CN106921985B

CN106921985B - Self-organizing optimization method and device for ultra-dense network

Info

Publication number: CN106921985B
Application number: CN201510996662.3A
Authority: CN
Inventors: 郭海友; 佘锋
Original assignee: Nokia Shanghai Bell Co Ltd
Current assignee: Nokia Shanghai Bell Co Ltd
Priority date: 2015-12-25
Filing date: 2015-12-25
Publication date: 2021-02-23
Anticipated expiration: 2035-12-25
Also published as: WO2017109577A1; CN106921985A

Abstract

A self-organization optimization method and device of a super-dense network are provided, wherein the self-organization method of a detection link comprises the following steps: the detection link transmits a detection signal by fixed power; when the locally measured SINR of the active link in the ultra-dense network converges to a constant, the detection link obtains the maximum achievable SINR of the detection link according to the current SINR and SNR of the local measurement and the current power normalization maximum value, so that the detection link determines whether to access the ultra-dense network. By adopting an autonomous process for a detection link to be accessed into the network and an active link in the network, the detection link can determine whether to access the ultra-dense network according to the obtained maximum achievable SINR, so that the power consumption is reduced on the basis of ensuring higher unit area spectral efficiency, and the network resources are efficiently utilized.

Description

Self-organizing optimization method and device for ultra-dense network

Technical Field

The invention relates to the field of network communication, in particular to a self-organizing optimization method and a self-organizing optimization device for an ultra-dense network.

Background

Currently, the global development of fifth generation mobile communication technology (abbreviated as 5G) is gradually increasing, wherein the network densification with global reuse capability of frequency resources is considered as one of the irreplaceable solutions of 5G technology. As the degree of network densification tends to be extreme, Ultra Dense Networks (UDNs) no longer consist of regular hexagonal cells, but instead are distorted and overlapping areas, especially in the case of uneven traffic distribution and random variations in network topology. For such a UDN with global reuse capability of frequency resources, it is impractical to specify interference patterns in advance and plan the capacity and coverage of the network, and an online-implementable self-organizing and self-optimizing method is needed to accomplish access control and interference control of the channel. The design aim of the method is to utilize a cognitive method to match underutilized wireless resources in space-time two dimensions according to the change of service requirements. To cope with the explosive growth in the number of user equipments and the rate required by each user equipment, the UDN needs to implement network-wide coordination of tens or hundreds of user equipments sharing the same channel. However, since the feedback and interaction of the channel state information and the network scheduling decision information are practically limited by the signaling transmission and the backhaul network, such large-scale coordination is difficult to be realized in a centralized manner. The practical application scheme is prone to adopt a distributed autonomous mode to realize self-organization and self-optimization of the whole network, and each link in the network can achieve consistent access and resource configuration decision according to local measurement values and a small amount of signaling interaction.

Disclosure of Invention

The self-organizing optimization method and the self-organizing optimization device of the ultra-dense network realize an autonomous process, so that a detection link can determine whether to access the ultra-dense network according to the obtained maximum achievable SINR.

One embodiment includes a method of self-organizing probe links in an ultra-dense network, comprising:

the detection link transmits a detection signal by fixed power;

when the locally measured signal to interference plus noise ratio (SINR) of an active link in the ultra-dense network converges to be a constant, the detection link obtains the maximum achievable SINR of the detection link according to the locally measured current SINR, the locally measured signal to noise ratio (SNR) and the current power normalization maximum value, so that the detection link determines whether to access the ultra-dense network.

Another embodiment is a method for self-organizing active links in an ultra-dense network, when a probe link transmits a probe signal with a fixed power, comprising:

each active link respectively updates the transmitting power at the next moment according to the target signal-to-interference-and-noise ratio SINR, the current SINR of local measurement, the normalized noise power value of local measurement, the current transmitting power value and the current power normalized maximum value;

and each active link iteratively updates the transmitting power of the active link along with time according to the transmitting power of the next moment until the locally measured SINR value of the active link converges to a constant.

Another embodiment is a method for self-organizing optimization for ultra-dense networks, comprising:

the detection link transmits a detection signal by fixed power;

each active link iteratively updates the transmission power of the active link along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant, and the detection link obtains the maximum achievable SINR of the detection link according to the locally measured current SINR, the signal-to-noise ratio (SNR) and the current power normalization maximum value; when the maximum achievable SINR is greater than or equal to the target SINR of the sounding link, the sounding link accesses a super-dense network as an active link; and,

and the detection link and the active link update respective transmitting power according to the respective target SINR, the current SINR measured locally, the current transmitting power value and the current power normalization maximum value until the working SINR of each detection link and each active link is greater than the respective target SINR.

Another embodiment includes an ad-hoc device for probing links in a very dense network, comprising:

a transmitter of the probing link for transmitting a probing signal with a fixed power;

and the receiver of the detection link is used for obtaining the maximum achievable SINR of the detection link according to the current SINR, the signal-to-noise ratio SNR and the current normalized maximum value of the power of the local measurement when the locally measured SINR of the active link in the ultra-dense network converges to be a constant, so that the detection link determines whether to access the ultra-dense network.

Another embodiment is an ad-hoc device for active links in an ultra-dense network, comprising:

a power updater for self-organizing, configured to, when a detection link transmits a detection signal with a fixed power, each active link respectively updates transmission power at a next time according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmission power value, and a current power normalized maximum value; and each active link iteratively updates the transmission power of the active link along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant.

Another embodiment is an apparatus for ad hoc optimization of ultra-dense networks, comprising:

a power updater for self-organizing, configured to, when a transmitter of the probe link transmits a probe signal, each active link respectively updates transmit power at a next time according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmit power value, and a current power normalized maximum value; each active link iteratively updates the transmitting power of the active link along with time according to the transmitting power at the next moment, and triggers a receiver of the detection link until the locally measured SINR value of the active link converges to a constant;

the receiver of the detection link is used for obtaining the maximum achievable SINR of the detection link according to the current SINR, the SNR and the current power normalization maximum value which are measured locally;

the access controller of the detection link is used for accessing the detection link to the super-dense network as an active link when the maximum achievable SINR obtained by the receiver of the detection link is greater than or equal to the target SINR of the detection link;

and the power updater is used for updating the respective transmission power of the detection link and the active link according to the respective target SINR, the locally measured current SINR, the current transmission power value and the current power normalization maximum value when the access controller of the detection link controls the detection link to access the ultra-dense network as the active link, until the working SINR of each detection link and each active link is greater than the respective target SINR.

