CN103441805A - Signal monitoring and optimizing method and system - Google Patents

Abstract

The invention discloses a signal monitoring and optimizing method and system and provides a wireless network structure assessment technology based on high-precision service channel timeslot frequency sweeping. The number of road overlapping and covering frequency points, road receiving indexes and road frequency share density values are obtained through accurate calculation, the comprehensive performance of a wireless network structure can be objectively reflected, subjectivity, inaccuracy and uncertainty in equivalent TCH frequency point measuring of basic traditional BCCH frequency point frequency sweeping measurement are overcome, and therefore monitoring and managing can be accurately performed on a communication signal. In addition, warning and reasonable optimizing and adjusting are performed according to the practical conditions of the signal, and the overall performance of a honeycomb wireless network is fundamentally improved and increased. Further, the comprehensive performance of the wireless network can be objectively and accurately assessed, a key cell and a key frequency point utilizing carrier timeslot grade measuring to perform accurate positioning and cause wireless network problems provide scientific and accurate measuring and analyzing means for adjusting and optimizing the wireless network structure.

Description

Signal monitoring and optimization method, system

Technical field

The present invention relates to the mobile communication technology field, particularly a kind of signal monitoring and optimization method, system.

Background technology

In prior art, usually use traditional sweep generator to be measured mobile communication signal, obtain the frequency sweep data, for the important evidence of communication network condition evaluation and optimization.The frequency sweep audio data that measures of tradition sweep generator can the reflected signal coverage condition, is not subject to producer, device-restrictive, is not subject to parameter influence; Sweep check can not take telecommunication system resources as operational trials, and tests easyly, is one of important technical of analyzing of current wireless network.

But, the wireless signal that the tradition sweep generator only can be measured the BCCH frequency covers situation, incoming level and the C/I that can measure the BCCH frequency measure, can obtain GPS positional information and Measuring Time information simultaneously, the tradition sweep frequency technique can't the TCH frequency relevant parameter of Validity Test except the BCCH frequency, normally with the sweep check of BCCH frequency, the TCH frequency of same cells is carried out to the Approximate Equivalent analysis in prior art, concrete:

1, traditional sweep generator can only carry out level measurement to the BCCH frequency, can't measure incoming level, the end of all carrier frequency that comprise the TCH frequency and make an uproar and C/I.

2, traditional sweep generator can only be measured and be decoded for the BCCH channel, and the BCCH frequency is the full power emission, from the TCH frequency, is different; And, for the TCH frequency, have the factors such as sudden and distributional difference of frequency hopping, DTX and power control, traffic; And the multiplexing density of BCCH frequency and TCH frequency is different, the end level of making an uproar of two class carrier frequency must be different.Different test zones (grid) in community, must there be larger difference in received power and the C/I of BCCH and TCH carrier wave.

3, traditional sweep generator can't be distinguished and be measured the co-channel interference signal from different districts, so can't accurately locate be disturbed community, interference source community and be disturbed frequency.This is the maximum technical bottleneck that current wireless network becomes more meticulous in analyzing, and causes the many serious problem of co-channel interference existed in existing network to locate in time and to solve.

Based on the problems referred to above, there are a lot of restrictions in traditional sweep frequency technique for the analysis of wireless network architecture, and this has become a key technology bottleneck of the further fine optimization of current wireless network.Must explore new measuring technique and analytical method, radio network problems be carried out to the qualitative and accurate quantification analysis of more deep science, and then obtain optimal solution more accurately, fundamentally improve the overall performance of cellular radio.

Summary of the invention

In view of the above problems, the embodiment of the present invention provides a kind of signal monitoring and optimization method, system, a kind of new signal optimizing technology has been proposed, the overlapping covering frequency of the road obtained by accurate Calculation number, road receive index and road frequency multiplexing coefficient value, overcome subjectivity, inaccuracy and uncertainty that basic traditional B CCH frequency sweep measurement equivalence TCH frequency is measured, thus the combination property of the objective and accurate assessment wireless network of energy.

The embodiment of the present invention has adopted following technical scheme:

One embodiment of the invention provides a kind of signal monitoring and optimization method, and described method comprises:

To select test segment and carry out rasterizing;

Each grid to selected test segment carries out frequency sweep, real time record frequency sweep data;

Each grid is carried out respectively: according to road structure index and/or the road frequency multiplexing coefficient of each frequency in frequency sweep data computation grid;

Described road structure index and road frequency multiplexing coefficient are monitored in real time, when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

Described road structure index and/or road frequency multiplexing coefficient according to each frequency in frequency sweep data computation grid comprises:

In computation grid, business takies time slot, and business is taken to training sequence code received power corresponding to each frequency in the frequency sweep data of time slot and carry out statistical average, obtains the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code;

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, calculate road structure index and/or the road frequency multiplexing coefficient of each frequency.

In described computation grid, business takies time slot and comprises:

Determine border and the central point of each time slot in each frame period;

Determine each time slot in grid according to border and the central point of the time slot obtained, calculate training sequence code mean receiving power and the maximal received power of each time slot;

Calculate the carrier/interface ratio of each time slot according to training sequence code mean receiving power and maximal received power;

Determine that it is that in grid, business takies time slot that carrier/interface ratio is greater than zero time slot.

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, the method for calculating the road structure index of each frequency specifically comprises:

Obtain the difference of maximum mean receiving power that the training sequence code combination is corresponding and mean receiving power lower than preset thresholding, or mean receiving power counts sum higher than whole BCCH and the TCH frequency of power threshold, as the overlapping covering frequency of road number;

Utilize the overlapping covering frequency of road number divided by the available frequency number of theory, obtain the road structure index;

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, the method for calculating the road frequency multiplexing coefficient of each frequency specifically comprises:

According to training sequence code number of combinations in the current grid of BCC data acquisition sent in common down channel, obtain for the corresponding training sequence code number of combinations of the overlapping covering frequency of each road, as overlapping covering carrier frequency transceiver T RX number;

Utilize overlapping covering TRX number divided by the overlapping covering frequency of road number, obtain the road frequency multiplexing coefficient.

Described method also comprises:

For each frequency, the shared different training sequence number of codes according to the current frequency of BCC data acquisition sent in common down channel, as the multiplexing density of the single-frequency point of each frequency;

The multiplexing density of the single-frequency point of described each frequency is monitored in real time, when the multiplexing density of described single-frequency point surpasses the 5th preset value, carried out early warning; When the multiplexing density of described single-frequency point surpasses the 6th preset value, signal is optimized to processing.

