CN114501478B - Rate-delay-based NB-IoT network resource scheduling method - 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 allocation optimization and uplink scheduling optimization; then, the optimized uplink power scheduling path is obtained 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, obtaining the transmission power waiting time by using the model; s3: and constructing an 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 under the condition of not changing the transmission power with lower complexity; 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 life of people, and social productivity is further improved due to the high efficiency of the electronic devices. In the face of hundreds of millions of electronic devices, how to effectively manage the devices, enhance the maintenance of the devices, reduce the cost, and the like has become a problem to be solved. With the increasing number of low-power-consumption internet of things equipment terminals, the conventional LTE communication cannot meet the rapidly expanding machine type communication requirement. NB-IoT is an emerging technology that is widely used worldwide, with a single sector having the performance advantages of supporting tens of thousands of connections, low power consumption, etc., effectively expanding the coverage area of the overall system and increasing the number of devices served by the system thousands of times. Although NB-IoT is designed to handle the challenges of larger number of device connections, existing NB-IoT resource scheduling algorithms also appear to be frustrating due to limited system resources, facing the need for massive machine-like communication traffic oversized connections and different QoS requirements in multiple traffic scenarios.
Since NB-IoT occupies only 180kHz bandwidth, the number of single base station devices can reach 20 tens of thousands, the 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 currently studying the resource allocation and scheduling problem of NB-IoT. Some of the existing methods do not develop optimization functions according to a given standard, while others do not specifically design scheduling policies for NB-IoT, such as when there are multiple RUCs (resource element configurations) in NB-IoT, the scheduling policies used are still specified by the 3GPP standard. In some documents, the impact of multi-device optimization and control plane optimization on resource scheduling is focused on, but the impact of throughput, latency, etc. on transmission power is ignored. Azari et al recognized that: the random access channel, the uplink shared channel, the downlink control channel, etc. should not be independently scheduled. Furthermore, to study the impact of scheduling on latency and battery life, they propose a traceable queuing model, but do not consider multitone allocation and throughput optimization. However, when studying the performance of RUCs under different traffic types, the relevant researchers use three scheduling strategies: and respectively designing corresponding scheduling strategies for each resource unit configuration according to an optimization target so as to measure the performance difference among all the resource unit configurations and select the optimal configuration.
The above-mentioned NB-IoT resource allocation study solves the problems in the respective scenarios, but with the continuous enrichment of NB-IoT application scenarios and the continuous increase of the number of access network devices, optimizing QoS requirements for different traffic scenarios has urgent practical significance. Therefore, there is a need to conduct intensive research on NB-IoT resource scheduling techniques, and design a reasonable and efficient resource scheduling algorithm to improve reliability of data transmission and network throughput.
Disclosure of Invention
Accordingly, the present invention is directed to a method for scheduling NB-IoT network resources based on rate-delay, which improves the data transmission rate, reduces the delay, and improves the network throughput based on the NB-IoT uplink characteristics, thereby optimizing the network performance.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a scheduling method of NB-IoT network resources based on rate-delay adopts a self-adaptive allocation scheduling mechanism aiming at different resource unit configurations in NB-IoT, and optimizes performance indexes such as delay, throughput, packet loss rate and the like by analyzing resource allocation among subcarriers of the same device and resource allocation among interfering devices; through researching the relation between throughput and time delay, an adaptive power distribution method is provided, and an optimization formula of NB-IoT throughput is extracted.
The method specifically comprises the following steps:
s1: constructing a rate optimization model, including power allocation optimization and uplink scheduling optimization; then, the optimized uplink power scheduling path is obtained 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, obtaining the transmission power waiting time by using the model;
s3: and constructing a self-adaptive rate-delay selection mechanism, and calculating by combining the optimized uplink power scheduling path and the transmission power waiting time to obtain the optimized throughput, namely, maximizing the throughput in the resource allocation process.