According to the embodiment of the invention, the detection link to be accessed to the ultra-dense network and the active link in the ultra-dense network adopt an autonomous process, so that the detection link can determine whether to access the ultra-dense network according to the obtained maximum achievable SINR, the power consumption is reduced on the basis of ensuring higher unit area spectral efficiency, and the network resources are efficiently utilized.

Drawings

The present invention will become more fully understood from the detailed description given herein below and the accompanying drawings, wherein like elements are represented by like reference numerals, which are given by way of illustration only, and thus are not intended to be limiting of the present invention, and wherein:

fig. 1-1 shows a system diagram with L-1 active links, a sounding link, and M external links superimposed on a common wireless channel.

Fig. 1-2 show a schematic structural diagram of one time frame in a self-organizing optimization method of a super-dense network according to an exemplary embodiment.

Fig. 1-3 are schematic structural diagrams illustrating a link 1, a link 2, a link 3, and a link 4 sequentially probing a time frame of an access network one by one according to an exemplary embodiment in an ad hoc optimization method of a super-dense network.

Fig. 2 illustrates a flow diagram of an ad-hoc method of probing links in an ultra-dense network, according to an example embodiment.

Fig. 3 shows a flowchart of step S220 in an ad hoc method of probing links in an ultra-dense network according to an example embodiment.

Fig. 4 illustrates a flow diagram of a method for self-organization of active links in a very dense network, according to an example embodiment.

FIG. 5 illustrates a flow diagram of a method for ad hoc optimization of a very dense network, according to an example embodiment.

Fig. 6 shows a flow diagram of a method for ad hoc optimization of a very dense network according to another exemplary embodiment.

Fig. 7 shows a flow chart of a method of ad hoc optimization of a very dense network according to yet another example embodiment.

Fig. 8 shows a block diagram of an ad-hoc device for probing links in an ultra-dense network according to an example embodiment.

Fig. 9 shows a block diagram of an ad-hoc optimization device of an ultra-dense network according to an example embodiment.

FIG. 10 illustrates a functional block diagram of an apparatus for self-organizing optimization for ultra-dense networks, according to an example embodiment.

Fig. 11-1 illustrates an operational diagram of an ad hoc optimization device of an ultra-dense network during an ad hoc period of access control according to an exemplary embodiment.

Fig. 11-2 illustrates an operational diagram of a self-organizing optimization device of an ultra-dense network during a self-optimization cycle of power control according to an exemplary embodiment.

Fig. 12 shows a CDF curve of the number of iterations after 1870 experiments performed by the self-organizing optimization method and apparatus for a super-dense network according to an exemplary embodiment, where the abscissa represents the number of iterations and the ordinate represents the empirical probability.

Fig. 13 shows a CDF curve of the maximum achievable SINR error after 1870 experiments with the method and apparatus for self-organizing optimization for ultra-dense networks according to an exemplary embodiment, where the abscissa represents the absolute value of the error (unit: dB) and the ordinate represents the empirical probability.

Fig. 14 shows the evolution process of the working SINR of each link when 5 internal links access the shared wireless channel one by one in sequence in a UDN consisting of 5 internal links and 2 external links. Wherein, the 1 st, 3 rd and 5 th circles from the left represent the self-organizing period of the access control, the 2 nd, 4 th and 6 th circles from the left represent the self-optimizing period of the power control, the abscissa represents time, the ordinate represents working sinr (db), 5 internal links are link 1, link 2, link 3, link 4 and link 5, respectively, reference sign a represents link 1, reference sign b represents link 2, reference sign c represents link 3, reference sign d represents link 4, and reference sign e represents link 5.

Fig. 15 shows the evolution process of the transmission power of each link when 5 internal links in a UDN, which is composed of 5 internal links and 2 external links, access a common wireless channel one by one in sequence, where 5 internal links are link 1, link 2, link 3, link 4 and link 5, respectively, reference numeral f denotes link 1, reference numeral g denotes link 2, reference numeral h denotes link 3, reference numeral i denotes link 4, and reference numeral j denotes link 5.

Fig. 16 shows an evolution process of normalized external interference power of 2 external links when 5 internal links in a UDN composed of 5 internal links and 2 external links access a common wireless channel one by one in sequence, where the 2 external links are external link 1 and external link 2, respectively, and reference k denotes external link 1 and reference m denotes external link 2.

It should be noted that these drawings are intended to illustrate the general nature of the methods, structures, and/or materials utilized in certain exemplary embodiments, and to supplement the written description provided below. The drawings are not necessarily to scale and may not accurately reflect the precise structural or performance characteristics of any given embodiment, and should not be construed as defining or limiting the scope of the values or attributes encompassed by example embodiments. The use of similar or identical reference numbers in various figures is intended to indicate the presence of similar or identical elements or features.

Detailed Description

While the exemplary embodiments are susceptible to various modifications and alternative forms, certain embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that there is no intention to limit example embodiments to the specific forms disclosed, but on the contrary, example embodiments are to cover all modifications, equivalents, and alternatives falling within the scope of the claims. Like reference numerals refer to like elements throughout the description of the various figures.

Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel, concurrently, or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

The term "wireless device" or "device" as used herein may be considered synonymous with and sometimes hereinafter referred to as: a client, user equipment, mobile station, mobile user, mobile terminal, subscriber, user, remote station, access terminal, receiver, mobile unit, etc., and can describe a remote user of wireless resources in a wireless communication network.

The methods discussed below, some of which are illustrated by flow diagrams, may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine or computer readable medium such as a storage medium. The processor(s) may perform the necessary tasks.

Specific structural and functional details disclosed herein are merely representative and are provided for purposes of describing example embodiments of the present invention. The present invention may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The present invention is described in further detail below with reference to the attached drawing figures.

