KR20200041235A - Method for controlling access for machine-type communication and allocation pilot signal in mimo system - Google Patents

Abstract

Disclosed is a method for controlling access and allocating a pilot signal for mechanical communication. The method comprises: a step of allowing a base station to broadcast an access blocking factor with mechanical communicating devices in a current time slot; a step of allowing each mechanical communicating device to generate a random number and to determine whether to proceed with a random access process; a step of allowing the mechanical communicating device to select a pilot from a set of pilots when the random access process is performed and to transmit the selected pilot to the base station; a step of allowing the base station to generate a random access response in response to the selected pilot and to check whether or not the mechanical communicating device has the strongest uplink signal gain based on the random access response when the generated random access response is transmitted to the mechanical communicating device; a step of allowing the mechanical communicating device having the strongest uplink signal gain to repeatedly transmit the pilot; and a step of allowing the base station to allocate dedicated payload pilots to the mechanical communicating device having the strongest uplink signal gain. The access blocking factor is dynamically controlled for each time slot.

Description

METHOD FOR CONTROLLING ACCESS FOR MACHINE-TYPE COMMUNICATION AND ALLOCATION PILOT SIGNAL IN MIMO SYSTEM

An embodiment according to the concept of the present invention relates to a method for allocating access control and pilot signals for mechanical communication, and more particularly, a method for allocating random access control and pilot signals in a large-scale MIMO environment for conflict resolution.

^{3GPP LTE (3 rd generation partnership project} long term evolution) system or IoT (internet of things) in the network of the physical device, such as a car, a smart meter, a sensor, and a smart device, the machine-type communication (machine-type communication (MTC) ) Is connected and controlled in real time without human intervention. The potential number of devices in IoT systems is expected to reach tens of billions, but radio resources are often scarce. Connecting a huge number of devices in limited bandwidth requires the development of new access solutions that can increase resource efficiency and reduce control overhead and access latency.

The main problems of IoT are low power, lack of spectrum resources, and short range of communication. Many wireless technologies have already been developed for IoT networks such as ZigBee, Wi-Fi, and Long Range (LoRa). However, communication providers currently prefer to develop technologies that are compatible with cellular networks, such as LTE-M, NB-IoT. In addition, cellular networks can predict and control interference well. Therefore, it is useful in high density networks such as IoT scenarios. For this reason, there are many studies on cellular networks that can respond to IoT needs.

  Because of the limited cellular frequency band, large-scale MIMO technology has been proposed to improve spectral efficiency. Large-scale MIMO operates in a time-division duplexing (TDD) mode, where channel estimation is achieved by using uplink pilots and realizing channel interoperability for estimating downlink channels. Nevertheless, in a dense mechanical communication device (MTC device) environment, channel estimation faces an important problem in certain characteristics.

  First, the number of pilot sequences is limited by the dimension of the coherence interval of the channel. This means that if the number of devices becomes very large, the number of pilots becomes insufficient. Therefore, the pilot allocation problem in a compact device scenario is important.

Second, not all devices are activated simultaneously and frequently at the same time. However, each device sporadically transmits data to the base station at random moments. Therefore, the network system must allocate pilots to the mechanical communication device according to a dynamic and adaptive mechanism. One common mechanism is to allow each device to randomly select one pilot and send it to the base station, but it results in a pilot collision.

In order to resolve the pilot collision, a trust propagation algorithm has been proposed that decontaminates the pilot signal and increases system throughput in exchange for excessive access delay. Another protocol, called strongest-user collision resolution (SUCR), also solves this problem: The SUCR protocol selects a mechanical communication device with the strongest channel signal gain in a distributed fashion as a competition winner. The protocol can increase the possibility of conflict resolution with low access delay.

 Also, in 3GPP LTE Release 11, access class barring (ACB) technique, physical random access channel resource separation technique, slotted access technique, dynamic allocation of random access (RA) resource, mechanical Techniques such as clustering of communication devices, and back-off techniques are provided to control random access of MTC devices.

Of these, ACB is one of the most efficient solutions to reduce traffic overload. An ACB technique with a fixed blocking factor has been proposed, and using a blocking factor as a constant can simplify the system and reduce the computational cost, but cannot achieve maximum performance. In addition, a traffic aware ACB has been proposed to alleviate congestion due to MTC communication.