Further, in step S1, a rate optimization model is constructed, which specifically includes the following steps:
s11: establishing a rate optimization function:
and
wherein ,fR The function of the rate is represented as such,
representing the rate component allocated in device d, +.>
Representing the transmit power of device d +.>
Representing the rate of device d at a time slot or subcarrier in cell C,/for>
Representing the minimum rate of device d in cell C; c represents NB-IoT network cell index in C, T represents index of subframe T available to the device, s represents subcarrier index available to the device; c represents NB-IoT network system, T represents device available subframe, dc represents device set in cell C, S available subcarrier;
find the optimal uplink power, where
The calculation formula of (2) is as follows:
wherein ,Da Indicating the devices in cell a, j indicating the interfering devices, a indicating the cell index belonging to C,
indicating the channel gain between device d and the base station in cell c, < >>
Representing the transmission power of interfering device j +.>
Indicating the channel gain between interfering device j and base station in cell c, +.>
Representing the rate component, W, in the interfering device j n Representing noise power;
s12: the addition constraint conditions are 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 the device in time t does not exceed its total power in the uplink; wherein W is max Representing the maximum power of the device in the uplink;
s13: resource unit constraints are added such that the optimizer selects at most one of the four RUCs:
③
wherein ,
representing the number of SC (subcarriers) allocated to the device, < > for>
Representing the number of TSs divided; wherein SC and TS are continuous and uninterrupted; constraint (3) represents SC given to device d from the frequency domain;
s14: introducing binary components
Index representing RUC, and +.>
S15: there is only one RUC per device,
and />
It is assumed that there are only two values in slots or SCs, which are denoted 0 if no slots or SCs are allocated to the device, denoted +.>
and />
They represent two aspects of the RUCs in the time and frequency domains, respectively;
the number of SCs allocated to each TS is equal to
Indicating that TS in SC is equal to
S16: then, according to the equation that there is only one RUC column per device:
steps S14-S16 describe constraints on 4 RUCs, step S14 ensuring
With only a single value, step S16 ensures that the SC and TS numbers of each device are equal to the set number of RUCs.
Further, in step S2, the delay optimization model is constructed as follows:
wherein ,fL Representing a delay function, e represents a constant close to 0; when (when)
When it is not 0, the +.A.in this function is taken into consideration by the different shapes of RUCs>
All of { u, c, t } being any value, vary from 1 to 0; when not equal to 0, each RUC ranges from 1 to 0 in the same number s and ε.
Further, 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 ,fRL Representing a rate-delay optimization function, K R and KL The two weights of rate and delay are respectively, and if the rate and delay are equally important, both values are 1.
Further, in order to reasonably allocate the NB-IoT resources, the present invention proposes an adaptive power allocation method, which is mainly used in the 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) prioritization is performed: scheduling starts when the UE transmits a preamble of RA (access channel identification) and the eNB detects the preamble transmitted by the UE; at a certain moment, when a plurality of UE waiting for scheduling exist in a scheduling queue, the UE in the queue reorders according to a priority algorithm, and the UE with high priority is selected to start scheduling of the next step;
uplink (UL) resource allocation is then performed: the method mainly uses frequency division and time division multiplexing to improve the utilization rate of time-frequency resources, calculates SINR by obtaining the number of allocated subcarriers through an UL scheduling algorithm, and obtains the retransmission times, SCs indexes and the number of RUs according to the SINR.
NB-IoT resource allocation procedure (see fig. 3), which contains the following elements:
1) Necessary inputs and outputs;
2) Both signal to noise ratio and rate requirements are included;
3) Consider the interference problem in the uplink transmission of the device;
4) And (5) completing resource allocation optimization output.
Furthermore, in order to improve the performance of network data transmission, the invention provides a resource scheduling algorithm based on throughput, which comprises the following specific implementation steps:
1) Starting from a first available Resource Unit (RU) of a first device;
2) Selecting a highest one of the 4 RUCs using a PDSD (power allocation among SCs of the same device) technique;
3) Repeating 2) for all devices;
4) Selecting RU of the device with highest rate, considering ASC;
5) Repeating 1) until all devices are scheduled to completion.