The system diagram of the embodiment of the invention is shown in fig. 1-1, and the system is superimposed with L-1 active links (marked as: link 1,2, … L-1), a probe link (marked as L), and M external links on a common wireless channel, wherein L-1 active links and a probe link realize the transmission of service traffic. Each active link, probe link and external link has a corresponding transmitter and receiver.

The self-organizing optimization method of the super-dense network comprises two periods, wherein one period is an access control self-organizing period of the super-dense network, and the other period is a power control self-optimizing period of the super-dense network. In the access control self-organizing period of the ultra-dense network, the detection link transmits a detection signal with fixed power, and when the local measurement SINR of the active link converges to a constant, the detection link obtains the maximum achievable SINR. Meanwhile, in order to realize that the local measurement SINR of the active link converges to be a constant, the transmission power of the active link is updated iteratively. And ending the access control self-organizing period of the ultra-dense network, and if the maximum achievable SINR obtained by the detection link is greater than or equal to the target SINR, determining whether the detection link is accessed as an active link allowed to be accessed by the detection link. After an original detection link is accessed into a network as an active link, in a power control self-optimization period of a super-dense network, a system is superposed with L active links and M external links on a shared wireless channel, wherein the L active links realize the transmission of service flow, and each active link and each external link are provided with a corresponding transmitter and a corresponding receiver. In a power control self-optimization period of the ultra-dense network, the L Active links iteratively update the transmission power thereof, and the updating of the transmission power is stopped until the working SINRs of the L Active links are all larger than respective target SINRs, so that an appropriate power configuration is automatically reached to meet the non-invasive prerequisite condition of Active Link Protection (ALP). The ALP conditions were:

ALP conditions:

wherein p is_lDenotes the transmission power, beta, of the link l_lWhich represents the target SINR for link i,

(M-1, 2, …, M) represents the upper interference power limit acceptable for link M,

(L-1, 2, …, L) represents the maximum allowable transmit power for link L, G_lkRepresenting the channel gain, n, of the transmitter of link k to the receiver of link l_lRepresenting the power, w, of the background noise of the receiver of link l determined under the influence of thermal noise and external link interference_m,lDenotes the channel gain of the transmitter of link i to the receiver of external link m, and p ═ p₁ p₂ … p_L]^T。

The time frame structure of the ultra-dense network of the embodiment of the present invention may be as shown in fig. 1-2, where one frame is composed of three consecutive periods for different purposes, i.e., an access control self-organizing period of the ultra-dense network, a power control self-optimizing period of the ultra-dense network, and a trivial period, where, in the trivial period, all links allowed to access the ultra-dense network transmit data signals without power update. As shown in fig. 1-3, the system shown in fig. 1-1 desirably superimposes as many links as possible sequentially on the common wireless channel.

Fig. 2 is a flow diagram of a method for self-organizing probe links in an ultra-dense network according to one embodiment of the present application.

Referring to fig. 2, the self-organizing method for detecting links in an ultra-dense network according to this embodiment includes the following steps:

s210, transmitting a detection signal by a detection link through fixed power;

s220, when the locally measured Signal to Interference plus Noise Ratio (SINR) of an active link in the ultra-dense network converges to a constant, the detection link obtains the maximum achievable SINR of the detection link according to the current SINR and Signal to Noise Ratio (SNR) of the local measurement and the current power normalization maximum value, so that the detection link determines whether to access the ultra-dense network.

The steps are described in further detail below.

In step S210, a common radio channel in the super-dense network has at least one active link that has been accessed to the network and at least one external link that satisfy the ALP condition, and the probe link is a new active link to be accessed to the super-dense network.

As shown in fig. 3, the operation performed by the probing link in S220 is step S2207, wherein the process of determining that the locally measured SINR of the active link i in the super-dense network converges to a constant is steps S2201-S2206:

s2201 receiver of each active link L (L ═ 1,2 … L-1) will measure locally normalized noise power value

Feeding back to its corresponding transmitter, where n_lRepresenting the sum of interference based on thermal noise plus external linkPower of background noise, G, of receiver affecting determined active link l_llRepresenting the channel gain from the transmitter of the active link/to the receiver of the active link/.

S2202, receiver of each active link L (L ═ 1,2 … L-1) will locally measure current SINR value SINR_l(t) feedback to its corresponding transmitter, wherein

p_l(t) denotes the transmit power of the currently active link L (L ═ 1,2 … L-1), P_LSaid fixed power representing the sounding link L

S2203, broadcasting the normalized external interference power of each external link M (M is 1,2, …, M) on the dedicated channel

Wherein,

represents the upper limit of the acceptable interference power of the external link m, w_m,lRepresenting the channel gain, w, from the transmitter of the active link/to the receiver of the external link m_m,LRepresenting the channel gain from the transmitter of the sounding link L to the receiver of the external link m.

S2204, broadcasting the normalized transmitting power of each active link l in a special channel

Representing the maximum allowable transmit power for the active link/.

S2205, the transmitter of each active link l updates the transmission power at the next moment to be

Wherein, beta_lRepresents the target SINR for the active link/, representing the current power normalized maximum.

In particular, the current power normalized maximum value

The method comprises the following steps: normalized transmit power per active link in ultra-dense networks

Normalized transmit power of the probe link

And normalized external interference power of each external link in ultra-dense network

Maximum value of (2).

S2206, if SINR in step S2202_l(t) converges to a constant, step S2207 is executed, otherwise steps S2202 to S2205 are iteratively repeated so that t equals t + 1.

S2207, the probing link obtains the maximum achievable SINR according to the current SINR and SNR measured locally and the current power normalization maximum value, so that the probing link determines whether to access the ultra-dense network. Specifically, the obtaining of the maximum achievable SINR includes:

wherein the maximum achievable SINR, SINR of the sounding link is represented_L(t) SNR, which is the current SINR value measured locally on the sounding link_LRepresenting locally measured SNR values of the probe link

Referring to fig. 4, the self-organizing method for active links in a super-dense network according to this embodiment includes the following steps:

and S410, each active link respectively updates the transmission power at the next moment according to the respective target SINR, the current SINR of local measurement, the normalized noise power value of local measurement, the current transmission power value and the current power normalized maximum value.