H. He, Q. Du, H. Song, W. Li, Y. Wang, and P. Ren, “Traffic-aware acb scheme for massive access in machine-to-machine networks,” in 2015 IEEE International Conference on Communications , June 2015, pp. 617-622.

The present invention has been devised to solve the above problems, and the access control and pilot signal allocation method for the mechanical communication of the present invention has an access class barring (ACB) factor dynamically in each time slot. It aims to be adjusted.

In order to achieve the above object, the access control and pilot signal allocation method for the mechanical communication of the present invention includes the steps of broadcasting an access blocking factor by the base station to the mechanical communication devices in the current time slot, and each mechanical communication The apparatus generates a random number and determines whether to perform a random access procedure, and when performing the random access procedure, the mechanical communication apparatus selects a pilot from a set of pilots and transmits the selected pilot to the base station. Wow, the base station generates a random access response in response to the selected pilot, and when the generated random access response is transmitted to the mechanical communication device, the mechanical communication device has the strongest uplink based on the random access response. Checking whether it has a signal gain, and the strongest upring And repeatedly transmitting a pilot by a mechanical communication device having a signal gain, and allocating dedicated payload pilots to the mechanical communication device having the strongest uplink signal gain by the base station, and blocking the access. The argument is dynamically adjusted for each time slot.

The step of broadcasting the access blocking factor by the base station may include estimating the number of mechanical communication devices for which the base station intends to select the pilot, and the next time slot based on the estimated number of mechanical communication devices. And calculating an access blocking factor.

The step of calculating the access blocking factor of the next time slot may include the ratio of the number of mechanical communication devices that want to select the pilot in the current time slot to the number of mechanical communication devices successfully accessed in the current time slot. Use to calculate the access blocking factor of the next time slot.

The number of mechanical communication devices successfully accessed in the current time slot is calculated using the probability that there will be collision devices that will select the same pilot from each other among the mechanical communication devices undergoing the random access procedure.

The number of mechanical communication devices successfully accessed in the current time slot is calculated using the probability that the collision devices are present, and the probability that the mechanical communication device having the strongest uplink signal gain repeatedly transmits a pilot. do.

The number of mechanical communication devices performing the random access procedure counts the number of idle pilots among the total number of pilots available in the current time slot, and calculates a probability that the pilots are idle using the count result Then, the number of machine-type communication devices performing the random access procedure is calculated using the calculated probability of being idle.

The access control and pilot signal allocation method for the mechanical communication of the present invention as described above increases the probability of successful access between the mechanical communication devices and the base station based on the SUCR protocol by using the access control implemented by the dynamic ACB technique. It has the effect.

1 is a diagram illustrating a cellular network having mechanical communication devices according to an embodiment of the present invention.
2 is a diagram showing a pilot block and a payload data block model according to an embodiment of the present invention.
3 is a view showing a procedure of the ACB-SUCR technique according to an embodiment of the present invention.
4 to 5 is a graph showing the result of simulating the ACB-SUCR method according to an embodiment of the present invention.

The present invention proposes an access control strategy using ACB and a pilot allocation strategy using SUCR protocol.

Hereinafter, the present invention will be further described with reference to examples and drawings according to the present invention.

1 is a view showing a cellular network having mechanical communication devices according to an embodiment of the present invention, and FIG. 2 is a view showing a pilot block and payload data block model according to an embodiment of the present invention.

라고 가정하자. Referring to FIG. 1, a single cell time division large-scale MIMO network 10 includes N single antenna mechanical communication devices 200 and 300, and a base station (BS) 100 equipped with M antennas is provided. Serviced by There is a certain number of active devices 200 each time, and the rest of the devices 300 are idle. Devices share orthogonal pilot sequences, and the symbol length of each sequence is

Suppose

, 이하, '관찰 기간'이라 한다.) 동안 기계형 통신 장치들의 전송을 관찰한다. 관찰 기간을

길이를 갖는

개의 이산 랜덤 액세스 슬롯들(RASTs)로 나눈다. 여기서,

는 채널 간섭성 간격보다 작거나 같다. First, as shown in FIG. 2, a pilot random access procedure is performed in a time slot. One frame time (

, Hereinafter, referred to as the 'observation period'). Observation period

Having length

Divided into two discrete random access slots (RASTs). here,

Is less than or equal to the channel coherence interval.