The computational methods of the training sequence code mean receiving power of each time slot comprise:

Obtain current time slots and receive the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals;

Calculate the mean receiving power of current time slots according to the power sequence of sinusoidal baseband signal I and cosine baseband signal Q;

The computational methods of the average carrier/interface ratio of each time slot comprise:

Calculate the difference of this time slot training sequence code maximal received power and this time slot mean receiving power;

Utilize this time slot training sequence code maximal received power divided by described difference, obtain the average carrier/interface ratio of this frequency;

The computational methods of each time slot training sequence code maximal received power comprise:

Obtain the received power peak value of each time slot in each frequency frame period;

For each received power peak value, carry out respectively: point centered by the current time of received power peak value value, calculate the maximum of each training sequence code received power of this power peak in Preset Time before and after this central point, as training sequence code maximal received power in this time slot.

Describedly obtain that current time slots receives the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals is specially:

I _S(SLOT _v,t-kT)={I _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

Q _S(SLOT _v,t-kT)={Q _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

The mean receiving power that the described power sequence according to sinusoidal baseband signal I and cosine baseband signal Q calculates this time slot is specially:

$\stackrel{\‾}{P}({\mathrm{SLOT}}_v,t-\mathrm{kT})=\frac{1}{N}(\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{\left|I_S({\mathrm{SLOT}}_v,n,t-\mathrm{kT})\right|}^2+\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{\left|Q_S({\mathrm{SLOT}}_v,n,t-\mathrm{kT})\right|}^2)$

The computational methods of the average carrier/interface ratio of described each time slot are specially:

$\mathrm{CtoI}({\mathrm{SLOT}}_v,t-\mathrm{kT})=10\lg \frac{P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})}{\stackrel{\‾}{P}({\mathrm{SLOT}}_v,t-\mathrm{kT})-P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})}$

Point centered by the described value of the current time by the received power peak value, the maximum of each training sequence code received power of this power peak of calculating in Preset Time before and after this central point is specially as training sequence code maximal received power in this time slot:

$P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_l,t-\mathrm{kT})=\underset{k=-10}{\overset{10}{\mathrm{MAX}}}\underset{{\mathrm{TSC}}_i,i=0}{\overset{8}{\mathrm{MAX}}}\left[P_{\mathrm{corr}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_m,S_i(t-\mathrm{kT})\right]$

Wherein, t is the test moment, SLOT _umean u time slot in the frame period, TSC _lbe expressed as serviced community CELL _hl the training sequence code TSC distributed, S _imean i power peak in this frame period, t-kT means that k delayer in the delayer group occurs overtime at t-kT constantly.

In addition, the embodiment of the present invention also provides a kind of signal monitoring and optimization system, and described system comprises:

Grid module, carry out rasterizing for selecting test segment;

The frequency sweep module, carry out frequency sweep, real time record frequency sweep data for each grid to selected test segment;

Computing module, for carrying out respectively each grid: according to road structure index and/or the road frequency multiplexing coefficient of each frequency of frequency sweep data computation grid;

Module is optimized in monitoring, for described road structure index and road frequency multiplexing coefficient are monitored in real time, and when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

Described computing module comprises the first computing unit and the second computing unit:

Described the first computing unit, take time slot for the computation grid business, and business is taken to training sequence code received power corresponding to each frequency in the frequency sweep data of time slot and carry out statistical average, obtain the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code;

Described the second computing unit comprises road structure index computing unit and/or frequency multiplexing coefficient computing unit,

Described road structure index computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road structure index of each frequency;

Described frequency multiplexing coefficient computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road frequency multiplexing coefficient of each frequency.

Described road structure index computing unit specifically comprises:

The overlapping covering frequency of road is counted computation subunit, for the difference of obtaining maximum mean receiving power that the training sequence code combination is corresponding and mean receiving power lower than preset thresholding, perhaps mean receiving power is counted sum higher than whole BCCH and the TCH frequency of power threshold, as the overlapping covering frequency of road number;

Road structure index computation subunit, for utilizing the overlapping covering frequency of road number divided by the available frequency number of theory, obtain the road structure index;

Described frequency multiplexing coefficient computing unit comprises:

Overlapping covering carrier frequency TRX counts computation subunit, for training sequence code number of combinations in the current grid of BCC data acquisition sent according to common down channel, obtain for the corresponding training sequence code number of combinations of the overlapping covering frequency of each road, as overlapping covering carrier frequency transceiver T RX number;

Road frequency multiplexing coefficient computation subunit, for utilizing overlapping covering TRX number divided by the overlapping covering frequency of road number, obtain the road frequency multiplexing coefficient.

Visible, the embodiment of the present invention provides a kind of signal monitoring and optimization method, system, a kind of new wireless network architecture assessment technology based on high accuracy Traffic Channel time slot frequency sweep has been proposed, the overlapping covering frequency of the road obtained by accurate Calculation number, road receives index and road frequency multiplexing coefficient value, can objectively respond the combination property of wireless network architecture, overcome the subjectivity that basic traditional B CCH frequency sweep measurement equivalence TCH frequency is measured, inaccuracy and uncertainty, thereby can accurately to signal of communication, carry out monitoring management, and carry out early warning and reasonably optimize and revise according to the actual state to signal, fundamentally improve the overall performance of cellular radio.And, the wireless network architecture assessment technology of this high accuracy Traffic Channel time slot frequency sweep, combination property that not only can objective and accurate assessment wireless network, and can apply crucial community and crucial frequency that the timeslot-level measurement precise positioning of carrier wave causes radio network problems, for adjusting optimizing wireless network structure, provide science to measure accurately and analysis means.

The accompanying drawing explanation

A kind of signal monitoring and optimization method flow chart that Fig. 1 provides for one embodiment of the invention;

The signal monitoring that Fig. 2-1 and Fig. 2-2 provide for the embodiment of the present invention and an instantiation exemplary plot of optimization method;

The delayer group specific implementation exemplary plot that Fig. 3 provides for the embodiment of the present invention;

Border and the center point method flow chart of determining each time slot in each frame period that Fig. 4 provides for the embodiment of the present invention;

Time slot central point and boundary alignment schematic diagram that Fig. 5 provides for the embodiment of the present invention;

A kind of signal monitoring and optimization system structured flowchart that Fig. 6 provides for the embodiment of the present invention.

Embodiment

For making the purpose, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, embodiment of the present invention is described further in detail.