Specifically, the transmitter of each active link l updates the transmit power at the next time instant to

Wherein, beta_lTarget SINR, SINR representing the active link l_l(t) current SINR value p representing local measurement of the active link l_l(t) represents the transmit power of the current active link l, represents the locally measured normalized noise power value of the active link l, and represents the current power normalized maximum.

In particular, the current power normalized maximum value

Normalized transmit power of the probe link

Maximum value of (1); wherein,

p_l(t) represents the transmit power of the currently active link/,

represents the maximum allowable transmit power of the active link/; wherein,

P_Lthe fixed power is represented by the power of the power,

represents a maximum allowable transmit power for the sounding link; wherein,

wherein,

S420 SINR of each active link L (L ═ 1,2 … L-1)_l(t) converges to a constant, step S430 is performed, otherwise step S410 is iteratively repeated in a manner that t is t + 1.

S430, the detection link obtains the maximum achievable SINR of the detection link according to the current SINR and SNR measured locally and the current power normalization maximum value, so that the detection link determines whether to access the ultra-dense network.

Referring to fig. 5, the self-organizing optimization method for the ultra-dense network according to this embodiment includes the following steps:

s510, detecting the passing of the link with fixed power P_LA probe signal is transmitted.

Further, broadcasting the normalized transmit power of the sounding link on a dedicated channel

S520, each active link L (L ═ 1,2 … L-1) updates the transmission power at the next time according to the target SINR, the current SINR of the local measurement, the normalized noise power value of the local measurement, the current transmission power value, and the current normalized maximum power value of the power, respectively

S530 SINR for each active link L (L ═ 1,2 … L-1)_l(t) converges to a constant, step S540 is performed, otherwise step S520 is iteratively repeated in a manner that t equals t + 1.

S540, the detection link obtains the maximum achievable SINR according to the current SINR and SNR of the local measurement and the current power normalization maximum value:

and S550, when the maximum achievable SINR is larger than or equal to the target SINR of the detection link, the detection link accesses the ultra-dense network as an active link.

And S560, the detection link and the active link update respective transmitting power according to the respective target SINR, the current SINR measured locally, the current transmitting power value and the current power normalization maximum value until the working SINR of each detection link and each active link is greater than the respective target SINR.

As shown in fig. 6, step S560 may be implemented by the following method:

s610, each active link k (k ═ 1,2, …, L-1, L) including the sounding link updates the transmit power at the time (t +1) according to the respective target SINR, the locally measured current SINR and the current transmit power value:

wherein p is_k(t) the transmit power of the currently active link k, β_kTarget SINR, SINR representing active link k_k(t) current SINR value representing local measurement of active link k i.e

S620, each active link k according to the transmission power p at the updated (t +1) moment_kThe maximum value of the power normalization at the time (t +1) and the time (t +1) determines the transmission power at the time (t +2) thereof: wherein the maximum normalized power value at time (t +1) is the normalized transmit power (k ═ 1,2, …, L-1, L) of each active link k at time (t +1) and the normalized outward power value at time (t +1) of each external link in the ultra-dense networkInterference power

Maximum value of (1); wherein,

p_k(t +1) represents the transmission power of the active link k at the time (t +1), representing the maximum allowable transmission power of the active link k; wherein, it represents the upper limit of interference power acceptable by the external link m, w_m,kRepresenting the channel gain from the transmitter of the active link k to the receiver of the external link m.

S630, if SINR of each active link k_k(t) converges to a constant, and then ends, otherwise, steps S610 to S620 are iteratively performed in such a manner that t equals t + 2.

Referring to fig. 7, the execution process of the self-organizing optimization method for the ultra-dense network according to this embodiment includes:

s701, setting t to 0 and the initial transmit power of the transmitter of each active link L (L to 1,2, …, L-1) is not zero.

S702, detecting the link passing through the fixed power P_LTransmitting a probe signal and broadcasting the normalized transmit power of the probe link on a dedicated channel

S703, the receiver of each active link L (L ═ 1,2, …, L-1) will

And feeding back to the corresponding transmitter.

S704, SINR of receiver of each active link l_l(t) feeding back to its corresponding transmitter.

S705 broadcasting each external link M (M is 1,2, …, M) on a dedicated channel

S706, broadcasting each active link l on a dedicated channel

S707, the transmitter of each active link l updates the transmission power at the next moment to

S708, if the SINR of each active link l in the step S704_l(t) all converge to a constant, step S709 is executed, otherwise, steps S704 to S707 are iteratively repeated in a manner that t equals t + 1.

S709, detecting link L according to SINR_L(t) and SNR_LAnd obtaining a maximum achievable SINR of

And S710, when the maximum achievable SINR is larger than or equal to the target SINR of the detection link L, the detection link L is used as an active link to access the ultra-dense network.

S711, the receiver of each active link k (k ═ 1,2, …, L-1, L) including the sounding link, compares the SINR_k(t) feeding back to its corresponding transmitter.

S712, each active link k (k ═ 1,2, …, L-1, L) updates the transmission power at time (t +1) to be

S713, broadcasting on dedicated channel (t +1) for each external link M (M1, 2, …, M)

Broadcasting each active link k at time (t +1) on a dedicated channel S714

S715, each active link k is according to the p_k(t +1) and determining its transmit power at time (t + 2):

s716, if SINR of each active link k in step S711_kIf (t) converges to a constant, the process ends, otherwise, steps S711 to S715 are iteratively performed such that t equals t + 2.

Embodiments of the invention in the system shown in fig. 1, in addition to the shared radio channel, a feedback channel and a dedicated channel are included, wherein the feedback channel is a feedback channel from the receiver of the a (including L, m, L or k) th link to the transmitter of the a-th link, which is dedicated to the a-th link, and is used to return the locally measured current SINR and SNR values, the locally measured normalized noise power value, and the maximum achievable SINR value of the sounding link. The dedicated channel is used for broadcasting the normalized external interference power of each external link, the normalized transmitting power of each active link, the normalized transmitting power of the detection link and the current power normalized maximum value.

