CN102196543A - Binary-power-allocation-based mobile communication base station energy efficiency optimization method - Google Patents

Abstract

The invention provides a binary-power-allocation-based mobile communication base station energy efficiency optimization method. Aiming at the base station energy efficiency optimization of a system, a judgment threshold value for performing power allocation on each sub-channel of the system is obtained according to the principles of keeping certain total transmission power of a binary power set and not reducing the energy efficiency of the system, and each sub-channel is judged according to the threshold value to determine the power set to which each sub-channel belongs and further perform corresponding power allocation on each sub-channel, thereby realizing the mobile communication base station energy efficiency optimization.

Description

A kind of mobile communication base station optimized for energy efficiency method based on the binary power division

Technical field

The invention belongs to wireless communication technology, specifically relate to a kind of mobile communication base station optimized for energy efficiency method based on the binary power division.

Background technology

Along with the rapid increase of mobile communication subscriber quantity and the rapid rise of wireless broadband business (as multimedia service), people expect that future mobile communication system can provide higher data transmission rate (more than the 100Mbps), higher spectrum efficiency (more than the 10bps/Hz).

(Multiple Input Multiple Output MIMO) is a kind of technology that disposes many antennas at transmitting terminal and receiving terminal to multiple-input and multiple-output.MIMO is a kind of effective means that improves spectrum efficiency, and it can for system brings diversity gain and spatial multiplexing gain, increase exponentially the spectrum efficiency of system under the prerequisite that does not increase transmitting power.

(Orthogonal frequency division multiplexing OFDM) has been used as the basic modulation system of wideband wireless communication system of future generation to OFDM.It at first utilizes string and conversion that signal is become the lower parallel signal of multichannel speed, again parallel signal is modulated on the orthogonal sub-carriers, realized the orthogonality between the subchannel, utilize the Cyclic Prefix technology to eliminate simultaneously and postpone the intersymbol interference that expansion brings, remarkable superiority on having represented this technology intersymbol being crosstalked in suppressing interchannel interference and channel.

In fact, the MIMO technology combine with OFDM the MIMO-OFDM technology that forms become the plan of 3GPP Long Term Evolution (Long Time Evolution, LTE) in the technical standard of physical layer descending chain circuit.Along with ICT system energy consumption problem causes extensive concern day by day, more and more Resource Allocation Formulas of being devoted to optimize MIMO-OFDM system capacity efficient are just put forward by academia and industrial circle, but these schemes are not reached an agreement on the standard of energy efficiency as yet at present, with the input-output relation of the transmitted power of base station end weigh energy efficiency and the scheme that is optimized actually rare.

Summary of the invention

The present invention is with the spectrum efficiency of base station in the mobile communication system and likening to weighing the standard of system energy efficiency of transmitted power, and on the basis of this kind efficiency standard, proposed a kind of mobile communication base station optimized for energy efficiency method, be intended to improve the energy efficiency of system based on the control of binary power.

A kind of mobile communication base station optimized for energy efficiency method based on the control of binary power may further comprise the steps:

(1) the total transmitted power P of the subchannel of initialization powerful channel collection _MaxtotalWith the total transmitted power P of the subchannel of small-power channel set _Mintotal

(2) all subchannels are obtained sets of sub-channels by the descending arrangement of channel norm value

(3) determine powerful channel collection and small-power channel set in the following manner:

(31) will

In the 1st subchannel add the powerful channel collection, make i=2;

(32) if

In the i subchannel sound out to add the total energy efficiency that does not reduce current powerful channel collection behind the powerful channel collection, then the i subchannel is added the powerful channel collection, enter step (33), otherwise, will

In i to N subchannel add the small-power channel set, enter step (4);

(33) i=i+1, if i≤N returns step (32), otherwise, enter step (4);

(4) each subchannel that powerful channel is concentrated distributes power

Each subchannel in the small-power channel set is distributed power

M is the subchannel number that powerful channel is concentrated, and N is In the subchannel number.

Further, described step (32) is judged as follows In the i subchannel sound out to add the total energy efficiency that whether reduces current powerful channel collection behind the powerful channel collection: if the signal to noise ratio snr of i subchannel _iSatisfy

Represent that then the i subchannel sound out to add the total energy efficiency that does not reduce current powerful channel collection behind the powerful channel collection, wherein,

n _iBe local noise power;

The transmission matrix norm of representing the i subchannel.

Technique effect of the present invention is embodied in, output with base-station transmitting-power---the relation of input is come the energy efficiency of define system, and at single cell mimo-ofdm system, to optimize the mobile communication base station energy efficiency is purpose, a kind of optimized for energy efficiency algorithm based on the control of binary power has been proposed, by the power judging threshold that mathematical derivation draws, subchannel is judged with the control of realization power, thus the energy efficiency of raising system.

