CN1866780A - Optimization method for network uplink load control - Google Patents

Abstract

The invention discloses a network ascending load control majorization method, which comprises the following steps: estimating load of subdistrict and impeding subdistrict in network; accounting the ratio of the estimated load value of subdistrict and impeding subdistrict; getting impeding burst factor in network; using impeding burst factor to optimize. The invention avoids the interference from artificial transmission model, which improves the capacitance and stability of system network.

Description

A kind of optimization method of network uplink load control

Technical field

The present invention relates to wireless communication technology field, relate in particular to a kind of optimization method of network uplink load control.

Background technology

At present, in the cellular radio communication network that adopts Wideband Code Division Multiple Access (WCDMA) (WCDMA) technology and code division multiple access (CDMA) technology, the cellular network frequency duplex factor as one is 1, whole cellular network can adopt same carrier frequency, any one base station can receive other neighbor cells user's signal when receiving this community user signal.Adjacent area user's received signal is a kind of strong jamming to base station this community user uplink demodulation, and along with progressively enhancing is disturbed in the adjacent area, the capacity of this sub-district can progressively reduce.

The capacity of this sub-district and load have certain corresponding relation, often characterize by load, and up load definition based on throughput is:

${\mathrm{\η}}_{\mathrm{UL}}=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{L}_j=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\frac{1}{1+\frac{W}{R_j\·{\left(\mathrm{EbvsN}0\right)}_j\·v_j}}$

Wherein i is the adjacent area interference factor, is defined as this sub-district received signal gross power I _OwnWith adjacent sub-district received signal gross power I _OthRatio, W is system bandwidth 3.84Mbps, R _jBe the message transmission rate of user j, v _jBe activity factor, N is this community user sum, L _jLoad value for user j.

In the computational methods of above-mentioned definition ascending load; can obtain the characteristic of this community user more exactly; but be difficult to obtain adjacent area interference factor in the real network; therefore in the load control of WCDMA; usually can be according to existing emulation empirical value; interference factor i is set at fixing constant the adjacent area; can get 0.6 such as dense city; general city gets 0.4 etc.; the adjacent area interference characteristic according to actual WCDMA wireless network is not provided with, and causes actual ascending load estimation and controls inaccurate.

Use the adjacent area interference factor to carry out in the method for ascending load control in the prior art, obtaining of adjacent area interference factor is based on system simulation model, and the distribution of base station covers according to the regular hexagon of standard as shown in Figure 1,3 sectors, every base station.

Suppose that certain user is distributed in the sub-district of each base station according to uniform mode, in order to embody the difference of different communication environments, as dense city and suburb and rural environment, path loss model need be revised respectively, other community user of this community user gross power and all that receives by the accounting base-station antenna arrives the ratio of the gross power of this base station then, obtains the adjacent area interference factor i under the different communication environments.According to the load and the adjacent area interference factor of this community user, can determine the load state of current area and carry out load control.

The existing adjacent area interference factor i that obtains by emulation can bring bigger evaluated error, and at first the base station distribution of actual wireless network is not the regular hexagon for standard, but coverage distance is uneven; Secondly user's distribution also can not be the even distribution of statistical model, but has in real time with sudden; Propagation model and the actual propagation model used of emulation is far apart once more.

Generally, simulating scenes is all various may scenes abstract statistical models that come out, details in can't the imbody real network, therefore the adjacent area interference factor value i that determines based on emulation can not reflect the adjacent area interference characteristic of actual wireless network really.

If the adjacent area interference factor value i that obtains with emulation carries out the ascending load estimation, may be incorrect because of the adjacent area interference factor, bring bigger evaluated error, it is inaccurate to make load estimate, and finally influence the capacity of WCDMA system cell, cause capacity to descend and user's demodulation performance poor.

Summary of the invention

In view of above-mentioned existing in prior technology problem, the purpose of this invention is to provide a kind of optimization method of network uplink load control, with the control of the ascending load of adjacent area interference factor optimization more accurately.