An embodiment of the present invention further provides a self-organizing apparatus for a probe link in an ultra-dense network, as shown in fig. 8, including:

a transmitter 210 of the sounding link for transmitting a sounding signal with a fixed power;

a receiver 220 of the probing link, configured to obtain a maximum achievable SINR of the probing link according to a current SINR and SNR of the local measurement and a current power normalization maximum value when the local measurement SINR of an active link in the ultra-dense network converges to a constant, so that the probing link determines whether to access the ultra-dense network.

Specifically, the method for determining the maximum achievable SINR is:

the embodiment of the invention also provides a self-organizing device of the active link in the ultra-dense network, which comprises:

a power updater for self-organizing, configured to, when a detection link transmits a detection signal with a fixed power, each active link respectively updates transmission power at a next time according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmission power value, and a current power normalized maximum value; and each active link iteratively updates the transmission power of the active link along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant. In particular for updating the transmission power

An embodiment of the present invention further provides a self-organizing optimization apparatus for a super-dense network, as shown in fig. 9, including:

a power updater 910 for self-organizing, configured to, when the transmitter 210 of the probe link transmits a probe signal, update, by each active link, the transmit power at the next time according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmit power value, and a current power normalized maximum value; each active link iteratively updates the transmission power of the active link along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant, and then triggers the receiver 220 of the probing link;

a receiver 220 of the probing link, configured to obtain a maximum achievable SINR of the probing link according to a current SINR, a signal-to-noise ratio SNR, and a current power normalization maximum value of the local measurement;

an access controller 920 for a sounding link, configured to access the super-dense network as an active link when the maximum achievable SINR obtained by the receiver 220 of the sounding link is greater than or equal to a target SINR of the sounding link;

a power updater 930 for self-optimization, configured to, when the access controller 920 of the probe link controls the probe link to access the super-dense network as an active link, update the respective transmit powers of the probe link and the active link according to the respective target SINR, the locally measured current SINR, the current transmit power value, and the current power normalization maximum value until the working SINR of each of the probe link and the active link is greater than the respective target SINR.

Further, the access controller 920 for the probe link is disposed in the transmitter 210 for the probe link. The power updater 910 for self-organization and the power updater 930 for self-optimization according to the embodiment of the present invention may be two different power updaters disposed in the active link transmitter, or may be the same power updater that performs different updating operations in the self-organization period and the self-optimization period. That is, the power updater 910 for self-organization is disposed in the transmitter of the active link, and the power updater 930 for self-optimization is disposed in the transmitter of the probe link and the active link, or a power updater is disposed in both the transmitter of the active link and the transmitter of the probe link, and during the self-organization period of the access control, the power updater in the transmitter of the active link in the ultra-dense network operates by using the calculation method of the power updater 910 for self-organization, and during the self-optimization period of the power control, the power updater in the transmitter of the probe link and the active link in the ultra-dense network operates by using the calculation method of the power updater 930 for self-optimization.

The self-organizing optimization device of the ultra-dense network according to the embodiment of the present invention may further include:

a power normalized maximum broadcaster to determine and broadcast the current power normalized maximum, the current power normalized maximum

The method comprises the following steps: each in super dense networkNormalized transmit power for bar active links

Normalized transmit power of the probe link

Maximum value of (1); wherein,

p_l(t) represents the transmit power of the currently active link/,

represents the maximum allowable transmit power of the active link/; wherein,

P_Lthe fixed power is represented by the power of the power,

represents a maximum allowable transmit power for the sounding link; wherein,

wherein,

In particular, the power-normalized maximum broadcaster is not in the transmitter and receiver of the probing link nor in the transmitter and receiver of the active link, which is independently present in the apparatus.

Based on the system diagram shown in fig. 1, when the same power updater 1010 is used for the power updater 910 for self-organization and the power updater 930 for self-optimization, the structural schematic diagram of all functional modules of the self-organization optimization apparatus of the ultra-dense network according to the embodiment of the present invention may be shown in fig. 10, the operation schematic diagram of the access control self-organization cycle may be shown in fig. 11-1, and the operation schematic diagram of the power control self-optimization cycle may be shown in fig. 11-2.

As shown in fig. 10, the power amplifier in the transmitter of each link adjusts the amount of transmission power according to the output of the power updater 1010. The power updater 1010 may output a fixed power, a zero value (the value output at the end of the access control ad hoc period if the probe link exits), p_l(t+1)、p_k(t +1) and p_k(t + 2). The access controller 920 of the probe link is configured to instruct the probe link to output a "probe" command at the beginning of an ad hoc period of the access control; when the maximum achievable SINR of the detection link is larger than or equal to the target SINR of the detection link, indicating the detection link to output an access instruction at the end of an ad hoc period of access control; and when the maximum achievable SINR of the detection link is smaller than the target SINR of the detection link, instructing the detection link to output an exit instruction at the end of the self-organization period of the access control. The target SINR for either the sounding link or the active link is stored by a memory in its transmitter. The locally measured SINR for either the sounding link or the active link is obtained by an SINR estimator in its receiver. The locally measured SNR of the sounding link is obtained by an SNR estimator in its receiver. The locally measured normalized noise power value of the active link is obtained by a normalized noise power estimator in its receiver. The maximum achievable SINR for the sounding link is obtained by a maximum achievable SINR calculator in its receiver. The normalized alien interference power measured for each external link is obtained by an estimator of the total interference normalization value in its receiver. The power management module in the transmitter of the active link calculates the current transmission power and the maximum allowable transmission power according to the current transmission powerAnd outputting the normalized transmitting power value according to the ratio of the transmitting power.