Description of drawings

Fig. 1 is the scene graph of single sub-district multi-user MIMO-OFDM that the present invention considered.

Fig. 2 is the flow chart of optimized for energy efficiency algorithm among the present invention.

Fig. 3 is the analogous diagram of the spectrum efficiency of algorithm of the present invention and these two kinds of algorithms of average power control algolithm with total transmitted power situation of change.

Fig. 4 is the analogous diagram of the energy efficiency of algorithm of the present invention and these two kinds of algorithms of average power control algolithm with total transmitted power situation of change.

Embodiment

Specifically describe the present invention below in conjunction with accompanying drawing and embodiment.

As shown in Figure 1, consider a single cell mimo-ofdm system, the dual-mode antenna number is respectively M _TAnd M _R, it is N that there is number of subchannels in system, set of sub-channels is combined into K ^N, the total frequency spectrum efficient of system is C _Total, total energy efficiency is η _Total, total consumed power is P _Total, P _iThe transmitted power that expression subchannel i is assigned to; n _iRepresent local noise power;

The transmission matrix norm of expression subchannel i, wherein, H _iBe M _T* M _RMatrix.According to the efficiency model that this programme proposes, this list cell mimo-ofdm system total frequency spectrum efficient C _Total, total energy efficiency η _Total, total consumed power P _TotalBetween relational expression be:

$C_{\mathrm{total}}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\log }_2(1+\frac{P_i}{n_i}{\left|\right|H_i\left|\right|}_F^2)$

${\mathrm{\η}}_{\mathrm{total}}=C_{\mathrm{total}}/P_{\mathrm{total}}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\log }_2(1+\frac{P_i}{n_i}{\left|\right|H_i\left|\right|}_F^2)}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{P}_i}$

$P_{\mathrm{total}}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{P}_i$

The present invention is in conjunction with binary power collection P _i∈ Ω ^B, Ω ^B={ P|P=P _MinorP=P _Max, with channel set K ^NThe subclass that is divided into two complementations is the powerful channel collection

With the small-power channel set

The powerful channel collection

In the power that is assigned to of each subchannel be P _Max,

In each sub-channel power and be P _MaxtotalThe small-power channel set

In the power that is assigned to of each subchannel be P _Min,

In each sub-channel power and be P _MintotalRelation equation group between each power is as follows:

$\left\{\begin{array}{c}{P}_{\mathrm{total}}=P_{\max \mathrm{total}}+P_{\min \mathrm{total}}\\ P_{\max \mathrm{total}}=M\×P_{\max }\\ P_{\min \mathrm{total}}=(N-M)\×P_{\min }\end{array}\right.$

Wherein, M is the powerful channel collection

In the subchannel number.

Can algorithm design of the present invention according to the different situations of each subchannel, determine each subchannel be assigned to the powerful channel collection from the angle of energy efficiency

There are two restrictive conditions in channel in the set:

(1) total consumed power P in this set _MaxtotalBe definite value.

(2) energy efficiency does not reduce principle, a subchannel k to be selected is added set that is:

Sound out, according to powerful channel collection behind this exploration subchannel of adding

The number M of sub-channels+1 averages power division: Just determine this subchannel put into set when not reducing the total energy efficiency of this set when the adding of souning out subchannel k this moment

Otherwise it is placed into set

According to the restrictive condition of this algorithm, can derive subchannel k and be selected into set

Threshold condition be:

Can get according to simulation result, When the powerful channel collection

The number M of sub-channels rises at 40 o'clock by 2,

Rise near limiting value e from numerical value 2, it is monotonically increasing along with the growth of number of subchannels; And, when subchannel less interval in (such as interval [0,10]) when changing, the threshold value growth is very fast; After number of subchannels surpassed certain number, the growth of threshold value was just slower, and quite near limiting value e: such as having existed at the powerful channel collection under the situation of 29 subchannel, by the threshold value expression formula

2.673 of threshold values that draws differ 1.67% with limiting value e, so threshold condition is done following simplification:

When souning out the subchannel sequence number and count k＜30, threshold condition 1 is arranged:

$({\mathrm{SNR}}_K=\frac{P_{\max }}{n_k}{\left|\right|H_k\left|\right|}_F^2)\≥{\left(\frac{M+1}{M}\right)}^M-1,$

When souning out the subchannel sequence number and count k 〉=30, threshold condition 2 is arranged:

$({\mathrm{SNR}}_K=\frac{P_{\max }}{n_k}{\left|\right|H_k\left|\right|}_F^2)\≥e-1,$

Tell about this example below in conjunction with algorithm flow chart.