The objective of the invention is to be achieved through the following technical solutions:

The optimization method of ascending load control in a kind of network comprises:

In network, estimate this cell load and adjacent cell load respectively, and calculate the ratio of the estimated value of the estimated value of adjacent cell load and this cell load, obtain the adjacent area interference factor in the network, utilize the adjacent area interference factor to optimize ascending load control.

Described estimation to this cell load comprises: current each time slot of channel that uses of this community user is carried out real-time signal-to-noise ratio (SNR) estimation, calculate this cell load according to real-time signal-to-noise ratio (SNR) estimation value.

The time interval of sample point is made as 2ms in the described real-time signal-to-noise ratio (SNR) estimation.

Estimation to this cell load comprises:

Estimate the current signal to noise ratio of using channel of this community user;

According to this cell load of signal-to-noise ratio (SNR) estimation.

Described the current signal-to-noise ratio (SNR) estimation of channel of using of this community user is comprised:

Utilize the transformat indicating gage of former frame demodulation to calculate the current power control gain factor β that uses the relative DPCCH of channel (Dedicated Physical Control Channel) of user _{Ch, i}, calculate the current power control yield value β that uses the relative Dedicated Physical Control Channel of each chip in the channel _DPCHC, the signal to noise ratio SIR of measurement Dedicated Physical Control Channel _DPCCH

Signal to noise ratio SIR according to Dedicated Physical Control Channel _DPCCHCalculate the current signal to noise ratio of using channel,

${\mathrm{SIR}}_{\mathrm{ch},i}={\mathrm{SIR}}_{\mathrm{DPCCH}}\·[1+{\left(\frac{{\mathrm{\β}}_{\mathrm{ch},i}}{{\mathrm{\β}}_{\mathrm{DPCHC}}}\right)}^2].$

Dedicated Physical Control Channel wherein is the standard agreement that defines in the 3GPP agreement.

The described load of this sub-district being carried out according to signal to noise ratio is estimated to comprise:

According to the current current load value that uses channel of snr computation user that uses channel,

${\mathrm{\η}}_{j,i}=\frac{{\mathrm{SIR}}_{\mathrm{ch},i}}{1+{\mathrm{SIR}}_{\mathrm{ch},i}};$

According to user's channel type kind, calculate load and summation that every kind of channel type brings successively, obtain the load of user to network cell, ${\mathrm{\η}}_j=\underset{i}{\mathrm{\Σ}}{\mathrm{\η}}_{j,i}=\underset{i}{\mathrm{\Σ}}\frac{{\mathrm{SIR}}_{\mathrm{ch},i}}{1+{\mathrm{SIR}}_{\mathrm{ch},i}};$

Calculate the load that this community user brings according to this community user sum, ${\mathrm{\η}}_{\mathrm{own}}=\underset{j}{\mathrm{\Σ}}{\mathrm{\η}}_j.$

Described adjacent cell load value η _OthBe this cell uplink total load η _ULWith this cell load η _OwnPoor.

To described cell uplink total load η _ULEstimation comprise:

Measure in real time and receive gross power P in the bandwidth _RTWP, measure Background Noise Power P _N

According to described measured value and this cell uplink total load formula ${\mathrm{\η}}_{\mathrm{UL}}=\frac{P_{\mathrm{RTWP}}-P_N}{P_{\mathrm{RTWP}}}=\frac{\mathrm{NR}-1}{\mathrm{NR}}$ Draw this cell uplink total load, wherein $\mathrm{NR}=\frac{P_{\mathrm{RTWP}}}{P_N}.$

Gross power P in the described reception bandwidth _RTWPBe to measure in real time by each sub-district in the base station to receive gross power in the bandwidth, and gross power in the reception bandwidth of each cell measurement is averaged, obtain the P that single subdistrict is measured in real time _RTWP

As seen from the above technical solution provided by the invention, it is little that the present invention is influenced by user's distribution situation, avoids being subjected to the interference of emulation mode drawback, so that control is optimized to ascending load, improves the capacity and the stability of communication system network; The interference factor of estimating has higher accuracy in real time, makes the control of ascending load more accurate.