Referring to Fig. 1, the embodiment of the present invention provides a kind of signal monitoring and optimization method, specifically comprises:

S101: will select test segment and carry out rasterizing.

Test route is carried out to rasterizing, such as being a road grid by 50 meters X50 rice regional extents.

S102: each grid to selected test segment carries out frequency sweep, real time record frequency sweep data.

S103: each grid is carried out respectively: according to road structure index and/or the road frequency multiplexing coefficient of each frequency in frequency sweep data computation grid.

Concrete, according to road structure index and/or the road frequency multiplexing coefficient of each frequency in frequency sweep data computation grid, comprise:

In computation grid, business takies time slot, and business is taken to training sequence code received power corresponding to each frequency in the frequency sweep data of time slot and carry out statistical average, obtains the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code;

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, calculate road structure index and/or the road frequency multiplexing coefficient of each frequency.

That is to say, by carrier/interface ratio C/I in a grid > the high accuracy Traffic Channel time slot sweep check data of 0 (being that time slot exists business to take) carry out statistical average by the combination of frequency+training sequence code, draw mean receiving power and the maximum mean receiving power of frequency+each training sequence code combination.As a kind of specific implementation can be:

The signal of table 1 statistics

Wherein, the method that in computation grid, business takies time slot specifically comprises:

Determine border and the central point of each time slot in each frame period;

Determine each time slot in grid according to border and the central point of the time slot obtained, calculate training sequence code mean receiving power and the maximal received power of each time slot;

Calculate the carrier/interface ratio of each time slot according to training sequence code mean receiving power and maximal received power;

Determine that it is that in grid, business takies time slot that carrier/interface ratio is greater than zero time slot.

It should be noted that, each time slot training sequence code maximal received power is different from the maximum mean receiving power implication of each training sequence code combination.Each time slot training sequence code maximal received power is the maximum in each power peak detected for this time slot, and the maximum in the mean receiving power that the maximum mean receiving power of training sequence code combination is corresponding each training sequence code combination of this frequency.

Equally, the training sequence code mean receiving power of each time slot is also different from the mean receiving power implication of each training sequence code combination, the training sequence code mean receiving power of each time slot is to utilize this time slot to receive the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals calculates, and the mean receiving power of training sequence code combination is for the received power of the training sequence code combination that in the frequency sweep data that business taken to time slot, each frequency is corresponding is carried out, statistical average obtains.

It should be noted that in addition, in actual applications, those skilled in the art, also claim that the training sequence code maximal received power is training sequence code maximal correlation received power, i.e. the performance number the highest with this training sequence code degree of association.

Preferably, in the embodiment of the present invention, the mean receiving power of corresponding training sequence code and maximum mean receiving power according to each frequency, the method for calculating the road structure index of each frequency specifically comprises:

Obtain the difference of the maximum mean receiving power of training sequence code and training sequence code mean receiving power lower than preset thresholding, or mean receiving power counts sum higher than whole BCCH and the TCH frequency of power threshold, obtain the overlapping covering frequency of road number.

Utilize the overlapping covering frequency of road number divided by the available frequency number of theory, obtain the road structure index.

In addition, the mean receiving power of corresponding training sequence code and maximum mean receiving power according to each frequency, the method for calculating the road frequency multiplexing coefficient of each frequency specifically comprises:

According to training sequence code number of combinations in the current grid of BCC data acquisition sent in common down channel, obtain for the corresponding training sequence code number of combinations of the overlapping covering frequency of each road, as overlapping covering carrier frequency transceiver T RX number.

Utilize overlapping covering TRX number divided by the overlapping covering frequency of road number, obtain the road frequency multiplexing coefficient.

S104: described road structure index and road frequency multiplexing coefficient are monitored in real time, when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

Application high accuracy Traffic Channel frequency sweep data are carried out structural appraisal, mainly can proceed to the overlapping frequency number of road, the overlapping TRX(carrier frequency of road transceiver) assessments such as number, road structure exponential sum road frequency multiplexing coefficient.Wherein, identical frequency is designated as n the TRX that has co-channel interference when having n different districts of overlapping covering.

Wherein, the overlapping covering frequency number of road=high accuracy Traffic Channel time slot sweep measurement to maximum mean receiving power deduct mean receiving power value lower than in peak signal 35dB (thresholding can arrange) scope, or mean receiving power is at-BCCH+TCH frequency the number of all communities more than 75dBm (thresholding can arrange).

The overlapping covering frequency of road structure index=road number/theoretical available frequency is counted * 100%.

Overlapping covering TRX number=high accuracy Traffic Channel time slot sweep measurement to maximum mean receiving power deduct the value of mean receiving power lower than in peak signal 35dB (thresholding can arrange) scope, perhaps mean receiving power is at-above the frequency of 75dBm (thresholding can arrange), and the training sequence code number of combinations corresponding with each frequency.

The overlapping covering frequency of the overlapping TRX number/road of road frequency multiplexing coefficient=road number.

Apply above-mentioned four network configuration indexs and can assess the structural behaviour of wireless network objective and accurately, such as, road structure index 70% need to carry out early warning, road structure index need to be optimized adjustment 100% the time; The road frequency multiplexing coefficient > needs carried out early warning, the road frequency multiplexing coefficient 1.2 o'clock > needs were optimized adjustment 2 o'clock.

Gsm mobile communication system has defined 9 groups of training sequence codes (TSC), and wherein 8 groups are used for the Zone channel, and one group of transmit signal power for BCCH carrier frequency free timeslot (dummy burst) is filled, shown in following expression.

Training?Bits=

[

0,0,1,0,0,1,0,1,1,1,0,0,0,0,1,0,0,0,1,0,0,1,0,1,1,1;

0,0,1,0,1,1,0,1,1,1,0,1,1,1,1,0,0,0,1,0,1,1,0,1,1,1;

0,1,0,0,0,0,1,1,1,0,1,1,1,0,1,0,0,1,0,0,0,0,1,1,1,0;

0,1,0,0,0,1,1,1,1,0,1,1,0,1,0,0,0,1,0,0,0,1,1,1,1,0;

0,0,0,1,1,0,1,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,1,0,1,1;

0,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,1,0,0,1,1,1,0,1,0;

1,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1;

1,1,1,0,1,1,1,1,0,0,0,1,0,0,1,0,1,1,1,0,1,1,1,1,0,0;

%above8is?for?the?TCH

0,1,1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1

%dummy?burst

];

The lowest order three bit indexes indications Liao Gai communities of the BCC sent in each common down channel (BSIC) have been applied which group in 8 groups of training sequences, training sequence is as known reference signal, channel time domain equilibrium while receiving for each cell signal, to improve the antijamming capability of gsm mobile communication system.Use the descending time slot signal of the different districts of same carrier to be distinguished with different training sequences, this discriminating measurement for interfering signal power between different districts provides efficient technical method.