Algorithm steps:

(1) initialization: determine the gross power P of system _Total, the powerful channel collection

In the power and the P of each subchannel _MaxtotalAnd small-power channel set

In the power and the P of each subchannel _MintotalUsually, powerful channel collection

In, the power of each subchannel and P _MaxtotalValue approach the gross power P of system _Total, account for P _Total97% to 99%, and correspondingly, the small-power channel set

In the power and the P of each subchannel _MintotalValue account for P _Total1% to 3%.

Produce N sets of sub-channels K:

$K=\left\{\mathrm{CH}\right|\mathrm{CH}=\underset{i=1}{\overset{N}{\∪}}{\mathrm{CH}}_i\};$

(2) N subchannel among the set K pressed the descending arrangement of its channel norm value:

$\tilde{K}=\left\{\mathrm{CH}\right|\mathrm{CH}=\underset{i=1}{\overset{N}{\&cup;}}{\mathrm{CH}}_i;\&ForAll;(1\&le;i\&le;k\&le;N):{\left|\right|H_i\left|\right|}_{\mathrm{<figure-callout\; id="2"\; label="F"\; filenames="110518150038.png"\; state="\{\{state\}\}">F</figure-callout>}}^2\&GreaterEqual;{\left|\right|H_k\left|\right|}_F^2\}.$

(3) determine the powerful channel collection in the following manner

With the small-power channel set

(31) will

In the 1st subchannel add the powerful channel collection Make i=2;

(32) for

In the i subchannel, carry out following steps:

$a)P_{\max }=\frac{P_{\max \mathrm{total}}}{i-1};$

B) for this subchannel i,

I) if i＜30 judge whether its signal to noise ratio satisfies threshold condition

If i 〉=30 judge whether its signal to noise ratio satisfies threshold condition

If ii) its signal to noise ratio satisfies threshold value, then the i subchannel is added the powerful channel collection Enter step (33), otherwise, will

In i to N subchannel add the small-power channel set, enter step (4);

(33) i=i+1, if i≤N returns step (32), otherwise, enter step (4);

(4) each subchannel that powerful channel is concentrated distributes power

Each subchannel in the small-power channel set is distributed power

M is the subchannel number that powerful channel is concentrated, and N is

In the subchannel number.

(5) all subchannels begin communication;

(6) algorithm finishes.

Fig. 3 and Fig. 4 result for the example among Fig. 1 is carried out emulation has compared spectrum efficiency performance and the energy efficiency Effect on Performance of the variation of total transmitted power to two kinds of algorithms respectively.During emulation, system's subchannel number is made as 64, total transmitted power P of system _TotalBe set at 0.6W, 0.8W, 1.0W, four power levels of 1.2W, small-power channel set

Total transmitted power P _MintotalBe set at 0.01W.

From simulation result as can be seen, along with the increase of total transmitted power, the performance of algorithm of the present invention all will obviously be better than the average power control algolithm aspect spectrum efficiency and the energy efficiency two; The spectrum efficiency of algorithm of the present invention increases along with the increase of total transmitted power, its energy efficiency reduces along with the increase of total transmitted power, but as can be seen from Figure 4, even algorithm of the present invention drops to the minimum point place, its energy efficiency still is better than the maximum of the average power control algolithm of this interval section.

Claims (2)

1. mobile communication base station optimized for energy efficiency method based on binary power control may further comprise the steps:

(1) the total transmitted power P of the subchannel of initialization powerful channel collection _MaxtotalWith the total transmitted power P of the subchannel of small-power channel set _Mintotal

(2) all subchannels are obtained sets of sub-channels by the descending arrangement of channel norm value

(3) determine powerful channel collection and small-power channel set in the following manner:

(31) will

In the 1st subchannel add the powerful channel collection, make i=2;

(32) if

In the i subchannel sound out to add the total energy efficiency that does not reduce current powerful channel collection behind the powerful channel collection, then the i subchannel is added the powerful channel collection, enter step (33), otherwise, will In i to N subchannel add the small-power channel set, enter step (4);

(33) i=i+1, if i≤N returns step (32), otherwise, enter step (4);

(4) each subchannel that powerful channel is concentrated distributes power

Each subchannel in the small-power channel set is distributed power

M is the subchannel number that powerful channel is concentrated, and N is

In the subchannel number.

2. mobile communication base station according to claim 1 optimized for energy efficiency method is characterized in that described step (32) is judged as follows In the i subchannel sound out to add the total energy efficiency that whether reduces current powerful channel collection behind the powerful channel collection: if the signal to noise ratio snr of i subchannel _iSatisfy

Represent that then the i subchannel sound out to add the total energy efficiency that does not reduce current powerful channel collection behind the powerful channel collection, wherein,

n _iBe local noise power; The transmission matrix norm of representing the i subchannel.

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