Description of drawings

Figure 1 shows that WCDMA macro cell base station layout;

Figure 2 shows that the flow chart of ascending load Control and Optimization.

Embodiment

Core of the present invention is by estimating the adjacent area interference factor, and the control of ascending load is optimized.When estimating the adjacent area interference factor, respectively adjacent cell load and this cell load are estimated, obtain the numerical value of adjacent area interference factor by the ratio that calculates adjacent cell load and this cell load.

Among the present invention the estimation of this cell load is based on the ascending load estimation of user's signal to noise ratio, is specially: the current channel that uses of user is carried out real-time signal-to-noise ratio (SNR) estimation, calculate the load contribution that this community user connects according to the real-time estimated value of signal to noise ratio.

The present invention is estimated as adjacent cell load: estimate cell uplink total load and this cell load respectively, adjacent cell load value is the poor of cell uplink total load and this cell load.Wherein, the estimation of cell uplink total load is based in the real-time reception bandwidth gross power realizes.

Say that more specifically in the present invention, the adjacent area interference factor that is used to optimize ascending load is estimated by estimating adjacent cell load and this cell load respectively, and the estimated value of adjacent area interference factor is the ratio of adjacent cell load estimated value and this cell load estimated value.

The relational expression of ascending load and adjacent area interference factor is among the present invention:

${\mathrm{\η}}_{\mathrm{UL}}=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{L}_j=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\frac{1}{1+\frac{W}{R_j\·{\left(\mathrm{EbvsN}0\right)}_j\·v_j}},$ Realize based on this relational expression by of the optimization of adjacent area interference factor ascending load.

By the relation of this cell load estimated value and adjacent cell load estimated value and adjacent area interference factor as can be seen, this cell load estimated value and adjacent cell load estimated value are only two amounts that influence the adjacent area interference factor, therefore the accuracy of this cell load estimated value and adjacent cell load estimated value directly determines the accuracy of adjacent area interference factor estimated value, also just directly influences the effect to ascending load control.

Among the present invention the estimation of this cell load is based on the ascending load estimation of user's signal to noise ratio, the current channel that uses of user is carried out real-time signal-to-noise ratio (SNR) estimation, calculate the load contribution that this community user connects according to the real-time estimated value of signal to noise ratio.

Need the transmission signals of each time slot of physical channel all be detected when using channel to carry out real-time signal-to-noise ratio (SNR) estimation the user is current, and according to the corresponding signal to noise ratio that calculates this time slot signal of testing result, the real estimation that realizes the physical channel signal to noise ratio.

When carrying out the load estimation by use channel signal-to-noise ratio (SNR) estimation value, in order to obtain channel signal to noise ratio more accurately, need when signal-to-noise ratio (SNR) estimation, reduce each time slots, as often as possible channel signal be sampled, detected, can each time slots length be set to 2ms here.

For the channel type that is adopted in the communication network, when the channel of user's bearer service comprises Dedicated Physical Data Channel, enhanced dedicated physical data channel, when then calculating this user's load, need the load contribution of considering that a plurality of correlated channels bring for the user.

Here a plurality of correlated channels that need to consider include but not limited to: Dedicated Physical Control Channel, Dedicated Physical Data Channel, enhancement mode Dedicated Physical Control Channel, enhanced dedicated physical data channel.

The present invention to the method for estimation of adjacent cell load is:

Estimate this cell uplink total load based on gross power in the reception bandwidth;

This up total load is made of jointly this cell load and adjacent cell load, drawn this cell load owing in the abovementioned steps again, so both differences is adjacent cell load.

After successively drawing this cell load and adjacent cell load, just can obtain the adjacent area interference factor, optimize network uplink load control.

Elaborate below in conjunction with the optimization method of accompanying drawing to network uplink load control of the present invention.

The present invention realizes by the adjacent area interference factor the optimization of network uplink load control, estimation adjacent area interference factor need be estimated adjacent cell load and this cell load respectively, and the estimated value of adjacent area interference factor is the ratio of adjacent cell load estimated value and this cell load estimated value.