동안 i-번째 RAST는

로 표시된다.

는 시간 t_{i -1}에서 시작해서 시간 t_i에서 끝난다. 각 서브 프레임이 하나의 슬롯으로 전송된다고 가정하자. 또한, 기계형 통신 장치들의 전송은 드물고(infrequent) 각 기계형 통신 장치는 독립적으로 현재 슬롯에서 활성화되기를 원한다.

를

동안 신규 도착자의 수로 나타낸다. Observation period

While i-th RAST

It is indicated by.

Starts at time t _{i -1} and ends at time t _i . Suppose that each subframe is transmitted in one slot. Also, transmission of machine-type communication devices is infrequent and each machine-type communication device wants to be activated independently in the current slot.

To

While it is represented by the number of new arrivals.

는 랜덤 액세스 요청들의 확률 밀도 함수인 활성화 트래픽 분산

와 총 장치들의 수 N을 따른다. 그러면,

는 다음과 같이 정의된다.

Is the active traffic distribution, which is a function of the probability density of random access requests.

And the number N of total devices. then,

Is defined as

[Equation 1]

The SUCR protocol can resolve the pilot collision with low access delay, but if the number of new arrivals is very large, the probability of successful access decreases. Therefore, applying an ACB scheme to control the number of accessed mechanical communication devices is an efficient solution. The ACB mechanism may provide access priority to the terminal based on the assigned access class.

3 is a view showing a procedure of the ACB-SUCR technique according to an embodiment of the present invention. Referring to FIG. 3, the procedure of the ACB-SUCR technique according to an embodiment of the present invention includes access control using the ACB technique and pilot allocation using the SUCR protocol.

Access control using ACB technique

를 생성한다. When congestion occurs, use ACB techniques to prevent access to mechanical communication devices and reduce network overload. In each slot, the base station broadcasts the ACB factor and cutoff time to all mechanical communication devices. Each mechanical communication device is a random number

Produces

가 ACB 인자보다 적으면, 기계형 통신 장치는 랜덤 액세스 절차를 진행한다. 즉, 기계형 통신 장치는 ACB 기법을 통과한 경우에만 랜덤 액세스 절차를 진행한다.

가 ACB 인자보다 크면, 기계형 통신 장치는 임의의 시간동안 랜덤 액세스 절차가 차단되고 난수를 재생성해야 한다.if

If is less than the ACB factor, the machine-type communication device proceeds with a random access procedure. That is, the mechanical communication device performs a random access procedure only when it passes the ACB technique.

If is greater than the ACB factor, the machine-type communication device must block random access procedures for some time and regenerate random numbers.

The conventional ACB technique sets a fixed blocking factor during the network access procedure of the machine-type communication devices. Among them, the traffic aware ACB changes the blocking factor according to the number of times the device arrives to reduce the access delay and increase the probability of success in access.

However, in the present invention, the base station selects a blocking factor by optimizing the probability of successful access. The base station calculates a blocking factor based on the number of arrivals in the current slot to obtain the maximum access success probability, and broadcasts the calculated blocking factor for use in the next slot.

Pilot assignment using SUCR protocol

Step 1-random pilot sequence selection

각각은 각 RA 슬롯에서 동일한 확률

로 파일럿들의 세트 P₀로부터 임의로 파일럿을 선택하고, 선택된 파일럿을 기지국으로 전송한다.Mechanical communication devices

Each is the same probability in each RA slot

A pilot is randomly selected from the set of pilots P ₀ , and the selected pilot is transmitted to the base station.

Step 2-the base station PRAR , ACB factor, and information of idle pilots is generated and broadcast

After the base station receives the pilot signal, it generates a precoded random access response (PRAR) and broadcasts the generated PRAR to all activated mechanical communication devices.

Step 3-Contention resolution using pilot iteration and pilot reselection

Each of the activated mechanical communication devices receives PRAR information and checks whether it has the strongest uplink signal gain based on the PRAR information. At this time, only the mechanical communication device having the strongest uplink signal gain must repeatedly transmit the random access pilot.