Based on this, the signal monitoring that the embodiment of the present invention provides and optimization method, also comprise the steps:

For each frequency, the shared different training sequence number of codes according to the current frequency of BCC data acquisition sent in common down channel, as the multiplexing density of the single-frequency point of each frequency;

The multiplexing density of the single-frequency point of described each frequency is monitored in real time, when the multiplexing density of described single-frequency point surpasses the 5th preset value, carried out early warning; When the multiplexing density of described single-frequency point surpasses the 6th preset value, signal is optimized to processing.

That is to say road f _ithe multiplexing density of single-frequency point=identical f _ithe overlapping covering of the road TRX number of different TSC.

And then, can apply the structural behaviour that above-mentioned network configuration index is assessed wireless network objective and accurately, as the road structure index>70% need to carry out early warning, road structure index>need to be optimized adjustment 100% the time; Road f _ithe multiplexing density of unifrequency>needs carried out early warning, road f 1.2 o'clock _ithe multiplexing density of unifrequency>needs were optimized adjustment 2 o'clock.

Described here optimizes and revises, and such as being, the cell signal far away received when the problem highway section is very strong, and it is not good enough that explanation covers rationality, needs to adjust antenna, controls area covered; The interference that is subject near community when the problem highway section is stronger, illustrates that frequency planning is unreasonable, need carry out frequency optimization.

Illustrate, as shown in Fig. 2-1 and Fig. 2-2, the network configuration correlation analysis index of utilizing the embodiment of the present invention to propose has been carried out analysis verification in a certain area, analyzes efficiently and accurately.In 6, the 7 grades of poor interference problem of matter highway sections shown in Fig. 2-1, corresponding road structure index > more than 90%, the road frequency multiplexing coefficient > more than 2, the complicated network structure, cause interference problem obvious.

When being scanned, each carrier frequency time-division slot can effectively distinguish idle condition and the service condition of this time slot: in the idle condition of time slot, the related power C/I that all training serial codes are corresponding<0, the reflection of time slot power now be to make an uproar the end of wireless network, so provide more fine-grained accurate measurement data source and new analytical method in the end assessment more accurately of making an uproar that is measured as of idle condition time slot; Business seizure condition at time slot, the related power C/I that all training serial codes are corresponding > 0, can judge that this carrier power is from Serving cell or interfered cell according to training sequence code, for the covering of carrier wave and interference problem location provide most scientific objectively accurate measurement data.

Carry out the wireless network architecture analysis by high accuracy Traffic Channel frequency sweep data and can overcome the inaccuracy of measuring with traditional B CCH carrier frequency measurement equivalence TCH frequency, the measurement of all BCCH+TCH frequency+training sequence codes (homogenous frequency signal is distinguished different districts with training sequence code) can be provided.

Tradition sweep measurement BCCH is subject to 1.88 seconds system message cycles (8 51 multiframe periods) restriction during frequency, and test specimens is counted few.High accuracy Traffic Channel frequency sweep is not subject to the system message cycle limit, to each frequency, all can carry out efficient sufficient timeslot-level measurement sampling.

Above-mentioned discussion shows, high accuracy Traffic Channel frequency sweep data have overcome traditional B CCH frequency and measured the deficiencies such as inaccuracy that equivalent TCH frequency measures, subjectivity, insufficiency; And high accuracy Traffic Channel frequency sweep data can reflect that the traffic in wireless network architecture distributes and the traffic correlation of minizone objective and accurately, can reflect that each community each channel time slot C/I(is service feature), be the hypothesis testing data source of carrying out the wireless network architecture analysis.

On the basis to the network configuration objective analysis, in conjunction with covering analyzing and the interference analysis based on high accuracy Traffic Channel frequency sweep, network is carried out to comprehensive optimization, can excavate the maximum potentiality energy of wireless network.

Visible, the embodiment of the present invention provides a kind of signal monitoring and optimization method, a kind of new wireless network architecture assessment technology based on high accuracy Traffic Channel time slot frequency sweep has been proposed, the overlapping covering frequency of the road obtained by accurate Calculation number, road receives index and road frequency multiplexing coefficient value, can objectively respond the combination property of wireless network architecture, overcome the subjectivity that basic traditional B CCH frequency sweep measurement equivalence TCH frequency is measured, inaccuracy and uncertainty, thereby can accurately to signal of communication, carry out monitoring management, and carry out early warning and reasonably optimize and revise according to the actual state to signal, fundamentally improve the overall performance of cellular radio.And, the wireless network architecture assessment technology of this high accuracy Traffic Channel time slot frequency sweep, combination property that not only can objective and accurate assessment wireless network, and can apply crucial community and crucial frequency that the timeslot-level measurement precise positioning of carrier wave causes radio network problems, for adjusting optimizing wireless network structure, provide science to measure accurately and analysis means.

In the embodiment of the present invention, the computational methods of the training sequence code mean receiving power of each time slot comprise:

Obtain current time slots and receive the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals;

Calculate the mean receiving power of each time slot according to the power sequence of sinusoidal baseband signal I and cosine baseband signal Q.

Be specially:

I _S(SLOT _v,t-kT)={I _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

Q _S(SLOT _v,t-kT)={Q _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

The computational methods of the average carrier/interface ratio of each time slot specifically comprise:

Calculate the difference of this frequency training sequence code maximal received power and this time slot mean receiving power;

Utilize this time slot training sequence code maximal received power divided by described difference, obtain the average carrier/interface ratio of this frequency.Be specially:

$\mathrm{CtoI}({\mathrm{SLOT}}_v,t-\mathrm{kT})=10\lg \frac{P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})}{\stackrel{\&OverBar;}{P}({\mathrm{SLOT}}_v,t-\mathrm{kT})-P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})}$

The computational methods of each time slot training sequence code maximal received power comprise:

Obtain the received power peak value of each time slot in each frequency frame period;

For each received power peak value, carry out respectively: point centered by the current time of received power peak value value, calculate the maximum of each training sequence code received power of this power peak in Preset Time before and after this central point, as training sequence code maximal received power in this time slot.

