CN114501478A - NB-IoT network resource scheduling method based on rate-delay - Google Patents
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Abstract
The invention relates to a rate-delay-based NB-IoT network resource scheduling method, and belongs to the technical field of wireless communication of the Internet of things. The method comprises the following steps: s1: constructing a rate optimization model, including power distribution optimization and uplink scheduling optimization; then, obtaining an optimized uplink power scheduling path by using the model; s2: constructing a delay optimization model, and setting constraint conditions including scheduling waiting time, RUC transmission time and retransmission time; then, the model is utilized to obtain the transmission power waiting time; s3: and constructing a self-adaptive rate-delay selection mechanism, and calculating to obtain the optimized throughput by combining the optimized uplink power scheduling path and the transmission power waiting time. The invention improves the transmission rate of the NB-IoT uplink and reduces the delay with lower complexity under the condition of not changing the transmission power; the throughput is increased while the power consumption is reduced, and the network performance is optimized.
Description
Technical Field
The invention belongs to the technical field of wireless communication of the Internet of things, and relates to a rate-delay-based NB-IoT network resource scheduling method.
Background
Nowadays, more and more electronic devices and machines become indispensable components of people's life, and social productivity has also been further promoted because of the high efficiency of electronic devices. In the face of hundreds of millions of electronic devices, how to effectively manage the devices, enhance the device maintenance, reduce the cost and the like becomes a problem which needs to be solved urgently. With the increasing number of low-power-consumption internet-of-things equipment terminals, the traditional LTE communication cannot meet the rapidly expanding machine type communication requirements. NB-IoT is an emerging technology widely used worldwide, and a single sector thereof has performance advantages of supporting tens of thousands of connections, low power consumption, etc., effectively expanding the coverage area of the entire system, and increasing the number of devices served by the system by thousands of devices. Although NB-IoT is designed to meet the challenge of connecting a larger number of devices, the existing NB-IoT resource scheduling algorithm is not satisfactory in the face of the requirement of huge connection of mass machine type communication services and different QoS requirements under various service scenarios due to limited system resources.
Because NB-IoT only occupies a bandwidth of 180kHz, the number of single base station devices can reach 20 thousands, transmission delay is often 10+ seconds, and a great deal of work is done by researchers to solve the problems of system delay increase, access success rate reduction and the like caused by large-scale access of devices. There are several papers that currently investigate NB-IoT resource allocation and scheduling issues. Some of the existing approaches do not develop an optimization function according to a given standard, while others do not specifically design scheduling policies for NB-IoT, e.g., when there are multiple RUCs (resource unit configurations) in NB-IoT, the scheduling policies used are still specified by the 3GPP standard. In some documents, the influence of multi-device optimization and control plane optimization on resource scheduling is intensively studied, but the influence of throughput, delay and the like on transmission power is neglected. Azari et al believe that: the random access channel, the uplink shared channel, the downlink control channel, etc. should not be scheduled individually. Furthermore, to investigate the impact of scheduling on latency and battery life, they proposed a traceable queuing model, but do not consider multi-tone allocation and throughput optimization. However, when studying the performance of the RUC under different traffic types, relevant researchers have used three scheduling strategies: polling scheduling, proportional fair scheduling and maximum throughput scheduling, and designing a corresponding scheduling strategy for each resource unit configuration according to an optimization target respectively to measure the performance difference among all resource unit configurations and select the optimal configuration.
The NB-IoT resource allocation research mentioned above solves the problems in the respective scenarios, but with the continuous abundance of NB-IoT application scenarios and the increasing number of access network devices, it is of urgent practical significance to optimize the QoS requirements for different service scenarios. Therefore, it is necessary to deeply research the NB-IoT resource scheduling technology and design a reasonable and efficient resource scheduling algorithm to improve the reliability of data transmission and network throughput.
Disclosure of Invention
In view of this, an object of the present invention is to provide a rate-delay based NB-IoT network resource scheduling method, which, according to NB-IoT uplink characteristics, improves data transmission rate, reduces delay, and simultaneously improves network throughput, thereby optimizing network performance, on the basis of implementing effective data transmission in an NB-IoT network.
In order to achieve the purpose, the invention provides the following technical scheme:
a NB-IoT network resource scheduling method based on rate-delay adopts a self-adaptive allocation scheduling mechanism aiming at different resource unit configurations in NB-IoT, and realizes the optimization of performance indexes such as delay, throughput and packet loss rate by resource allocation among subcarriers of the same equipment and resource allocation analysis among interfered equipment; through the research on the relation between the throughput and the time delay, a self-adaptive power distribution method is provided, and an NB-IoT throughput optimization formula is extracted.