Relation according to this cell load estimated value and adjacent cell load estimated value and adjacent area interference factor, this cell load estimated value and adjacent cell load estimated value are only two amounts that influence the adjacent area interference factor, so the accuracy of this cell load estimated value and adjacent cell load estimated value directly determines the accuracy of adjacent area interference factor estimated value.

Realization preface of the present invention mainly comprises following step:

Estimate this sub-district total load;

Estimate this cell load;

Estimate adjacent cell load;

Estimate the adjacent area interference factor;

Optimize ascending load control.

As shown in Figure 2, the detailed process of ascending load Control and Optimization is as follows.

Step 1, estimate this sub-district total load.

The total load of a sub-district comprises this cell load and two parts of adjacent cell load.

The present invention estimates that the adjacent area interference factor need obtain this cell load and adjacent cell load respectively, and the numerical value of determining this sub-district total load is for the needs that obtain this cell load and adjacent cell load.

The estimation of this sub-district total load is the numerical value P by gross power in the measured real-time reception bandwidth _RTWPEstimate, therefore at first need to obtain the interior gross power of reception bandwidth of real-time measurement.

Each sub-district in the communication network in certain base station to receiving belt wide in gross power measure in real time, promptly every this sub-district of certain time interval just to receiving belt wide in gross power carry out one-shot measurement, and the measured value that at every turn measures of reservation.

After after a while, can obtain this sub-district measured value that gross power is measured in different time points is wide to receiving belt.

Gross power measured value in a plurality of reception bandwidth of gained is averaged gross power in the reception bandwidth that so promptly obtains to measure in real time.

The numerical value of the background noise of each sub-district is fixed numeric values relatively in the base station, can be approximated to be a constant, can be by measuring the numerical value P that obtains background noise _N

Computing formula according to the sub-district total load: ${\mathrm{\η}}_{\mathrm{UL}}=\frac{I_{\mathrm{own}}+I_{\mathrm{oth}}}{P_{\mathrm{RTWP}}}=\frac{P_{\mathrm{RTWP}}-P_N}{P_{\mathrm{RTWP}}},$ Determined just can calculate this sub-district total load behind the numerical value of gross power and background noise in the reception bandwidth of real-time measurement.

Noise value of raising of base station cell is $\mathrm{NR}=\frac{P_{\mathrm{RTWP}}}{P_N}.$

Therefore the sub-district total load can also be expressed as:

${\mathrm{\η}}_{\mathrm{UL}}=\frac{I_{\mathrm{own}}+I_{\mathrm{oth}}}{P_{\mathrm{RTWP}}}=\frac{P_{\mathrm{RTWP}}-P_N}{P_{\mathrm{RTWP}}}=\frac{\frac{P_{\mathrm{RTWP}}}{P_N}-1}{\frac{P_{\mathrm{RTWP}}}{P_N}}=\frac{\mathrm{NR}-1}{\mathrm{NR}}.$

Step 2, estimate this cell load.

The estimation of this cell load is based on the ascending load method of estimation of user's signal to noise ratio.

This method is that the current channel that uses of user is carried out real-time signal-to-noise ratio (SNR) estimation, calculates the load contribution that this community user connects according to the real-time estimated value of signal to noise ratio.

When being carried out real-time signal-to-noise ratio (SNR) estimation, physical channel need the transmission signals of each time slot in the physical channel all be detected, and according to the corresponding signal to noise ratio that calculates this time slot signal of testing result, the real estimation that realizes the physical channel signal to noise ratio.

When carrying out the load estimation by use channel signal-to-noise ratio (SNR) estimation value, in order to obtain channel signal to noise ratio more accurately, need when signal-to-noise ratio (SNR) estimation, reduce each time slots, as often as possible channel signal be sampled, detected, can each time slots length be set to 2ms here.

For the channel type that is adopted in the communication network, when the channel of user's bearer service comprises Dedicated Physical Data Channel, enhanced dedicated physical data channel, when then calculating this user's load, need the load contribution of considering that a plurality of correlated channels bring for the user.