Step 4-Base Station Assigns Dedicated Payload Pilots

The base station receives repetitive random access pilots transmitted by the machine-type communication devices during step 3. The base station estimates the channel gain of each mechanical communication device that has transmitted the pilot during step 3, and decodes the corresponding message using this. When the base station decodes successfully, dedicated payload pilots are allocated to the corresponding machine-type communication device.

In step 4, resource allocation in the downlink is similar to the precoded response in step 2. The random access procedure is repeated after a given interval. Mechanical communication devices that do not receive dedicated payload pilots during step 4 select an integer value as an arbitrary wait time. After any waiting time, the failing mechanical communication devices retry random access in a new random access slot.

In the following, the optimization problem is formulated to maximize the probability of success in access. In a large-scale mechanical communication system, scarce resources cannot afford the random access of a large number of mechanical communication devices. Therefore, the effectiveness of resource costs should be considered. Here, the probability of successful access is defined as a ratio between the number of mechanical communication devices that successfully access the base station at the observation time and the total number of mechanical communication devices to be activated.

[Table 1] defines the parameters used in this specification.

Variables Interpretation N Number of MTCDs M Number of antennas of BS

Number of orthogonal pilot sequences

Duration of observation (ms)

Number of RASTs

the length of a RAST (ms) K _i Number of new arrival MTCDs during i ^th time slot K _{C, i} Number of MTCDs passing the ACB scheme

Number of successful access MTCDs during i ^th time slot p _{ACB, i} ACB factor in i ^th time slot

이다. 또한, 간섭성 리소스의 한계 때문에

이다. 각 활성화된 기계형 통신 장치는 각 타임 슬롯에서 무작위로

개의 파일럿 시퀀스들 중에서 하나의 파일럿을 선택한다. If P ₀ is represented as a set of orthogonal pilots, P ₀ =

to be. In addition, due to the limitation of coherent resources

to be. Each activated mechanical communication device is randomized in each time slot.

One pilot is selected from among the pilot sequences.

)을 갖는 파일럿을 전송하고, 그렇지 않으면

이다.

을 기계형 통신 장치 k와 기지국 사이의 채널 벡터라 하고, 전파 모델이 다음의 두 조건들을 만족하는 채널들을 가지고 있다고 가정하자.If the mechanical communication device k tries to access it, it has a non-zero power (

), Otherwise

to be.

Let b be the channel vector between the mechanical communication device k and the base station, and assume that the propagation model has channels satisfying the following two conditions.

는 반드시 양수(strictly positive)이고, 각 기계형 통신 장치 k는 이 값을 알고 있다.이러한 채널들은 채널 강화(hardening)와 점근적으로 좋은 전파(asymptotic favorable propagation)를 제공한다. here,

Is strictly positive, and each mechanical communication device k knows this value; these channels provide channel hardening and asymptotic favorable propagation.

The base station can obtain the number of pilot collisions and the number of successes, but cannot know the number of mechanical communication devices requesting pilots. In order to perform a dynamic access control mechanism according to an embodiment of the present invention, the base station needs to estimate the number of mechanical communication devices to select pilots.

를 찾기 위해 추정 기법에 기반한 동적 접근 제어 알고리즘을 설명한다. i-번째 슬롯에서의 기계형 통신 장치 도착 횟수는 k_i이다. 실제로, 장치의 도착 횟수는 다음의 세가지 요소들에 의해 결정된다: 슬롯 i에서 새로 활성화된 장치들의 수, 랜덤 액세스 실패에 의해 슬롯 i에서 네트워크에 다시 액세스 해야하는 백로그된(backlogged) 장치들의 수, 및 이전 슬롯들에서 ACB 기법으로 백로그된 장치들의 수. ACB 기법을 통과한 K_C,i 장치들이 있다. T_A 동안 N개의 활성화된 기계형 통신 장치들을 갖는 셀에서, ACB 기법 후 SUCR 프로토콜에 의한 파일럿 할당을 적용하는 K_C,i 장치들이 있고, 각 슬롯에서 사용 가능한 파일럿들의 수는

이다. Optimal ACB factor for next time slot

In order to find, a dynamic access control algorithm based on an estimation technique is described. The number of arrivals of the mechanical communication device in the i-th slot is k _i . Indeed, the number of devices arriving is determined by three factors: the number of newly activated devices in slot i, the number of backlogged devices that need to access the network again in slot i due to random access failure, And number of devices backlogged with ACB technique in previous slots. There are K _{C, i} devices that have passed the ACB technique. T _A While in a cell with N active mechanical communication devices, there are K _{C, i} devices that apply pilot allocation by SUCR protocol after ACB technique, and the number of pilots available in each slot is

to be.

중에서 유휴(idle) 파일럿들의 수

를 카운트한다. 파일럿들이 유휴 상태일 확률

은 다음과 같이 계산할 수 있다.Base station is the total number of pilots available in the i-th slot

Number of idle pilots

Counts. The probability that the pilots are idle

Can be calculated as

[Equation 2]

The probability that the pilot is idle can also be determined as follows.

[Equation 3]

라 하면, i-번째 슬롯에 있는 경쟁자들의 수 K_C,i 는 다음과 같이 추정할 수 있다.

S, the number of competitors in the i-th slot K _{C, i} can be estimated as follows.

[Equation 4]

From K _{C, i} and blocking factor p _{ACB, i in the} i-th slot, the number of mechanical communication devices in the (i + 1) -th slot can be estimated as follows.

[Equation 5]

이다.At this time, it is possible to improve the probability of access success of the system by adaptively adjusting the ACB factor. Given K _i active devices during the i-th time slot, the number of devices passing the ACB technique is

to be.

Given the competitors K _{C, i} , the probability that there are collision devices C can be represented by the probability that the devices C will select the same pilot sequence among the devices K _{C, i} . The probability is as follows.

[Equation 6]

로 표시되는 이항 분포를 따른다.Where C is

Follow the binomial distribution represented by.

로 정의된다. i-번째 타임 슬롯동안 성공적으로 액세스한 기계형 통신 장치들의 수

는 다음과 같이 계산할 수 있다. The probability that there are devices C competing to select a pilot sequence and only the strongest device repeats this pilot in step 3 is

Is defined as Number of mechanical communication devices successfully accessed during the i-th time slot

Can be calculated as

 [Equation 7]

로 나타내면 다음과 같다.the probability of successful access during the i-th slot

It is represented as follows.

[Equation 8]

Here, K _i represents the number of mechanical communication devices newly arrived during the _i -th time slot.

을 최대화하는 ACB 기법의 ACB 인자 p_AVB 와 파일럿 시퀀스 길이

의 값을 결정하면 최적의

는 다음과 같이 결정될 수 있다.At this time, the probability of successful access

ACB factor p _AVB and pilot sequence length of ACB technique to maximize

Determining the value of

Can be determined as follows.

[Equation 9]

This approach aims to limit the number of competitors in order to maximize the probability of access success in an overload situation. The dynamic access control algorithm based on the estimation is shown in [Table 2] below. Finally, the average probability of successful access during the observation time T _A may be determined as follows.

[Equation 10]

One

: 셀에서 사용 가능한 파일럿의 수

: Number of pilots available in the cell 2

: Number of idle pilots counted in i-th time slot 3 // p _{ACB, i} : ACB factor in i-th time slot 4 p _{ACB, i} = 1 5 i = 0 6 for i ≤ I _A do 7 Base station

Calculation 8 By [Equation 2]

Calculation 9 By [Equation 3]

Calculation 10 By [Equation 5]

Calculation 11

12 Calculate p _{ACB, i + 1} by [Equation 9] 13 i = i + 1 14 end for

를 가지며 액세스 제어 단계의 복잡도는 매 타임 슬롯마다

로 설정된다. 따라서, I_A 타임 슬롯 동안 총 복잡도는

이다.In Table 1, the estimation step is computational complexity.

And the complexity of the access control step is every time slot

Is set to Thus, the total complexity during the I _A time slot

to be.

4 to 5 is a graph showing the result of simulating the ACB-SUCR method according to an embodiment of the present invention. In the simulation, the radius of the cell is 250 m, and the device is uniformly distributed in the cell at a distance of 25 m from the base station. It is assumed that the mechanical communication devices and the base station in the cell transmit pilots at maximum power.

Three channel models are considered for propagation.

