The organizer - Guangdong OPPO Mobile Communications Corp., Ltd.

◼ Competition Background

The deep integration of wireless communication and artificial intelligence (AI) has become an

important direction for the construction of future wireless communication systems. At present,

many researches with good results on AI solutions for specific modularization problems of 5G

wireless communication systems have been carried out in academia and industry. At the same

time, with the evolution from 5G to 6G, researchers have once again obtained the opportunity

to ponder, define and build a new generation of wireless communication systems. In this

process, many constraints in current system can be relaxed, and the direction and depth of the

integration for 6G and AI can further be expanded.

Based on the above background, we launched the "6G AI Competition", which aims to combine

the strengths of all parties and the promotion of the competition to systematically and

comprehensively study the impact of AI on the future wireless communication system and the

solutions for key issues. In the first stage of the competition design, from the perspective of

methodological innovation, we introduce some common problems that AI-based solutions need

to face, and will comprehensively promote the technological breakthrough and industrial

landing of smart 6G.

◼ Competition Schedule

The competition will be held online, and technology sharing and awarding will be carried out

offline. Contestants should register, team up, and submit the model for evaluation on the

official platform DataFountain. After the online competition, the top ten teams or individuals

whose submitted models have been reviewed need to participate in the seminar and attend the

6G AI Competition

award ceremony.

The schedule is as follows:

- December 24, 2021：The competition tasks are released, contestants can log in to

the official website for registering：

https://www.datafountain.cn/competitions/557?lang=en-US

- January 4, 2022 12:00 (Beijing time)：The dataset is released and the registration

on the official website is open. Contestants registered can log in to the official website

to download the dataset. At the same time, the competition officially enters the

evaluation stage. Contestants can submit the required files online to the competition

platform. Each team can submit up to 3 times a day. The evaluation system will

automatically evaluate the score and update it to the leaderboard. The highest scores

of each contestant will be recorded on the leaderboard, and the relevant teams must

save the source code of the highest score for review.

- March 8, 2022 12:00 (Beijing time)：Deadline for registration and team formation.

- March 11, 2022 24:00 (Beijing time)：The evaluation platform is closed, and the

leaderboard is locked.

- March 11 - 31, 2022：After reviewing the submission of the top ten teams, the teams

will be awarded the Golden, Silver, Bronze and the Winning prize in descending order

of the evaluation results. The winning teams must participate in the seminar and the

award ceremony. Teams that do not participate will abandon the competition by

default. Note: After receiving the notification from the organizing committee, if the

top ten teams fail to submit their materials or abandon the competition, the organizing

committee will notify other teams to submit review materials based on the ranking.

- April 10, 2022：Seminar and award ceremony. Note: if the time is changed due to

force majeure or other factors, the organizing committee will notify the winning

teams as soon as possible. If the winning team is from outside of China, online access

is recommended for participating in the seminar and the award ceremony.

◼ Irregularities

If the participating team has the following or other major irregularities, the qualifications and

results of the competition can be cancelled after the discussion of competition organizing

committee, and the list of winning teams will be postponed sequentially.

a. Serious violation of competition rules,

b. Cheating by using multiple accounts, colluding, plagiarizing others’ codes, etc.,

c. Use of external data without permission, (Including but not limited to using external data

directly or indirectly without permission)

d. Other major violations.

◼ Bonus

Golden Prize: 300,000 RMB for 1 team

Silver Prize: 50,000 RMB (per team) for 2 teams

Bronze Prize: 20,000 RMB (per team) for 3 teams

Winning Prize: 10,000 RMB (per team) for 4 teams

Note 1– the award can be settled in US dollars according to the exchange rate on the settlement

date

Note 2– the individual income tax or other forms of tax on the bonus will be borne by the

winners, and will be withheld and paid by the organizer of the competition. The participating

teams shall be responsible for the distribution and distribution of the bonus among their

members, and the organizer will not be held responsible for this.

◼ Competition Rules

• Participants: The competition is open to all the people around the world, regardless of age

or nationality. All colleges and universities, scientific research institutions, enterprises,

maker teams, individuals, etc. can log on to the official website to register for the

competition. Guangdong OPPO Mobile Telecommunications Corp., Ltd and affiliated units

of which can participate the competition but cannot win prizes, and will not occupy the

prize quota (i.e. if the team is in the top 10 of the rank after the rank is locked, the team will

not be awarded, nor will it occupy the award quota. The team can participate in sharing

activities. The winning team will be ranked in sequence except for this team).

• Registration requirements: Each person can only participate in one team (1-5 team

member per team(s)) for each track. All team members must provide basic personal

information and pass the real-name certification when registering the competition. The

team formation must be completed before the deadline. Once the formation of the team is

completed, team members cannot quit from the team.

• Team up conditions: In order to ensure that each team has a relatively equal opportunity

for submission, the total number of submissions of all members in a team must be no larger

than 3 times of the number of days open for evaluation.

• Submission of works: Contestants can submit up to 3 works per day on the competition

platform, and the evaluation system will automatically evaluate the score. Entries must

guarantee originality, do not violate any relevant laws of the People’s Republic of China,

and do not infringe any third-party intellectual property rights or other rights. Once

discovered or submitted and verified by the right holder (within 1 month after the

publishing of final winner list of the competition), the committee will cancel its competition

results and deal with it seriously.