FIG. 11-1 illustrates the operation of the access control self-organizing period, where at the beginning of the period, the access controller 920 in the probe link transmitter outputs a "probe" command to the power updater 1010, and the power updater 1010 outputs a constant value P_LTo the power amplifier, the probe signal may be a predetermined training sequence for estimating SINR and SNR, or may carry some basic information such as link ID, and the power normalization maximum broadcaster broadcasts the normalized transmit power of the probe link. An access controller in the active link transmitter outputs an 'access' command to a power updater, and simultaneously, a memory in the active link transmitter outputs a target SINR to the power updater, and the power updater transmits an initial power amount of p_l(0) The data signal of (1). A normalized noise power estimator in the active link receiver estimates a locally measured normalized noise power value and feeds it back to a power updater in the active link transmitter via a feedback channel. Iterative process within the self-organizing period: the SINR estimator in the active link receiver estimates the locally measured SINR and feeds back to the power updater of the active link transmitter through a feedback channel. The method comprises the steps that an estimator of a total interference normalization value in an external link receiver estimates normalized external interference power and sends the normalized external interference power to a power normalization maximum value broadcaster, a power management module in an active link transmitter calculates normalized transmitting power and sends the normalized transmitting power to the power normalization maximum value broadcaster, and the power normalization maximum value broadcaster determines the maximum value of the normalized transmitting power of a detection link, the normalized transmitting power of the active link and the normalized external interference power and broadcasts the maximum value. And updating the transmission power by a power updater in the active link transmitter, and ending the self-organizing period of the access control if the local measurement SINR of each active link after updating converges to a constant. When the self-organizing period of the access control is finished, the normalized maximum value broadcaster broadcasts the current normalized maximum value, an SINR estimator and an SNR estimator in the detection link receiver respectively estimate local measurement SINR and SNR, a maximum achievable SINR calculator in the detection link receiver calculates the maximum achievable SINR, and the maximum achievable SINR is used for calculating the maximum achievable SINRThe maximum achievable SINR is fed back to an access controller in the detection link transmitter through a feedback channel, and the access controller outputs an 'access' instruction or an 'exit' instruction to a power updater after comparing the maximum achievable SINR with a target SINR stored in a memory in the detection link transmitter, so that the detection link enters a power control self-optimization period or the power updater outputs a zero value.

Fig. 11-2 is a schematic diagram of a power control self-optimization cycle, in which at the beginning of the cycle, an access controller of a transmitter including an active link k of a probing link outputs an "access" command to a power updater, and a memory outputs a stored target SINR to the power updater, the power updater transmits an initial power amount p_k(0) The data signal of (1). Iterative process within self-optimization cycle: the SINR estimator in the active link k receiver estimates the locally measured SINR and feeds back the estimated locally measured SINR to the power updater in the active link k transmitter via feedback information, which updates the transmit power to p_k(t +1), and outputs to the power amplifier. The method comprises the steps that an estimator of a total interference normalization value in an external link receiver estimates normalized external interference power and sends the normalized external interference power to a power normalization maximum value broadcaster, a power management module in an active link k transmitter calculates normalized transmission power and sends the normalized transmission power to the power normalization maximum value broadcaster, and the power normalization maximum value broadcaster determines the maximum value of the normalized transmission power and the normalized external interference power of an active link k and broadcasts the maximum value. And updating the transmission power by a power updater in the transmitter of the active link k, and ending the self-optimization period of the power control if the updated local measurement SINR of each active link k converges to a constant.

The performance of the proposed self-organizing and self-optimizing method is evaluated as follows:

a UDN is simulated, which is composed of a plurality of internal links and two external links, wherein the transmission power of the internal links is respectively restricted to the maximum transmission power limited by a power supply, and the transmission power of the internal links is also restricted to the requirements of the two external nodes on interference control. In SINR-based power control, fast fading effects are due to passing through the power measurement process orThe averaging process of the diversity processing method can be neglected. Thus, the gain G of the useful channel and the interfering channel_ijCan be modeled as

Wherein d is_ijIs the distance between the transmitter of the internal link j and the receiver of the internal link i.

Similarly, the channel gain from the transmitter of the internal link/to the receiver of the external link m can also be modeled as:

wherein d is_m,lIs the distance between the transmitter of the internal link i and the receiver of the external link m. Fading factor A_ijAnd A_m,lThe power variation due to the shadow effect, which can be modeled with an independent identically distributed lognormal distribution, is modeled as a random variable with a mathematical expectation of 0-dB and a logarithmic variance of 8-dB, and the simulation parameters are specified in table 1. To plot the Cumulative Density Function (CDF) curves, the following data are the results after 1870 independent experiments were performed.

TABLE 1 simulation parameters

Fig. 12 measures the implementation complexity of the proposed method with the number of iterations required within the access control ad hoc period. The number of iterations averaged from 1870 independent realizations is 46.6818. The probability of requiring less than 10 iterations is 40% and the probability of greater than 100 iterations is 6%. Fig. 13 measures the accuracy of the implementation of the proposed method by the absolute error between the actual result and the theoretical value. The average of the absolute error values averaged from 1870 trials was 1.3058e-5 dB. The absolute value of the error is less than 0.0001dB with a probability of 98%. Simulation results prove that the algorithm in the access control self-organizing period of the embodiment of the invention has high precision and low complexity.

In the following, the proposed ad-hoc self-optimization method is evaluated by an example of a network extension. This example simulates a UDN consisting of 5 internal links and 2 external links. The detailed simulation parameters are shown in table 2. In the simulation experiment, 5 internal links access the common radio channel one by one in order. In order to observe the convergence performance of the algorithm, the lengths of the access control self-organizing period and the power control self-optimizing period are not fixed. Furthermore, this example ignores the case of trivial periods. The evolution process of SINR, transmission power and normalized external interference power along with time is recorded by a numerical simulation experiment.

Table 2 simulation parameters for network extension example:

table 3: maximum achievable SINR under multiple power constraints:

table 3 shows the resulting values of the maximum achievable SINR obtained during the network access control ad hoc procedure. Which accurately predicts the maximum achievable SINR for the probing link under network ALP conditions. The maximum achievable SINR for

links

1,2,3,4 exceeds their target SINR, respectively, and then they are allowed to access the common wireless channel and can reach their target SINR. However, the maximum achievable SINR for link 5 is lower than its target SINR. In the simulation experiment, link 5 gave up its target SINR28dB, but was allowed to do so

dB is the target access common radio channel.