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 without 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 objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is an overall framework diagram of a rate-delay based NB-IoT network resource scheduling method in accordance with the present invention;
FIG. 2 is a diagram of an NB-IoT resource allocation scheduling model;
fig. 3 is a NB-IoT resource allocation flow diagram.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Referring to fig. 1 to 3, fig. 1 is an overall frame diagram of an NB-IoT network resource scheduling method based on rate-delay according to the present invention. The method can be applied to the deployment of limited-scale terminal equipment and the deployment of large-scale terminal equipment, and the whole framework mainly consists of two parts, namely a scheduling level, an ASC (integrated circuit), a PDSD (packet data storage device) and the like, and can be realized in a mode according to the information in the uplink of an actual network system. The implementation steps of the invention are divided into several parts:
the first part, the specific implementation steps of the self-adaptive power distribution are as follows:
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, selecting the best RUC device;
s2: when multiple transmission is performed, that is, each device has a plurality of SCs in the TS, the maximum transmission power needs to be allocated between the SCs by using the water injection principle, so that the maximum throughput transmission is achieved;
s3: and after the best equipment is selected in the step S1, continuing to select the next idle equipment in the resource network, and repeating the step S1 until all the equipment is separated.
The second part, the specific implementation steps of the distribution shape constraint are as follows:
s1: selecting unallocated spaces or SCs in the resource grid at a transmission rate of the best device in the first portion;
the third part, the power control optimization concretely comprises the following steps:
s1: when interference equipment exists, MAPEL (MLFP-based power allocation) is utilized to allocate power for the interference equipment, and if the interference signal channel gain and the noise power of a receiver are also needed to be known in a formulated number of link systems;
the fourth part, delay control optimization concretely comprises the following steps:
s1: determining different sources and weights of the delay, the constraint ensures that there is only one RUC per device:
s2: if the scheduling waiting time of the single equipment is in the environment with higher signal-to-noise ratio, dividing the total number of available RUs by the number of equipment;
s3: the minimum 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 SINR of each SC to determine retransmission times, up to 128 times;
s5: the minimum signal-to-noise ratio SC triggers retransmission when it is below a threshold and the maximum SINR SC triggers retransmission when it is below a threshold, the threshold being determined by the minimum SINR acceptable to the system.
Verification experiment:
to further verify the adaptive NB-IoT network-based resource allocation method of the present invention, the present experiment simulates a dense NB-IoT network cell with interference. Seven adjacent cells (C) are provided, each cell has three sectors with a radius of 250 meters, the equipment UE is uniformly distributed in each cell, and the detailed parameters are shown in table 1.
Table 1 detailed parameters for the devices UE to be evenly distributed in each cell
The resource scheduling method comprises the following specific implementation steps:
s1: establishing an overall optimization function:
s2: the impact of RU and power allocation on throughput is evaluated:
(1) Compare DAL (adaptive allocation) to RR (standard poll);
(2) Comparing the DAL with adaptive RR (the best RUC to select for the current device) and dal+mapel, respectively;
(3) Separately evaluating the effect of ASC;
s3: the effect of PDSD on throughput and delay was evaluated:
(1) At minimum SINR retransmission, the DAL is compared with different types of PDSDs and adaptive RRs;
(2) At maximum SINR retransmission, the DAL is compared to different types of PDSDs and adaptive RRs.
S4: the impact of the scheduling procedure on throughput and delay is evaluated:
(1) Using the PDSD to allocate power, recording power allocation and maximum and minimum signal to noise ratio;
(2) Selecting an optimal RUC, and recording different parts of each configuration;
(3) Assigning RU to the highest performance device, i.e., the rate in DAL;
(4) The effect of RUCs on the allocated network is studied, taking into account the number of unallocated/unused RUs.