The method specifically comprises the following steps:
s1: constructing a rate optimization model, including power distribution optimization and uplink scheduling optimization; then, obtaining an optimized uplink power scheduling path by using the model;
s2: constructing a delay optimization model, and setting constraint conditions including scheduling waiting time, RUC (resource unit configuration) transmission time and retransmission time; then, the model is utilized to obtain the transmission power waiting time;
s3: and constructing a self-adaptive rate-delay selection mechanism, and calculating to obtain optimized throughput by combining the optimized uplink power scheduling path and the transmission power waiting time, namely realizing the maximization of the throughput in the resource allocation process.
Further, in step S1, constructing a rate optimization model, specifically including the following steps:
s11: establishing a rate optimization function:
and
wherein ,fRThe function of the rate is represented by,
representing the allocated rate component in device d,
which represents the transmit power of the device d,
representing the rate of device d at a time slot or subcarrier in cell C,
represents the minimum rate of device d in cell C; c represents the NB-IoT network cell index in C, T represents the index of the subframe T available to the device, and s represents the subcarrier index available to the device; c denotes NB-IoT network system, T denotes device usable subframe, Dc denotes device set in cell C, S usable subcarrier;
finding the optimal uplink power, wherein
The calculation formula of (2) is as follows:
wherein ,DaDenotes a device in cell a, j denotes an interfering device, a denotes a cell index belonging to C,
representing the channel gain between device d and the base station in cell c,
represents the transmission power of the interfering device j,
representing the channel gain between interfering device j and the base station in cell c,
representing the rate component, W, in the interfering device jnRepresenting the noise power;
s12: the constraint conditions are added as follows:
①
this formula represents: when non-overlapping devices are deployed in the same cell, the resource unit is ensured to be used by only one device, and no internal interference exists;
②
this formula represents: a power constraint, i.e. the total power of a device over time t does not exceed its total power in the uplink; wherein, WmaxRepresents an uplinkMaximum power of devices in the link;
s13: resource unit constraints are added so that the optimizer selects at most one of the four RUCs:
③
wherein ,
indicating the number of SC (sub-carriers) divided by the device,
representing the number of TSs scored; wherein SC and TS are continuous and uninterrupted; constraint c represents the SC given to device d from the frequency domain;
s14: introducing binary components
Represents an index of the RUC, and
s15: each device has only one of the RUCs,
and
assume only two values at slots or SCs, and if no slots or SCs are allocated to the device, it is represented as 0, and it is recorded as 0
And
they represent the two aspects of the RUCs in the time domain and the frequency domain, respectively;
allocating each TS a number of SCs equal to
Indicates that TS in SC is equal to
S16: then the following equation is given for only one RUC per device:
steps S14-S16 describe the constraint of 4 RUCs, and step S14 ensures
With only a unique value, step S16 ensures that the number of SCs and TSs per device is equal to the set number of RUCs.
Further, in step S2, the delay optimization model is constructed as follows:
wherein ,fLRepresenting a delay function, e representing a constant close to 0; when in use
When not 0, in the function, taking into account the different shapes of the RUCs
Varies from 1 to 0 when { u, c, t } is arbitrary; when not equal to 0, each RUC goes from 1 to 0 in the same number of s and ∈.
Further, in step S3, an adaptive rate-delay selection mechanism is constructed, that is, a multi-objective optimization problem is constructed, where the expression is:
wherein ,fRLRepresenting a rate-delay optimization function, KR and KLTwo weights for rate and delay, respectively, both values being 1 if rate and delay are equally important.
Further, in order to reasonably allocate NB-IoT resources, the adaptive power allocation method provided in the present invention is mainly used in NB-IoT uplink scheduling process, and a scheduling model diagram thereof is shown in fig. 2. The scheduling process is mainly divided into the following two parts:
first, User Equipment (UE) priority ranking is performed: when the UE sends a lead code of RA (access channel identification) and the eNB detects the lead code sent by the UE, scheduling starts; at a certain moment, when a plurality of UE (user equipment) waiting for scheduling exist in a scheduling queue, the UE in the queue is reordered according to a priority algorithm, and the UE with high priority is selected to start to perform the next scheduling;
then, uplink (Up-Link, UL) resource allocation is carried out: the method mainly uses frequency division multiplexing and time division multiplexing to improve the utilization rate of time-frequency resources, obtains the number of distributed subcarriers through an UL scheduling algorithm, calculates SINR, and obtains the number of retransmission times, the SCs index and the RUs according to the SINR.
NB-IoT resource allocation flow (see fig. 3), which contains the following elements:
1) the necessary inputs and outputs;
2) both signal-to-noise ratio and rate requirements are involved;
3) the problem of interference in uplink transmission of equipment is considered;
4) and finishing the optimized output of the resource allocation.