Fig. 14 shows the SINR variation process of each link, and the corresponding transmit power and the normalized external interference power variation are respectively shown in fig. 15 and fig. 1Shown in fig. 6. In fig. 14,

circles

1, 3, and 5 from the left represent self-organizing periods of access control, and circles 2, 4, and 6 from the left represent self-optimizing periods of power control. When link 3 accesses the network containing

active links

1 and 2 for the probe link, it predicts

Because of the fact that

The link 3 is automatically allowed to enter the self-optimization period of power control. After the self-optimization process of distributed power control,

links

1,2 and 3 respectively obtain a feasible power allocation to achieve the purpose that the working SINR level is greater than the respective target SINR. As is link 4. Then, when link 5 probes the network including

active links

1,2,3, and 4, it predicts

Due to the fact that

Link 5 with

The network is accessed for the target. Then, after entering the period of power optimization, the entire network reaches a critical point where the SINRs of

links

1,2,3 and 4 reach their respective target SINRs, while link 5 actually achieves an SINR level equal to the target SINR

By the self-organization optimization method and the self-organization optimization device of the ultra-dense network, the SINRs of the active link and the detection link are fast in convergence speed in the self-organization of access control and the self-optimization period of power control, even if the SINRs appear

In the extreme case of (a). Moreover, each link can be independently determined according to the convergence situation of the SINRThe iterative process of power update is immediately stopped.

The self-organizing optimization method and the self-organizing optimization device of the ultra-dense network in the embodiment of the invention adopt an autonomous process through the detection link to be accessed to the ultra-dense network and the active link in the ultra-dense network, so that the detection link can determine whether to access to the ultra-dense network according to the obtained maximum achievable SINR, the power consumption is reduced on the basis of ensuring higher unit spectral efficiency, and the network resources are efficiently utilized. The invention has the following technical characteristics and effects:

first, the self-organizing optimized UDN according to the embodiments of the present invention provides a distributed sounding channel capability that can accurately predict the maximum achievable SINR under multi-power constraint conditions. The self-optimization UDN measures the frequency space multiplexing capability of the network by using the maximum SINR (signal to interference plus noise ratio) which can be realized by the new link, and the method guarantees pareto optimization of frequency space multiplexing in a certain sense. The prediction capability of the network critical point can be used for realizing the self-adaptive distribution of the user rate, and the method goes beyond the traditional method of only estimating the critical point.

Second, ad hoc optimized UDNs enable online non-invasive probing and access. When the active link is transmitting data signals, the probing link transmits probing signals with any constant power during the whole channel probing process. The probing behavior is not competitive and aggressive, but rather is flat and friendly. More precisely, the power of the probing signal can be set small so that the interference of the probing link does not prevent the ongoing transmission of the active link. Furthermore, the current state of the existing active network is not observed in the process of self-optimizing the UDN whole channel sounding, but the state that comes up after the network is extended.

Third, ad hoc optimized UDNs are suitable for large-scale autonomous networks that can achieve efficient spatial multiplexing with low computational cost and control overhead. The computation and control overhead of a self-optimizing UDN increases linearly with respect to the total number of communication links, rather than exponentially. Notably, distributed and parallel designs that do not require cross-link information interaction facilitate the expansion of networks in an autonomous manner.

Fourth, ad hoc optimized UDNs ensure good backward compatibility with current wireless systems. Both the power update process and the distributed power control mechanism are widely used as a standardized technique in current wireless systems. Furthermore, the actual implementation of the power update procedure involves only local measurement methods of SINR, SNR and normalized noise that are commonly employed in commercial communication systems. The upgrade of the existing commercial system to the ad-hoc self-optimization system can be realized only by changing the rule of power update.

In summary, the scheme of the embodiment of the present invention provides a cognitive capability for predicting a global maximum achievable SINR under multiple power constraints. It only performs a single iterative process and relies on local measurements only, i.e. the new link can make an access decision independently and autonomously on the premise of active link protection. Such cognitive capabilities avoid the high signaling overhead required for interaction between access links.

It is noted that the present invention may be implemented in software and/or in a combination of software and hardware, for example, the various means of the invention may be implemented using Application Specific Integrated Circuits (ASICs) or any other similar hardware devices. In one embodiment, the software program of the present invention may be executed by a processor to implement the steps or functions described above. Also, the software programs (including associated data structures) of the present invention can be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Further, some of the steps or functions of the present invention may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Claims

1. A self-organizing method of probe links in ultra-dense networks, comprising the steps of:

the detection link transmits a detection signal by fixed power;

when the locally measured signal to interference plus noise ratio SINR of each active link in the super-dense network converges to a constant, the detection link obtains the maximum achievable SINR of the detection link according to the locally measured current SINR, signal to noise ratio SNR, and the current power normalization maximum value, so that the detection link determines whether to access the super-dense network as an active link, where the current power normalization maximum value includes the maximum value of the normalized transmit power of each active link, the normalized transmit power of the detection link, and the normalized external interference power of each external link in the super-dense network.

2. The self-organizing method of claim 1, wherein the step of the probing link obtaining the maximum achievable SINR of the probing link according to the current SINR, SNR and the current power normalized maximum of the local measurement comprises:

wherein,

representing a maximum achievable SINR, SINR of the sounding link_L(t) is represented byCurrent measured SINR value, SNR, of said probing link_LA locally measured SNR value representing the probing link,

represents the current power normalized maximum value,

the ultra-dense network comprises M external links and L-1 active links, wherein the L-th link is the detection link.

3. A method for self-organizing active links in a super-dense network, when a probe link transmits a probe signal with a fixed power, the method comprising the steps of:

each active link respectively updates the transmitting power at the next moment according to the respective target signal-to-interference-and-noise ratio SINR, the locally measured current SINR, the locally measured normalized noise power value, the current transmitting power value and the current power normalized maximum value, wherein the current power normalized maximum value comprises the maximum value of the normalized transmitting power of each active link, the normalized transmitting power of the detection link and the normalized external interference power of each external link in the ultra-dense network;

each active link iteratively updates the transmission power of the active link along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant, so that the detection link obtains the maximum achievable SINR to determine whether to access the ultra-dense network as the active link;

and the detection link obtains the maximum achievable SINR of the detection link according to the current SINR, the SNR and the current power normalized maximum value which are measured locally.