S5: according to the steps and the processes, the resource scheduling method of the invention is evaluated by comparing through simulation.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and 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 modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (2)
1. A method for scheduling NB-IoT network resources based on rate-delay, the method comprising the steps of:
s1: constructing a rate optimization model, including power allocation optimization and uplink scheduling optimization; then, the optimized uplink power scheduling path is obtained by using the model;
the rate optimization model is constructed, and the method specifically comprises the following steps:
s11: establishing a rate optimization function:
and
wherein ,fR The function of the rate is represented as such,
representing the rate component allocated in device d, +.>
Representing the transmit power of device d +.>
Representing the rate of device d at a time slot or subcarrier in cell C,/for>
Representing the minimum speed of device d in cell CA rate; c represents NB-IoT network cell index in C, T represents index of subframe T available to the device, s represents subcarrier index available to the device; c represents NB-IoT network system, T represents device available subframe, dc represents device set in cell C, S available subcarrier;
find the optimal uplink power, where
The calculation formula of (2) is as follows:
wherein ,Da Indicating the devices in cell a, j indicating the interfering devices, a indicating the cell index belonging to C,
indicating the channel gain between device d and the base station in cell c, < >>
Representing the transmission power of interfering device j +.>
Indicating the channel gain between interfering device j and base station in cell c, +.>
Representing the rate component, W, in the interfering device j n Representing noise power;
s12: the addition constraint conditions are 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 the device in time t does not exceed its total power in the uplink; wherein W is max Representing the maximum power of the device in the uplink;
s13: resource unit constraints are added such that the optimizer selects at most one of the four RUCs:
③
wherein ,
representing the number of sub-carriers SC allocated to the device, < >>
Representing the divided time slots TS; wherein SC and TS are continuous and uninterrupted; constraint (3) represents SC given to device d from the frequency domain;
s14: introducing binary components
Index representing RUC, and +.>
S15: there is only one RUC per device,
and />
It is assumed that there are only two values in slot or SCs, which are denoted 0 if no slot or SC is allocated to the device, denoted +.>
and />
Which represent two aspects of the plurality of RUCs in the time and frequency domains, respectively;
the number of SCs allocated to each TS is equal to
Indicating that TS in SC is equal to
S16: then, according to the equation that there is only one RUC column per device:
s2: constructing a delay optimization model, and setting constraint conditions including scheduling waiting time, resource unit configuration RUC transmission time and retransmission time; then, obtaining the transmission power waiting time by using the model;
the delay optimization model is constructed as follows:
wherein ,fL Representing a delay function, e represents a constant close to 0; when (when)
If the value is not 0, the patient is added with->
All of { u, c, t } being any value, vary from 1 to 0; when not equal to 0, each RUC is from 1 to 0 in the same number of s and ε;
s3: 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, maximizing the throughput in the resource allocation process;
constructing an adaptive rate-delay selection mechanism, namely constructing a multi-objective optimization problem, wherein the expression is as follows:
wherein ,fRL Representing a rate-delay optimization function, K R and KL Two weights of rate and delay, respectively.
2. The NB-IoT network resource scheduling method based on rate-delay according to claim 1, wherein in the resource scheduling process, the method first performs User Equipment (UE) prioritization: when the UE transmits a preamble of an access channel identifier (RA) and the eNB detects the preamble transmitted by the UE, scheduling starts; at a certain moment, when a plurality of UE waiting for scheduling exist in a scheduling queue, the UE in the queue reorders according to a priority algorithm, and the UE with high priority is selected to start scheduling of the next step;
uplink (UL) resource allocation is then performed: and calculating SINR (signal to interference plus noise ratio) by using frequency division and time division multiplexing and obtaining the number of allocated subcarriers through an UL scheduling algorithm, and obtaining the retransmission times, the SCs index and the number of RUs according to the SINR.
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