Further, the invention provides a resource scheduling algorithm based on throughput for improving the performance of network data transmission, which comprises the following concrete implementation steps:
1) starting from a first available Resource Unit (RU) of a first device;
2) the highest of the 4 RUCs is selected using the PDSD (Power Allocation between SCs of the same device) technique;
3) repeat for all devices 2);
4) selecting RU of the device with the highest rate, and considering ASC;
5) repeat 1) until all devices are scheduled to complete.
The invention has the beneficial effects that: the invention improves the transmission rate of the NB-IoT uplink and reduces the delay with lower complexity under the condition of not changing the transmission power.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
Drawings
For the purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made to the following detailed description taken in conjunction with the accompanying drawings in which:
fig. 1 is an overall framework diagram of the rate-delay based NB-IoT network resource scheduling method of the present invention;
FIG. 2 is a diagram of an NB-IoT resource allocation scheduling model;
fig. 3 is an NB-IoT resource allocation flow diagram.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention in a schematic way, and the features in the following embodiments and examples may be combined with each other without conflict.
Referring to fig. 1 to 3, fig. 1 is an overall framework diagram of a rate-delay based NB-IoT network resource scheduling method according to the present invention. The method can be applied to the deployment of terminal equipment with limited scale and can also be applied to the wireless network scene of the deployment of terminal equipment with large scale, the whole framework mainly comprises two parts, the former is composed of a scheduling level, an ASC, a PDSD and the like, and the method can be realized according to the information in the uplink of the actual network system. The implementation steps of the invention are divided into several parts:
in the first part, the adaptive power allocation is implemented by the following steps:
s1: assuming that N NB-IoT devices (denoted as d) are randomly distributed in a circular area (denoted as cell C), in cell C, each device d is tested according to the original RUC rate, and the best RUC device is selected;
s2: when the multiple transmission is performed, namely the TS of each device has a plurality of SCs, the maximum transmission power needs to be distributed among the SCs by applying the water-filling principle, so as to achieve the maximum throughput transmission;
s3: after selecting the best device in S1, the next idle device in the resource network continues to be selected, and S1 is repeated until all devices are distributed.
And in the second part, the specific implementation steps of distributing shape constraints are as follows:
s1: selecting unallocated space or SC in the resource grid at the transmission rate of the best device in the first portion;
and in the third part, the specific implementation steps of power control optimization are as follows:
s1: when there is an interfering device, allocating power to the interfering device by using MAPLEL (MLFP-based power allocation), and if in a specified number of link systems, knowing the channel gain of the interfering signal and the noise power of a receiver;
the fourth part specifically realizes the delay control optimization steps as follows:
s1: determining different sources and weights of the time delay, and ensuring that each device has only one RUC:
s2: if in an environment with a higher signal-to-noise ratio, the scheduling latency of a single device is divided by the total number of available RUs divided by the number of devices;
s3: the minimum one TS to the eighth TS are pure transmission time, and are distributed to specific RUCs, namely 8 SCs and a TS transmission time average value;
s4: calculating the SINR of each SC to determine the retransmission times which can reach 128 times to the maximum;
s5: the SC of the minimum signal-to-noise ratio triggers retransmission when it is below a threshold and the SC of the maximum SINR triggers retransmission when it is below a threshold, which is determined by the minimum SINR acceptable to the system.
And (3) verification experiment:
to further verify the resource allocation method based on the adaptive NB-IoT network of the present invention, the experiment simulates a dense NB-IoT network cell with interference. There are seven adjacent cells (C), each with three sectors with a radius of 250 meters, and the devices UE are evenly distributed in each cell, the detailed parameters are shown in table 1.
Table 1 detailed parameters of devices UE evenly distributed in each cell
The resource scheduling method of the invention comprises the following concrete implementation steps:
s1: establishing an overall optimization function:
s2: the impact of RU and power allocation on throughput was evaluated:
(1) comparing DAL (adaptive allocation) with RR (standard polling);
(2) compare DAL to adaptive RR (which can select the best RUC for the current device) and DAL + MAPEL, respectively;
(3) the effect of ASC was evaluated separately;
s3: the impact of PDSD on throughput and delay was evaluated:
(1) comparing the DAL with different types of PDSDs and with an adaptive RR at minimum SINR retransmission;
(2) at maximum SINR retransmission, DAL is compared to different types of PDSDs and adaptive RR.
S4: the impact of the scheduling process on throughput and delay is evaluated:
(1) using the PDSD to distribute power, recording power distribution and the maximum and minimum signal-to-noise ratio;
(2) selecting an optimal RUC, and recording different parts of each configuration;
(3) assigning the RU to the highest performance device, i.e., the rate in the DAL;
(4) the impact of the RUC on the distribution network was studied, taking into account the number of unallocated/unused RUs.