Here a plurality of correlated channels that need to consider include but not limited to: Dedicated Physical Control Channel, Dedicated Physical Data Channel, enhancement mode Dedicated Physical Control Channel, enhanced dedicated physical data channel.

At this moment, the step of load estimating method comprises:

Utilize the transformat indicating gage of former frame demodulation to calculate the current power control gain factor β that uses the relative Dedicated Physical Control Channel of channel of user _{Ch, i}, calculate the current power control yield value β that uses the relative Dedicated Physical Control Channel of each chip in the channel _DPCHC

Obtaining power control gain factor β _{Ch, i}With power control yield value β _DPCHCAfter, according to formula:

${\mathrm{SIR}}_{\mathrm{ch},i}={\mathrm{SIR}}_{\mathrm{DPCCH}}\·[1+{\left(\frac{{\mathrm{\β}}_{\mathrm{ch},i}}{{\mathrm{\β}}_{\mathrm{DPCHC}}}\right)}^2],$ Just can directly calculate the current signal to noise ratio of using channel;

Obtain the current signal to noise ratio SIR that uses channel _{Ch, i}After, according to formula: ${\mathrm{\η}}_{j,i}=\frac{{\mathrm{SIR}}_{\mathrm{ch},i}}{1+{\mathrm{SIR}}_{\mathrm{ch},i}},$ Just can directly calculate the current load contribution value of using channel of user;

For the user that multiple channel type is arranged, calculate load contribution and summation that every kind of channel type brings successively, obtain the load contribution of user to network cell, wherein the computing formula of the load contribution of network cell is: ${\mathrm{\η}}_j=\underset{i}{\mathrm{\Σ}}{\mathrm{\η}}_{j,i}=\underset{i}{\mathrm{\Σ}}\frac{{\mathrm{SIR}}_{\mathrm{ch},i}}{1+{\mathrm{SIR}}_{\mathrm{ch},i}},$ Wherein i represents channel type;

According to this community user sum, the load contribution summation to the all-network sub-district just can calculate the load that this community user brings at last, ${\mathrm{\η}}_{\mathrm{own}}=\underset{j}{\mathrm{\Σ}}{\mathrm{\η}}_j,$ Wherein j represents the number of users in the sub-district.

Step 3, estimate adjacent cell load.

Through above step 1 and step 2, obtain sub-district total load and this cell load respectively.

Because the sub-district total load is this cell load and adjacent cell load sum,

Therefore, the result who the sub-district total load that obtains is deducted this cell load gained is adjacent cell load.

Step 4, estimation adjacent area interference factor.

Through above each step, this cell load and adjacent cell load have been obtained.Directly calculate according to the computing formula of adjacent area interference factor and can obtain the adjacent area interference factor.

Adjacent area interference factor computing formula is: $i=\frac{{\mathrm{\η}}_{\mathrm{oth}}}{{\mathrm{\η}}_{\mathrm{own}}}.$

Step 5, the control of optimization ascending load.

After obtaining accurately the adjacent area interference factor, according to the relational expression of ascending load and adjacent area interference factor ${\mathrm{\η}}_{\mathrm{UL}}=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{L}_j=(1+i)\×\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\frac{1}{1+\frac{W}{R_j\·{\left(\mathrm{EbvsN}0\right)}_j\·v_j}}$ Control to ascending load is optimized.

In sum, the present invention is according to the numerical value P of gross power in the real-time reception bandwidth that measures _RTWPEstimate this cell load, use is estimated adjacent cell load based on the ascending load method of estimation of user's signal to noise ratio, thereby finally obtain an adjacent area interference factor that authenticity is higher, be used to optimize ascending load control, improve the capacity and the stability of communication system network.

The above; only for the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (9)

1, the optimization method of ascending load control in a kind of network is characterized in that, comprising:

In network, estimate this cell load and adjacent cell load respectively, and calculate the ratio of the estimated value of the estimated value of adjacent cell load and this cell load, obtain the adjacent area interference factor in the network, utilize the adjacent area interference factor to optimize ascending load control.