4. The self-organizing method of claim 3, wherein the step of updating the transmit power of each active link at the next time according to the target SINR of the respective active link, the locally measured current SINR, the locally measured normalized noise power value, the current transmit power value, and the current normalized maximum power value respectively comprises:

the transmission power at the next moment is

Wherein, beta_lTarget SINR, SINR representing the active link l_l(t) current SINR value, p, representing local measurements of the active link/_l(t) represents the current transmit power of the active link/,

normalized noise power value, n, representing local measurements of the active link/_lRepresenting the power, G, of the background noise of the receiver of the active link l determined according to the total effect of the thermal noise plus the interference of said external link_llRepresenting the channel gain from the transmitter of the active link/to the receiver of the active link/,

represents the current power normalized maximum value,

the ultra-dense network comprises M external links and L-1 active links, wherein the L-th link is the detection link to be accessed to the ultra-dense network.

5. A self-organizing optimization method of an ultra-dense network comprises the following steps:

the detection link transmits a detection signal by fixed power;

each active link in the ultra-dense network respectively updates the transmitting power at the next moment according to a respective target signal-to-interference-and-noise ratio (SINR), a locally measured current SINR, a locally measured normalized noise power value, a current transmitting power value and a current power normalized maximum value, wherein the current power normalized maximum value comprises the maximum value of the normalized transmitting power of each active link, the normalized transmitting power of the detection link and the normalized external interference power of each external link in the ultra-dense network;

the transmission power of each active link is updated iteratively along with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant, and the detection link obtains the maximum achievable SINR of the detection link according to the locally measured current SINR, the locally measured SNR and the current power normalization maximum value; when the maximum achievable SINR is greater than or equal to the target SINR of the probing link, accessing the probing link as an active link to the ultra-dense network; and the number of the first and second groups,

and updating respective transmission power of all current active links according to the respective target SINR, the locally measured current SINR, the current transmission power value and the current power normalization maximum value until the working SINR of each of all the active links is greater than the respective target SINR.

6. The self-organizing optimization method of claim 5, further comprising:

determining and broadcasting the current power normalized maximum value, the current power normalized maximum value

The method comprises the following steps: normalized transmitting power of each active link

Normalized transmit power of the probe link

And normalized external interference power of each external link

Maximum value of (1);

wherein,

p_l(t) represents the current transmit power of the active link/,

represents the maximum allowable transmit power of the active link/;

wherein,

P_Lrepresents the fixed power of the sounding link,

representing a maximum allowable transmit power of the sounding link;

wherein,

wherein,

represents the upper limit of the acceptable interference power of the external link m, w_m,lRepresenting the channel gain, w, from the transmitter of the active link/to the receiver of the external link m_m,LRepresenting the channel gain from the transmitter of the sounding link to the receiver of the external link m;

7. An ad-hoc device of probe links in an ultra-dense network, comprising:

the transmitter of the detection link is used for transmitting a detection signal by fixed power;

the receiver of the probe link is configured to, when the locally measured signal-to-interference-and-noise ratio SINR of each active link in the ultra-dense network converges to a constant, obtain a maximum achievable SINR of the probe link according to a current SINR, a signal-to-noise ratio SNR, and a current power normalization maximum value of the local measurement, so that the probe link determines whether to access the ultra-dense network as an active link, where the current power normalization maximum value includes a maximum value of the normalized transmit power of each active link, the normalized transmit power of the probe link, and the normalized external interference power of each external link in the ultra-dense network.

8. The self-organizing apparatus of claim 7, the receiver of the probing link, in particular for determining

Wherein,

representing a maximum achievable SINR, SINR of the sounding link_L(t) current SINR value, SNR, representing a local measurement of the probing link_LA locally measured SNR value representing the probing link,

represents the current power normalized maximum value,

9. An ad-hoc device of active links in an ultra-dense network, comprising:

a power updater for self-organizing, configured to, when a detection link transmits a detection signal with a fixed power, update, for each active link, a transmission power at a next time according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmission power value, and a current power normalized maximum value; iteratively updating the transmission power of each active link with time according to the updated transmission power at the next moment until the locally measured SINR value of the active link converges to a constant, so that the detection link obtains the maximum achievable SINR to determine whether to access the ultra-dense network as an active link;

wherein the current normalized maximum power value comprises a maximum value of the normalized transmit power of each active link, the normalized transmit power of the probe link, and the normalized external interference power of each external link in the ultra-dense network;

10. The self-organizing apparatus of claim 9, the power updater for self-organizing, in particular for updating the transmit power at the next time instant, to be

represents the current power normalized maximum value,

11. An apparatus for ad-hoc optimization of ultra-dense networks, comprising:

a power updater for self-organizing, configured to, when the transmitter of the probe link transmits the probe signal, respectively update the transmit power at the next time for each active link in the ultra-dense network according to a respective target signal-to-interference-and-noise ratio SINR, a locally measured current SINR, a locally measured normalized noise power value, a current transmit power value, and a current power normalized maximum value; iteratively updating the transmitting power of each active link along with time according to the transmitting power of the next moment, and triggering the receiver of the detection link until the locally measured SINR value of the active link is converged to a constant;

the access controller of the detection link is used for accessing the detection link as an active link to the ultra-dense network when the maximum achievable SINR obtained by the receiver of the detection link is greater than or equal to the target SINR of the detection link;

a power updater for self-optimization, configured to update respective transmit powers for the probe link and each of the active links according to a respective target SINR, a locally measured current SINR, a current transmit power value, and a current power normalization maximum value when the access controller of the probe link controls the probe link to access the super-dense network as an active link, until a working SINR of each of the probe link and each of the active links is greater than the respective target SINR;

wherein the current normalized maximum power value includes a maximum value of the normalized transmit power of each active link, the normalized transmit power of the probe link, and the normalized external interference power of each external link in the ultra-dense network.

12. The self-organizing optimizing device of claim 11, further comprising: