable for each antennamaxFor inclination maximum.With
Machine initializes p kind antenna tilts adjustment scale set { v1(t), v2(t) ..., vp(t) }, wherein being n tested rotating platform scale set, correspond to n antenna tilt set ψn
(t), element is the Inclination maneuver scale that n antenna tilt adjusts kth root antenna in scale set,
It needs to meet
Second step:Calculate each antenna tilt set ψn(t) corresponding system utility.For current each antenna tilt set
ψn(t), user j (j ∈ [1, U]) calculates received come fromAntennaGinseng
Examine signal reception power (RSRP) PJ, i, k,
PJ, i, k=PiLJ, isjGJ, i, k, (1)
Wherein PiIt is the transmission power of eNB i, LJ, iIt is user's j to eNB i path losses, sjIt is the shadow fading of user j,
GJ, i, kIt is the antenna gain of the antenna k to user j of eNB i, with antenna tilt set ψn(t) related.Each user j is in all eNB
All antennas in selection RSRP be more than threshold value RSRPthrAnd the maximum eNB of RSRP and antenna combination (i, k) are associated with as it
ENB and antenna.If eNB and antenna combination (i, k) meet PJ, i, k> RSRPthrAnd (i, k) is in all eNB, all antennas
RSRP PJ, i, kMaximum combination, then user j be associated with (i, k), be denoted as uJ, i, k=1.What user j was received comes from eNB i days
The Signal to Interference plus Noise Ratio (S1NR) of line k is
Wherein cnFor all adjacent interference eNB, i.e. c of eNB in≠ i, n0It is additive white Gaussian noise power.User j's
The bandwidth efficiency e obtained from eNB i antennas kJ, i, kFor
eJ, i, k=log2[1+γJ, i, k]。 (3)
In order to meet the data-rate requirements r of user jj, the Physical Resource Block for the eNB i antennas k that user j need to be occupied
(PRB) number is
Wherein BPRBFor the bandwidth of a PRB.The load for the eNB i antennas k that user j is occupied is
Wherein NPRBIt is the PRB number that each eNB possesses.The total load of eNB i is
ηi=∑J ∈ [1, U]uJ, i, kρJ, i, k。 (6)
To meet the data-rate requirements of user, the total load of each eNB should meet ηi≤ 1, claim ηi≤ 1 for eNB load about
Beam.The number of users n of eNB i antennas k coveringsI, kTo meet the sum of the number of users of Correlation Criteria and load restraint
System utility f (ψn(t)) it is the number of users being capped in system, i.e., meets Correlation Criteria and load restraint in system
The sum of all numbers of users
Third walks:Judge whether the candidate antenna tilt set for being unsatisfactory for load restraint.If in the presence of being unsatisfactory for loading
The candidate antenna tilt set of constraint then resets the antenna tilt collection merging computing system effectiveness for not being unsatisfactory for constraint, directly
Meet load restraint to all set;If being unsatisfactory for the set of load restraint, carry out in next step.
4th step:Record itself and global optimum's antenna tilt set.It, will current each antenna tilt set conduct if t=0
It is corresponding to be denoted as all antenna tilt set more obtained in the previous step for itself optimal set
The maximum set of system utility is gathered as current global optimum, is denoted as ψ by system utilityg(0), if t ≠ 0, by each antenna tilt aggregation system effectiveness obtained in the previous step with
Itself and the global optimum's system utility that last iteration obtains compare, if right
Then update itself optimal antenna inclination angle set otherwise,If
Then update global optimum's antenna tilt set otherwise ψg(t)=ψg(t-1).'s
The same formula of computational methods (8), by by the ψ in formula (8)n(t) it replaces with to obtain.
5th step:Update iterations t=t+1.
6th step:Update antenna tilt adjustment scale and candidate antenna tilt set.Calculate new antenna tilt adjustment ruler
Spend set vn(t) and candidate antenna tilt set ψn(t),
ψn(t)=ψn(t-1)+vn(t), (10)
Wherein, it rule of thumb studies, inertia weight ω (t)=ω ωmax-t(ωmax-ωmin)/tmax, ωmax=0.4,
ωmin=1, ξ, χ are the random number in [0,1] section, accelerator coefficient c1、c2Take 1.49.
7th step:Judge iteration termination condition.If t < tmax, then second step is returned to, each newer candidate antenna is calculated and inclines
Gather corresponding system utility and update itself and global optimum's antenna tilt set in angle;Otherwise, the 8th step is carried out.
8th step:Stop, the antenna tilt of each eNB is set according to obtained global optimum's antenna tilt set.