Point centered by the above-mentioned value of the current time by the received power peak value, calculate the maximum of each training sequence code received power of this power peak in Preset Time before and after this central point, as training sequence code maximal received power in this time slot, comprise following 2 sub-steps:

Point centered by the current time of current time slots power peak value, arrange the delayer group signal power in Preset Time before and after this central point monitored;

Record one by one each TSC performance number corresponding to the overtime current demand signal of each delayer in this delayer group, and calculate each delayer maximum TSC performance number corresponding to current demand signal when overtime.

Through repeatedly a large amount of test repeatedly of inventor, as a preferred scheme, the delayer group comprises 21 delayers, and the delay value T of each delayer is 1 μ s, and effect compares better.

Concrete, the described delayer group of the embodiment of the present invention also claims when sliding window is parallel to examine the gap survey technology, and the sliding window construction that the delayer group forms is as shown in Figure 3.

Parallel slide windows mouth shown in Fig. 3 is comprised of 21 delayers, and each delayer time delay cycle is T=1us, and whole sliding window length is expanded respectively 10us 21us altogether with time slot central point left and right.Sampled signal after time delay and 9 groups of training sequence codes carry out the Parallel correlation detection each time.For the measurement of a time slot, altogether need to carry out to train the most by force the parallel detection of serial codes related power 21 times.

In this step, preferably, to each time delay, adopt 9 groups of training sequence code TSC of signal to carry out parallel detection, adopt the TSC maximum power to detect, can detect this time slot whether exist business to take and time slot when business takies, the training sequence code that the maximal correlation power signal is corresponding, be cell signal or interference etc. with judgement, and the measurement of movable signal relevant parameter can be provided preferably.

Because the beginning 5bit in the training sequence of each group 26bit and afterbody 5bit carry out cycle expansion and obtain by being positioned at center point 16bit original series, so, while with 16 original bitDui community transmission time slot signals, carrying out coherent detection, in the both sides of correlation peak, 50 points can respectively occur.This also provides a kind of concrete screening conditions for the judgement power peak.

In the embodiment of the present invention, point centered by the current time of received power peak value value, calculate the maximum of each training sequence code received power of this power peak in Preset Time before and after this central point, be specially as training sequence code maximal received power in this time slot:

$P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_l,t-\mathrm{kT})=\underset{k=-10}{\overset{10}{\mathrm{MAX}}}\underset{{\mathrm{TSC}}_i,i=0}{\overset{8}{\mathrm{MAX}}}\left[P_{\mathrm{corr}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_m,S_i(t-\mathrm{kT})\right]$

T is the test moment, SLOT _umean u time slot in the frame period, TSCl is expressed as serviced community CELL _hl the training sequence code TSC distributed, S _imean i power peak in this frame period, t-kT means that k delayer in the delayer group occurs overtime at t-kT constantly.

Method for the above-mentioned border of determining each time slot in each frame period and central point is specifically shown in Figure 4, mainly comprises:

S401: for a selected frame of a frequency, in the cycle, obtain the power peak of signal in this frame period.

It should be noted that, the embodiment of the present invention, in order to determine accurate border and the central point of each time slot, can be selected at random a frame period and carry out this step S401.

Simultaneously, in the process of carrying out this step S401, can also record the power data of whole signals in this frame period, in order to for subsequent step, signal power is analyzed to use.

Concrete, the power peak that obtains signal in this frame period comprises following 3 sub-steps:

The monitoring delayer is set signal power is monitored, described delay value is less than slot cycle.

When time delay is overtime, record the current signal power value monitored.

In the signal power value monitored, obtain power peak within this frame period.

Because the signal power value monitored, be not all peak value, in the signal power value monitored, need to select therein to belong to the part of peak value within this frame period.

It should be noted that, the delay value of the delayer used in this step at least is less than a slot cycle, because generally, should have peak value in a slot cycle and occur, in actual applications.It is less that delay value arranges, the power peak obtained is more accurate, can avoid omitting, but what arrange is too little, easily cause needing data volume to be processed to increase, Efficiency Decreasing, therefore, in actual applications, those skilled in the art can rationally arrange delay value according to concrete application scenarios and demand.

S402: at each power peak place, point centered by the current time of power peak value calculates accurate power peak, and records this accurate power peak place time value before and after this central point in Preset Time.

Concrete, point centered by the current time of power peak value calculates accurate power peak and comprises following 3 sub-steps before and after this central point in Preset Time:

The delayer group is set is monitored signal power in Preset Time before and after this central point.

Record one by one the overtime current demand signal performance number of each delayer in this delayer group.

Calculate the maximum signal power value in the signal power value of above-mentioned record, using this maximum signal power value as accurate power peak.

The delayer group comprises a plurality of delayers, suppose to comprise N delayer (N is odd number usually), the delay value of each delayer is made as time t1, can measure point centered by the current time of function peak value value, and before and after this central point, preset time is to calculate accurate power peak in N*t1.Concrete, in the delayer group, using middle delayer as center, both sides arrange (N-1)/2 delayer forwards, backwards respectively, before the current time of the function peak value as central point value, (N-1) * t1/2 is during the moment, top delayer is overtime, record the current demand signal performance number of this delayer when overtime, the like, when second delayer is overtime, record again the current demand signal performance number of second delayer when overtime, until last delayer when overtime, is recorded the current demand signal performance number of last delayer when overtime.

Above-mentioned power peak is specially the power peak of training sequence code TSC.

Above-mentionedly record one by one the overtime current demand signal performance number of each delayer in this delayer group and be specially: for each delayer in the delayer group, when delayer is overtime, record each TSC performance number that current demand signal is corresponding, and calculate maximum TSC performance number.

In the signal power value of above-mentioned record, calculate the maximum signal power value, this maximum signal power value is specially as accurate power peak: calculate the maximum in the maximum TSC performance number that each delayer obtains when overtime, as accurate power peak.

Here the delayer group is preferred, also can select delayer group shown in above-mentioned Fig. 2, comprises 21 delayers, and the delay value T of each delayer is 1 μ s, and effect compares better.Repeat no more herein.