S5: according to the steps and the process, the resource scheduling method is evaluated through simulation comparison.
Finally, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. A method for rate-delay based NB-IoT network resource scheduling, the method comprising:
s1: constructing a rate optimization model, including power distribution optimization and uplink scheduling optimization; then, obtaining an optimized uplink power scheduling path by using the model;
s2: constructing a delay optimization model, and setting constraint conditions including scheduling waiting time, resource unit configuration RUC transmission time and retransmission time; then, the model is utilized to obtain the transmission power waiting time;
s3: and constructing a self-adaptive rate-delay selection mechanism, and calculating to obtain optimized throughput by combining the optimized uplink power scheduling path and the transmission power waiting time, namely realizing the maximization of the throughput in the resource allocation process.
2. The method for scheduling NB-IoT network resources based on rate-delay according to claim 1, wherein in step S1, constructing the rate optimization model specifically includes the following steps:
s11: establishing a rate optimization function:
and
wherein ,fRThe function of the rate is represented by,
representing the allocated rate component in device d,
which represents the transmit power of the device d,
representing the rate of device d at a time slot or subcarrier in cell C,
represents the minimum rate of device d in cell C; c represents the NB-IoT network cell index in C, T represents the index of the subframe T available to the device, and s represents the subcarrier index available to the device; c denotes NB-IoT network system, T denotes device usable subframe, Dc denotes device set in cell C, S usable subcarrier;
finding the optimal uplink power, wherein
The calculation formula of (2) is as follows:
wherein ,DaDenotes a device in cell a, j denotes an interfering device, a denotes a cell index belonging to C,
representing the channel gain between device d and the base station in cell c,
represents the transmission power of the interfering device j,
representing the channel gain between interfering device j and the base station in cell c,
representing the rate component, W, in the interfering device jnRepresenting the noise power;
s12: the constraint conditions are added as follows:
this formula represents: when non-overlapping devices are deployed in the same cell, the resource unit is ensured to be used by only one device, and no internal interference exists;
this equation represents: a power constraint, i.e. the total power of a device over time t does not exceed its total power in the uplink; wherein, WmaxRepresents the maximum power of the device in the uplink;
s13: resource unit constraints are added so that the optimizer selects at most one of the four RUCs:
wherein ,
indicating the number of subcarriers SC divided by the device,
representing the divided time slot TS; wherein SC and TS are continuous and uninterrupted; constraint c represents the SC given to device d from the frequency domain;
s14: introducing binary components
q ═ {1, 2, 3, 4} represents an index of the RUC, and
s15: each device has only one of the RUCs,
and
only two values are assumed at the slot or the SCs, and if the slot or the SC is not allocated to the equipment, the value is represented as 0 and is respectively recorded as
And
they represent the two aspects of multiple RUCs in the time domain and frequency domain, respectively;
allocate multiple to each TSNumber of SCs equal to
Indicates that TS in SC is equal to
S16: then the following equation is given for only one RUC per device:
3. the method for scheduling NB-IoT network resources based on rate-delay according to claim 2, wherein the delay optimization model constructed in step S2 is:
wherein ,fLRepresenting a delay function, e representing a constant close to 0; when in use
When the average molecular weight is not 0, the average molecular weight,
varies from 1 to 0 when { u, c, t } is arbitrary; when not equal to 0, each RUC has the same number of slaves with s and ∈1 to 0.
4. The method for scheduling NB-IoT network resources based on rate-delay according to claim 3, wherein in step S3, an adaptive rate-delay selection mechanism is constructed, that is, a multi-objective optimization problem is constructed, and the expression is:
wherein ,fRLDenotes the rate-delay optimization function, KR and KLTwo weights for rate and delay, respectively.
5. The method for scheduling NB-IoT network resources based on rate-delay as claimed in any of claims 1-4, wherein in the process of scheduling resources, the method first performs User Equipment (UE) prioritization: when the UE sends a lead code of the access channel identifier RA and the eNB detects the lead code sent by the UE, scheduling starts; at a certain moment, when a plurality of UE (user equipment) waiting for scheduling exist in a scheduling queue, the UE in the queue is reordered according to a priority algorithm, and the UE with high priority is selected to start to perform the next scheduling;
then, uplink (Up-Link, UL) resource allocation is carried out: and (3) using frequency division and time division multiplexing, obtaining the number of the distributed subcarriers through a UL scheduling algorithm, calculating SINR, and obtaining the retransmission times, the SCs index and the number of RUs according to the SINR.
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