, 여기서

는

단위 행렬을 나타낸다.Channel model 1: uncorrelated Rayleigh fading,

, here

The

Unit matrix.

는

를 갖는 기지국에서 균일한 선형 어레이로 간주된다. 여기서, r은 0.7로 설정된 인접한 안테나들 j 와 i 사이의 상관 계수이고,

는 기계형 통신 장치들 k과 기지국 사이의 각도이다. 이 모델에서 일부 방향은 다른 방향에 비해 채널이 더 강하다.Channel model 2: correlated rayleigh fading

The

It is regarded as a uniform linear array at the base station having. Here, r is a correlation coefficient between adjacent antennas j and i set to 0.7,

Is the angle between the mechanical communication devices k and the base station. In this model, some directions have stronger channels than others.

Channel Model 3: This model is a line-of sight (LOS) propagation using:

Channel model 1 and channel model 2 follow a logarithmic normal distribution with a path loss index of 3.8 and a shadow fading of 10 dB standard deviation. Channel model 3 has a path loss index of 2.5 and a logarithmic standard deviation with a standard deviation of 4 DB.

SUCR: This method can efficiently resolve pilot collisions that occur when devices randomly select a pilot sequence to access the network. Each device with the strongest channel gain is assigned one pilot.

RA wo ACB: This is a traditional random access procedure without ACB technique to control the number of arrival devices. If more than one device selects the same pilot sequence in an access attempt, the network cannot be accessed.

SUCR with fixed ACB: This uses a fixed ACB factor to limit the number of arrival devices, and applies the SUCR protocol for pilot allocation.

RA with fixed ACB: Similar to SUCR with fixed ACB, access control using a fixed ACB factor (p _ACB = 0.5) is applied, and devices that pass the ACB technique realize a random access procedure.

SUCR with traffic-aware ACB: Access control is realized based on the traffic-aware ACB, and the SUCR protocol performs pilot allocation.

RA with traffic-aware ACB: After controlling the number of new arrivals by the traffic-aware ACB technique, a random access procedure is performed.

,

,

랜덤 액세스 슬롯들.Here, in order to confirm the effect on the collision resolution capability, a simulation was performed to show the possibility of collision resolution by changing the number of base station antennas for the three channel models mentioned. The simulation setup for this scenario

,

,

Random access slots.

Here, the possibility of conflict resolution is defined as follows.

는

경쟁 장치들을 가지는 파일럿 충돌을 해결할 확률이고,

는

일 때, 가장 강한 장치만이 파일럿을 반복할 확률이다. here,

The

The probability of resolving a pilot collision with competing devices,

The

Is the probability that only the strongest device will repeat the pilot.

Figure 4 shows that the ACB-SUCR method according to an embodiment of the present invention is affected by the propagation channel model. The first observation is that the uncorrelated Rayleigh fading model outperforms two other scenarios, and the larger the number of antennas, the relatively difference in performance obtained by uncorrelated Rayleigh fading and correlated Rayleigh fading is relatively apparent. In addition, the result of the visible distance model is inferior to that of Rayleigh fading. The probability of collision resolution is low when M is small, and increases when the number of base station antennas is larger.

In particular, in FIG. 4 (a), P _resleved is about 15% for the Rayleigh fading model, and almost 0% for the LoS model when M = 1. When M increases to 40 antennas, the probability of collision resolution is 50% for the LoS model and about 78% for the Rayleigh fading model. In FIG. 4 (b), P _resleved is about 9% for LoS and about 32% for Rayleigh fading when M = 1. However, when M goes to 40 antennas, it increases to 70-89%.

Therefore, it was concluded that the ACB technique can improve the possibility of conflict resolution for the existing SUCR protocol in the three-channel model and the existing RA protocol. In addition, it can be seen that the performance of the SUCR protocol using the dynamic ACB technique for the LoS case is significantly improved. Another observation is that the proposed technique with a three-channel model can resolve collisions twice as compared to conventional RA techniques.

In order to compare the performance of the proposed method with the method proposed in this paper, a simulation with the results of FIGS. 5 and 6 was realized. All these simulations use uncorrelated Rayleigh fading and the path loss index is 3.8. It is assumed that the base station and the mechanical communication devices in the cell operate at the maximum power giving the same SNR in both directions. Consider a congested scenario where π = 50 during IA = 100 random access slots and the total number of active devices is N.