Concrete, point centered by the above-mentioned value of the current time by power peak calculates accurate power peak before and after this central point in Preset Time, and the specific implementation algorithm is:

$P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_l,t-\mathrm{kT})=\underset{k=-10}{\overset{10}{\mathrm{MAX}}}\underset{{\mathrm{TSC}}_i,i=0}{\overset{8}{\mathrm{MAX}}}\left[P_{\mathrm{corr}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_m,S_i(t-\mathrm{kT})\right]$

Wherein, t is the test moment, SLOT _umean u time slot in the frame period, TSC _lbe expressed as l the training sequence code TSC that serviced community CELLh distributes, S _imean i power peak in this frame period, t-kT means that k delayer in the delayer group occurs overtime at t-kT constantly.

That is to say, at test moment t, nominative testing zone (grid) g _qin, carrier frequency f _psome sequential SLOT _u(a u interior time slot of frame period), serviced community CELL _hthe business of (h community in wireless network) takies, and can detect community CELL _hthe training sequence code TSC distributed _lthe maximal correlation power P of (l training sequence code) _corrMAX(SLOT _u, TSC _l, t-kT).MAX () symbol wherein means to get the maximum of array element in bracket.

S403: in above-mentioned each accurate power peak calculated, calculate maximum precisely power peak.

Concrete, this step is using the maximum in each accurate power peak as the accurate power peak of maximum.

Power peak is specially the power peak of training sequence code TSC, the delayer group comprises 21 delayers, and when the delay value T of each delayer is 1 μ s, this step is in above-mentioned each accurate power peak calculated, calculate maximum precisely related power peak value, the specific implementation algorithm is:

$P_{\mathrm{corrMAX}}({\mathrm{FLAM}}_w,{\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})=\underset{{\mathrm{SLOT}}_u,u=0}{\overset{7}{\mathrm{MAX}}}\underset{k=-10}{\overset{10}{\mathrm{MAX}}}\underset{{\mathrm{TSC}}_i,i=0}{\overset{8}{\mathrm{MAX}}}\left[P_{\mathrm{corr}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_m,S_i(t-\mathrm{kT})\right].$

That is to say, 0-7 in totally 8 time slot SLOT, obtains maximum training sequence code TSC performance number, P _corrMAX(FLAM _w, SLOT _v, TSC _l, t-kT) meaning that in a frame period w, the maximum precisely power peak of training sequence code TSC is l training sequence code of v time slot in this frame, the accurate power peak current time of this maximum is t-kT, wherein t is the testing time.

S404: using the central point of the accurate power peak of described maximum place time value as its place time slot, and to take this time slot central point be benchmark, carry out left and right and expand, determine successively border and the central point of each time slot in this frame period, and, the border of each time slot in other each frame period and central point.

Be taken at the time slot central point that maximum training sequence code related power is corresponding in 8 slot cycles of a frame and detect time slot central point time reference of time slot analysis in frame period for this, and take each time slot center and the time slot border of this time benchmark in a frame is carried out on basis and expand division.As shown in Figure 5, SLOT ₃the training sequence code related power received is the strongest, usings its correlation peak constantly as SLOT ₃time slot central point benchmark carry out the location of all the other time slot central points and boundary of time slot in the whole frame period and expand.The maximum training sequence code that carries out on this basis each time slot detects the correlation peak power detection.

S405: border and central point according to time slot in each frame period obtained, detected signal.

Therefore, as preferably, in the embodiment of the present invention, at first accurately determine border and the central point of each time slot in each frame period, think that the calculating of subsequent power and carrier/interface ratio provides basis, so that the carrier/interface ratio calculated is more accurate.

In addition, referring to Fig. 6, the embodiment of the present invention provides a kind of signal monitoring and optimization system, and system specifically comprises:

Grid module 601, carry out rasterizing for selecting test segment;

Frequency sweep module 602, carry out frequency sweep, real time record frequency sweep data for each grid to selected test segment;

Computing module 603, for carrying out respectively each grid: according to road structure index and/or the road frequency multiplexing coefficient of each frequency of frequency sweep data computation grid;

Module 604 is optimized in monitoring, for described road structure index and road frequency multiplexing coefficient are monitored in real time, and when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

Wherein, described computing module comprises the first computing unit and the second computing unit:

Described the first computing unit, take time slot for the computation grid business, and the received power that business is taken to the training sequence code combination that in the frequency sweep data of time slot, each frequency is corresponding carries out statistical average, obtain the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code.

That is to say, take time slot for the computation grid business, and respectively business is taken to the be combined as objects of statistics of the frequency sweep data of time slot with frequency and training sequence code, each training sequence code received power (being the value that the maximum mean receiving power of training sequence code deducts the training sequence code mean receiving power) corresponding to each frequency measured is less than to appointed threshold (as lower than this test grid g _qstrong cohesiveness is received in level 35dB scope), or the training sequence code mean receiving power is greater than power threshold (as-75dBm), carries out statistical average, obtains mean receiving power and the maximum mean receiving power of corresponding each training sequence code combination of each frequency.

The second computing unit comprises road structure index computing unit and/or frequency multiplexing coefficient computing unit.

Described road structure index computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road structure index of each frequency.

Described frequency multiplexing coefficient computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road frequency multiplexing coefficient of each frequency.

Concrete, road structure index RSI (g _q) computing unit, be less than appointed threshold (as lower than this test grid g for the mean receiving power of the training sequence code corresponding according to each frequency (being the value that the maximum mean receiving power of training sequence code deducts the training sequence code mean receiving power) _qstrong cohesiveness is received in level 35dB scope), or the training sequence code mean receiving power is greater than power threshold (as-75dBm), and average carrier interference ratio C/I>all frequency numbers of 0, the overlapping covering frequency of road is counted N _{f_overlap}(g _q), calculate nominative testing grid g _qinside respectively test the road structure index of grid.Computing formula is as follows:

RSI(g _q)＝N _{F_overlap}(g _q)/M×100%

Wherein, M is theoretical available frequency sum.

Described frequency multiplexing coefficient ρ _f(g _q) computing unit, for being less than appointed threshold according to mean receiving power (being the value that the maximum mean receiving power of training sequence code deducts the training sequence code mean receiving power) (as lower than this test grid g _qstrong cohesiveness is received in level 35dB scope), or the training sequence code mean receiving power is greater than power threshold (as-75dBm), and average carrier interference ratio C/I>training sequence code various combination that 0 each frequency is corresponding counts N _{tRX_overlap}and the overlapping covering frequency of road is counted N _{f_overlap}(g _q), calculate nominative testing grid g _qinterior road frequency multiplexing coefficient.Computing formula is as follows:

ρ _F(g _q)＝N _{TRX_overlap}(g _q)/N _{F_overlap}(g _q)

Described road structure index computing unit specifically comprises:

The overlapping covering frequency of road is counted computation subunit, for the difference of obtaining maximum mean receiving power that the training sequence code combination is corresponding and mean receiving power lower than preset thresholding, perhaps mean receiving power is counted sum higher than whole BCCH and the TCH frequency of power threshold, as the overlapping covering frequency of road number.Concrete, obtain average carrier/interface ratio in C/I>0, and mean receiving power higher than power threshold (as with this test grid g _qstrong cohesiveness is received in level 35dB scope, or be greater than-75dBm) whole BCCH and TCH frequency count sum, obtain the overlapping covering frequency of road and count N _{f_overlap}(g _q).