2, the optimization method of ascending load control in a kind of network according to claim 1, it is characterized in that, described estimation to this cell load comprises: current each time slot of channel that uses of this community user is carried out real-time signal-to-noise ratio (SNR) estimation, calculate this cell load according to real-time signal-to-noise ratio (SNR) estimation value.

3, the optimization method of ascending load control in a kind of network according to claim 2 is characterized in that, the time interval of sample point is made as 2ms in the described real-time signal-to-noise ratio (SNR) estimation.

4, according to the optimization method of ascending load control in each described a kind of network of claim 1 to 3, it is characterized in that, the estimation of this cell load comprised:

Estimate the current signal to noise ratio of using channel of this community user;

According to this cell load of signal-to-noise ratio (SNR) estimation.

5, the optimization method of ascending load control in a kind of network according to claim 4 is characterized in that, described the current signal-to-noise ratio (SNR) estimation of channel of using of this community user is comprised:

Utilize the transformat indicating gage of former frame demodulation to calculate the current power control gain factor β that uses the relative Dedicated Physical Control Channel of channel of user _{Ch, i}, calculate the current power control yield value β that uses the relative Dedicated Physical Control Channel of each chip in the channel _DPCHC, the signal to noise ratio SIR of measurement Dedicated Physical Control Channel _DPCCH

Signal to noise ratio SIR according to Dedicated Physical Control Channel _DPCCHCalculate the current signal to noise ratio of using channel,

${\mathrm{SIR}}_{\mathrm{ch},i}={\mathrm{SIR}}_{\mathrm{DPCCH}}\·[1+{\left(\frac{{\mathrm{\β}}_{\mathrm{ch},i}}{{\mathrm{\β}}_{\mathrm{DPCHC}}}\right)}^2].$

6, the optimization method of ascending load control in a kind of network according to claim 4 is characterized in that, the described load of this sub-district being carried out according to signal to noise ratio is estimated to comprise:

According to the current current load value that uses channel of snr computation user that uses channel,

${\mathrm{\η}}_{j,i}=\frac{{\mathrm{SIR}}_{\mathrm{ch},j}}{1+{\mathrm{SIR}}_{\mathrm{ch},i}};$

According to user's channel type kind, calculate load and summation that every kind of channel type brings successively, obtain the load of user to network cell, ${\mathrm{\η}}_j=\underset{i}{\mathrm{\Σ}}{\mathrm{\η}}_{j,i}=\underset{i}{\mathrm{\Σ}}\frac{{\mathrm{SIR}}_{\mathrm{ch},i}}{1+{\mathrm{SIR}}_{\mathrm{ch}.,i}};$

Calculate the load that this community user brings according to this community user sum, ${\mathrm{\η}}_{\mathrm{own}}=\underset{j}{\mathrm{\Σ}}{\mathrm{\η}}_j.$

7, according to the optimization method of ascending load control in each described a kind of network of claim 1 to 3, it is characterized in that described adjacent cell load value η _OthBe this cell uplink total load η _ULWith this cell load η _OwrPoor.

8, the optimization method of ascending load control in a kind of network according to claim 7 is characterized in that, to described cell uplink total load η _ULEstimation comprise:

Measure in real time and receive gross power P in the bandwidth _RTWP, measure Background Noise Power P _N

According to described measured value and this cell uplink total load formula ${\mathrm{\η}}_{\mathrm{UL}}=\frac{P_{\mathrm{RTWP}}-P_N}{P_{\mathrm{RTWP}}}=\frac{\mathrm{NR}-1}{\mathrm{NR}}$ Draw this cell uplink total load, wherein $\mathrm{NR}=\frac{P_{\mathrm{RTWP}}}{P_N}.$

9, the optimization method of ascending load control in a kind of network according to claim 8 is characterized in that gross power P in the described reception bandwidth _RTWPBe to measure in real time by each sub-district in the base station to receive gross power in the bandwidth, and gross power in the reception bandwidth of each cell measurement is averaged, obtain the P that single subdistrict is measured in real time _RTWP

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