It can be seen that the improvement in probability of access success achieved by ACB-SUCR proposed in FIG. 5 is remarkable compared to the others. Initially, if the number of active mechanical communication devices is small, most of the mechanical communication devices can successfully access the network in all ways.

Obviously, the probability of access success decreases as the total number of active devices increases. However, the probability of successful access to the proposed ACB-SUCR is still higher than the others. Two methods of SUCR using traffic-aware ACB and dynamic ACB can handle up to 10000 mechanical communication devices, but the other method is effective only under 5000 mechanical communication devices.

일 때 시스템 성능은 포화 상태가 된다. 유한 개의 파일럿 시퀀스의 수 때문에, 기지국 안테나의 수가 30 이상으로 증가하더라도 액세스 성공 확률은 포화 상태가 된다.In FIG. 6, the probability of access success as a function of the number of Gadget antennas is shown for different schemes. It can be seen that the simulation result of SUCR using ACB technique provides higher performance than the original SUCR technique. The probability of successful access is small at M = 1, but increases significantly as the number of base station antennas increases. But,

When the system performance is saturated. Because of the finite number of pilot sequences, the probability of access success is saturated even if the number of base station antennas increases to 30 or more.

The present invention is an invention for solving intra-cell pilot collision in a complex multiple MIMO system by combining ACB and SUCR techniques. Simulation results show that the ACB-SUCR method can increase the probability of access success and reduce pilot collisions compared to other methods. In addition, the proposed dynamic ACB technique improves the access success performance of conventional RAB and SUCR techniques compared to traditional ACB and traffic-aware ACB techniques.

The present invention has been described with reference to one embodiment shown in the drawings, but this is merely exemplary, and those skilled in the art will understand that various modifications and other equivalent embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

10; Cellular network
100; Base station
200; Active devices
300; Idle devices

Claims (6)

Broadcasting the access blocking factor to the mechanical communication devices in the current time slot;
Each mechanical communication device includes generating a random number and determining whether to proceed with a random access procedure;
In the case of performing a random access procedure, the mechanical communication apparatus selecting a pilot from a set of pilots and transmitting the selected pilot to the base station;
When the base station generates a random access response in response to the selected pilot, and transmits the generated random access response to the mechanical communication device, the mechanical communication device generates the strongest uplink signal gain based on the random access response. Checking whether or not to have;
Repeatedly transmitting a pilot by the mechanical communication device having the strongest uplink signal gain; And
And the base station assigning dedicated payload pilots to the mechanical communication device having the strongest uplink signal gain.
The access blocking factor is dynamically adjusted for each time slot, Access control and pilot signal allocation method for a mechanical communication.
According to claim 1,
The step of the base station broadcasting the access blocking factor,
Estimating the number of mechanical communication devices for the base station to select the pilot; And
And calculating an access blocking factor of the next time slot based on the estimated number of mechanical communication devices.
According to claim 2,
Calculating the access blocking factor of the next time slot,
Calculating an access blocking factor of the next time slot using a ratio of the number of mechanical communication devices that want to select the pilot in the current time slot and the number of mechanical communication devices successfully accessed in the current time slot. A method for access control and pilot signal allocation for mechanical communication.
According to claim 3,
The number of mechanical communication devices successfully accessed in the current time slot is:
Access control and pilot signal allocation method for a mechanical communication, characterized in that it is calculated by using the probability that there will be collision devices to select the same pilot from each other among the mechanical communication devices performing the random access procedure.
According to claim 4,
The number of mechanical communication devices successfully accessed in the current time slot is:
Access control and pilot signal allocation method for mechanical communication, characterized in that, with the probability that the collision devices are present, the mechanical communication device having the strongest uplink signal gain is repeatedly calculated using a probability of transmitting a pilot. .
According to claim 4,
The number of mechanical communication devices that perform the random access procedure,
Count the number of idle pilots among the total number of pilots available in the current time slot, calculate the probability that the pilots are idle using the count result, and use the calculated probability of being idle to perform the random access procedure. Access control and pilot signal allocation method for a mechanical communication, characterized in that for calculating the number of mechanical communication devices proceeding.

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