With, road structure index computation subunit, count N for utilizing the overlapping covering frequency of road _{f_overlap}(g _q) count M divided by the available frequency of theory, obtain road structure index RSI (g _q).

In addition, described frequency multiplexing coefficient computing unit comprises:

Overlapping covering carrier frequency TRX counts computation subunit, for being less than appointed threshold according to mean receiving power (being the value that the maximum mean receiving power of training sequence code deducts the training sequence code mean receiving power) (as lower than this test grid g _qstrong cohesiveness is received in level 35dB scope), or the training sequence code mean receiving power is greater than power threshold (as-75dBm), and average carrier interference ratio C/I 0 condition calculates each frequency and the training sequence code various combination is counted N _{tRX_overlap}it is overlapping covering carrier frequency transceiver T RX number.

With, road frequency multiplexing coefficient computation subunit, count N for utilizing overlapping covering TRX _{tRX_overlap}count N divided by the overlapping covering frequency of road _{f_overlap}(g _q), obtain nominative testing grid g _qinterior road frequency multiplexing coefficient.

Apply every network configuration index defined above and can assess the structural behaviour of wireless network objective and accurately, as the road structure index 70% need to carry out early warning, road structure index need to be optimized adjustment 100% the time; The road frequency multiplexing coefficient > needs carried out early warning, the road frequency multiplexing coefficient 1.2 o'clock > needs were optimized adjustment 2 o'clock.It should be noted that, the modules in system embodiment of the present invention or the operation principle of submodule and processing procedure can, referring to the associated description in embodiment of the method shown in above-mentioned Fig. 1-Fig. 5, repeat no more herein.

Visible, the embodiment of the present invention provides a kind of signal monitoring and optimization system, a kind of new wireless network architecture assessment technology based on high accuracy Traffic Channel time slot frequency sweep has been proposed, the overlapping covering frequency of the road obtained by accurate Calculation number, road receives index and road frequency multiplexing coefficient value, can objectively respond the combination property of wireless network architecture, overcome the subjectivity that basic traditional B CCH frequency sweep measurement equivalence TCH frequency is measured, inaccuracy and uncertainty, thereby can accurately to signal of communication, carry out monitoring management, and carry out early warning and reasonably optimize and revise according to the actual state to signal, fundamentally improve the overall performance of cellular radio.And, the wireless network architecture assessment technology of this high accuracy Traffic Channel time slot frequency sweep, combination property that not only can objective and accurate assessment wireless network, and can apply crucial community and crucial frequency that the timeslot-level measurement precise positioning of carrier wave causes radio network problems, for adjusting optimizing wireless network structure, provide science to measure accurately and analysis means.

For the ease of the clear technical scheme of describing the embodiment of the present invention, in inventive embodiment, adopted the printed words such as " first ", " second " to be distinguished the essentially identical identical entry of function and efficacy or similar item, it will be appreciated by those skilled in the art that the printed words such as " first ", " second " are not limited quantity and execution order.

One of ordinary skill in the art will appreciate that, realize that all or part of step in above-described embodiment method is to come the hardware that instruction is relevant to complete by program, described program can be stored in a computer read/write memory medium, this program is when carrying out, comprise the steps: (step of method), described storage medium, as: ROM/RAM, magnetic disc, CD etc.

The foregoing is only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.All any modifications of doing within the spirit and principles in the present invention, be equal to replacement, improvement etc., all be included in protection scope of the present invention.

Claims (10)

1. a signal monitoring and optimization method, is characterized in that, described method comprises:

To select test segment and carry out rasterizing;

Each grid to selected test segment carries out frequency sweep, real time record frequency sweep data;

Each grid is carried out respectively: according to road structure index and/or the road frequency multiplexing coefficient of each frequency in frequency sweep data computation grid;

Described road structure index and road frequency multiplexing coefficient are monitored in real time, when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

2. signal monitoring according to claim 1 and optimization method, is characterized in that, described road structure index and/or road frequency multiplexing coefficient according to each frequency in frequency sweep data computation grid comprises:

In computation grid, business takies time slot, and the received power that business is taken to the training sequence code combination that in the frequency sweep data of time slot, each frequency is corresponding carries out statistical average, obtains the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code;

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, calculate road structure index and/or the road frequency multiplexing coefficient of each frequency.

3. signal monitoring according to claim 2 and optimization method, is characterized in that, in described computation grid, business takies time slot and comprises:

Determine border and the central point of each time slot in each frame period;

Determine each time slot in grid according to border and the central point of the time slot obtained, calculate training sequence code mean receiving power and the maximal received power of each time slot;

Calculate the carrier/interface ratio of each time slot according to training sequence code mean receiving power and maximal received power;

Determine that it is that in grid, business takies time slot that carrier/interface ratio is greater than zero time slot.

4. signal monitoring according to claim 2 and optimization method, is characterized in that, the mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, and the method for calculating the road structure index of each frequency specifically comprises:

Obtain the difference of maximum mean receiving power that the training sequence code combination is corresponding and mean receiving power lower than preset thresholding, or mean receiving power counts sum higher than whole BCCH and the TCH frequency of power threshold, as the overlapping covering frequency of road number;

Utilize the overlapping covering frequency of road number divided by the available frequency number of theory, obtain the road structure index;

The mean receiving power of corresponding training sequence code combination and maximum mean receiving power according to each frequency, the method for calculating the road frequency multiplexing coefficient of each frequency specifically comprises:

According to training sequence code number of combinations in the current grid of BCC data acquisition sent in common down channel, obtain for the corresponding training sequence code number of combinations of the overlapping covering frequency of each road, as overlapping covering carrier frequency transceiver T RX number;

Utilize overlapping covering TRX number divided by the overlapping covering frequency of road number, obtain the road frequency multiplexing coefficient.

5. signal monitoring according to claim 1 and optimization method, is characterized in that, described method also comprises:

For each frequency, the shared different training sequence number of codes according to the current frequency of BCC data acquisition sent in common down channel, as the multiplexing density of the single-frequency point of each frequency;

The multiplexing density of the single-frequency point of described each frequency is monitored in real time, when the multiplexing density of described single-frequency point surpasses the 5th preset value, carried out early warning; When the multiplexing density of described single-frequency point surpasses the 6th preset value, signal is optimized to processing.

6. signal monitoring according to claim 3 and optimization method, is characterized in that, the computational methods of the training sequence code mean receiving power of each time slot comprise:

Obtain current time slots and receive the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals;

Calculate the mean receiving power of current time slots according to the power sequence of sinusoidal baseband signal I and cosine baseband signal Q;

The computational methods of the average carrier/interface ratio of each time slot comprise:

Calculate the difference of this time slot training sequence code maximal received power and this time slot mean receiving power;

Utilize this time slot training sequence code maximal received power divided by described difference, obtain the average carrier/interface ratio of this frequency;

The computational methods of each time slot training sequence code maximal received power comprise:

Obtain the received power peak value of each time slot in each frequency frame period;

For each received power peak value, carry out respectively: point centered by the current time of received power peak value value, calculate the maximum of each training sequence code received power of this power peak in Preset Time before and after this central point, as training sequence code maximal received power in this time slot.

7. signal monitoring according to claim 6 and optimization method, is characterized in that,

Describedly obtain that current time slots receives the sinusoidal baseband signal I of sampled signal and the power sequence of cosine baseband signal Q two paths of signals is specially:

I _S(SLOT _v,t-kT)={I _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

Q _S(SLOT _v,t-kT)={Q _S(SLOT _v,n,t-kT),n=0,1,2,...,N-1}

The mean receiving power that the described power sequence according to sinusoidal baseband signal I and cosine baseband signal Q calculates this time slot is specially:

$\stackrel{\&OverBar;}{P}(\mathrm{SLO}{T}_v,t-\mathrm{kT})=\frac{1}{N}(\underset{n=0}{\overset{N-1}{\mathrm{\&Sigma;}}}{\left|I_S({\mathrm{SLOT}}_v,n,t-\mathrm{kT})\right|}^2+\underset{n=0}{\overset{N-1}{\mathrm{\&Sigma;}}}{\left|Q_S({\mathrm{SLOT}}_v,n,t-\mathrm{kT})\right|}^2)$

The computational methods of the average carrier/interface ratio of described each time slot are specially:

$\mathrm{CtoI}({\mathrm{SLOT}}_v,t-\mathrm{kT})=101g\frac{P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l,t-\mathrm{kT})}{\stackrel{\&OverBar;}{P}({\mathrm{SLOT}}_v,t-\mathrm{kT})-P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_v,{\mathrm{TSC}}_l\text{,t-kT})}$

Point centered by the described value of the current time by the received power peak value, the maximum of each training sequence code received power of this power peak of calculating in Preset Time before and after this central point is specially as training sequence code maximal received power in this time slot:

$P_{\mathrm{corrMAX}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_l,t-\mathrm{kT})=\underset{k=-10}{\overset{10}{\mathrm{MAX}}}\underset{{\mathrm{TSC}}_i,i=0}{\overset{8}{\mathrm{MAX}}}\left[P_{\mathrm{corr}}({\mathrm{SLOT}}_u,{\mathrm{TSC}}_m,S_i(t-\mathrm{kT})\right]$

Wherein, t is the test moment, SLOT _umean u time slot in the frame period, TSC _lbe expressed as serviced community CELL _hl the training sequence code TSC distributed, S _imean i power peak in this frame period, t-kT means that k delayer in the delayer group occurs overtime at t-kT constantly.

8. a signal monitoring and optimization system, is characterized in that, described system comprises:

Grid module, carry out rasterizing for selecting test segment;

The frequency sweep module, carry out frequency sweep, real time record frequency sweep data for each grid to selected test segment;

Computing module, for carrying out respectively each grid: according to road structure index and/or the road frequency multiplexing coefficient of each frequency of frequency sweep data computation grid;

Module is optimized in monitoring, for described road structure index and road frequency multiplexing coefficient are monitored in real time, and when the road structure index surpasses the first preset value, and/or, when the road frequency multiplexing coefficient is greater than the second preset value, carry out early warning; When the road structure index surpasses the 3rd preset value, and/or, when the road frequency multiplexing coefficient is greater than the 4th preset value, signal is optimized to processing.

9. signal monitoring according to claim 8 and optimization system, is characterized in that, described computing module comprises the first computing unit and the second computing unit:

Described the first computing unit, take time slot for the computation grid business, and the received power that business is taken to the training sequence code combination that in the frequency sweep data of time slot, each frequency is corresponding carries out statistical average, obtain the mean receiving power of each training sequence code combination that each frequency is corresponding; And, obtain the maximum of above-mentioned each mean receiving power, as the maximum mean receiving power of training sequence code;

Described the second computing unit comprises road structure index computing unit and/or frequency multiplexing coefficient computing unit,

Described road structure index computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road structure index of each frequency;

Described frequency multiplexing coefficient computing unit, for mean receiving power and the maximum mean receiving power of the training sequence code combination corresponding according to each frequency, calculate the road frequency multiplexing coefficient of each frequency.

10. signal monitoring according to claim 9 and optimization system, is characterized in that, described road structure index computing unit specifically comprises:

The overlapping covering frequency of road is counted computation subunit, for the difference of obtaining maximum mean receiving power that the training sequence code combination is corresponding and mean receiving power lower than preset thresholding, perhaps mean receiving power is counted sum higher than whole BCCH and the TCH frequency of power threshold, as the overlapping covering frequency of road number;

Road structure index computation subunit, for utilizing the overlapping covering frequency of road number divided by the available frequency number of theory, obtain the road structure index;

Described frequency multiplexing coefficient computing unit comprises:

Overlapping covering carrier frequency TRX counts computation subunit, for training sequence code number of combinations in the current grid of BCC data acquisition sent according to common down channel, obtain for the corresponding training sequence code number of combinations of the overlapping covering frequency of each road, as overlapping covering carrier frequency transceiver T RX number;

Road frequency multiplexing coefficient computation subunit, for utilizing overlapping covering TRX number divided by the overlapping covering frequency of road number, obtain the road frequency multiplexing coefficient.

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