• Winning conditions: The top 10 teams on the list at the end of the online evaluation will

be the winning teams. If any team quits the competition (the committee failed to contact

any member of the team for three consecutive days according to the contact information

provided by the contestants, or the team took the initiative to quit the competition), the list

of winners will be filled with following teams by sequence. Contestants need to cooperate

with the committee to verify the validity and authenticity of the submitted competition

works, and at the same time check the correctness of the works by themselves, and submit

them after confirming that they are correct. The committee is not responsible for making

changes and adjustments to the submitted competition works.

• Fair competition: Participants are not allowed to use rule loopholes or technical loopholes

to improve their rankings outside the scope of the designated assessment technical ability,

and it is forbidden to copy other people’s works, exchange answers, and use multiple IDs

in the competition. It is forbidden for different contestants to submit similar works

maliciously. The committee will cancel the unfair competition results and deal with it

seriously.

• Organization statement: The committee reserves the right to adjust and modify the rules

of the competition, the right to determine and dispose of cheating in the competition, and

the right to withdraw or refuse the award of the participating team that affects the

organization and fairness.

• Competition data: The committee authorizes participants to use the provided data to

conduct model training for the designated contest. Participants are not allowed to use the

data for any commercial purposes. If it is used for scientific research, please indicate the

relevant data provider.

• Intellectual property rights of works: The intellectual property rights of the works

(including but not limited to algorithms, models, etc.) belong to the contestants. The

committee can use the works, works-related materials, and participating team information

for promotional materials and related publications, e.g. designated and authorized media

releases, official website browsing and downloads, exhibitions (including touring

exhibitions) and other activities, under the consent of the contestants. The organizers of the

competition have the priority of cooperation.

• Special avoidance: Personnel involved in track design and data provision in Guangdong

OPPO Mobile Telecommunications Corp., Ltd,is prohibited from participating, or

entrusting others to participate or guiding the participating team.

• Notification and communication: The committee will invite teams to participate in

sharing seminar, awards ceremony and other activities through the contact information

reserved by the participating teams. If the participating team does not reply within 3 days

after the above-mentioned related notice is issued, it will be deemed to have automatically

given up the corresponding opportunity, and the organizer has the right to replace other

participating teams in order.

◼ Rights and Responsibilities

• The committee has the right to judge and dispose of cheating in the competition.

• The organizing committee reserves the right to modify the submission deadline, defense

date and awards date of the competition works. The organizing committee reserves the right

to suspend or terminate the competition under special conditions.

• The organizing committee reserves the right to withdraw or refuse awards to participating

teams that affect the organization and fairness of the competition.

• In case of data update, review code update, cheating check and other reasons, the committee

has the right to re-evaluate the results of the competition and update the rankings.

• The committee reserves the right to adjust and modify the rules of the competition. The

organizers of the competition have the final right to interpret the competition.

◼ Organization

Host - Guangdong OPPO Mobile Telecommunications Corp., Ltd

Platform - DataFountain

◼ Committee

Chairman：

Ning Yang Head of the OPPO Standard and Research Department

Professorate Senior Engineer, OPPO Research Institute

Shi Jin Vice President of Southeast University

Professor, Southeast University

Chairman of Technical Committee:

Zhaoyang Zhang Leader of the IMT-2030 Wireless AI Work Group

Professor, Zhejiang University

Xiaofeng Liu Leader of the IMT-2020(5G) Promotion Group 5G+AI Work Group,

Professorate Senior Engineer, China Academy of Information and

Communications Technology,

Feifei Gao Associate Professor, Tsinghua University

Jia Shen Vice-Leader of the IMT-2020(5G) Promotion Group 5G+AI Work

Group

Professorate Senior Engineer, OPPO Research Institute

Zheng Qin Director of Industry University Research Affairs Department, OPPO

Technology strategy and planning center

Technical Committee：

Caijun Zhong Professor, Zhejiang University

Jianhua Zhang Professor, Beijing University of Posts and Telecommunications

Lingyang Song Professor, Peking University

Wei Chen Professor, Beijing Jiaotong University

Wenchi Cheng Professor, Xidian University

Zhaocheng Wang Professor, Tsinghua University

Xiang Zhang Professorate Senior Engineer, China Academy of Information and

Communications Technology,

Zhi Zhang Communication Standards Expert, OPPO Research Institute

Technical Working Group：

Wenqiang Tian, Han Xiao, Wendong Liu, Dexin Li

◼ Contact

Tel: 010-62381637

Email: liujia@datafountain.cn

Community:

Official WeChat Communication Group:

Official WeChat Group: OPPO 6G AI Competition Communication Group

Official WeChat Account: (Continue to release contest-related information)

Competition Topic: AI-based Channel Modeling and Generating

Background

As the basis of wireless communication system design and performance evaluation, channel

modeling has attracted lots of attentions in the 6th generation (6G) pre-research. There are various

channel modeling approaches that have been proposed. However, considering the increasing

complexity of wireless environments, the extension of frequency band and the introduction of large-

scale multiple-input multiple-output (MIMO) systems, current channel modeling schemes are

difficult extracting the complicated wireless characteristics effectively. Recently, deep learning (DL)

based wireless communication has been regarded as a potential technology in the 6G. In addition to

accurate channel modeling, DL-based wireless communication approaches also require amounts of

high-quality wireless channel dataset to support the training of neural network (NN). However, the

collection of large wireless channel data is quite costly and time-consuming, which motivates novel

channel data generating solutions to support the training of NN. Therefore, to solve these problems,

the first 6G AI competition will take ‘AI based Channel Modeling and Generating‘ as the topic to

explore possible solutions.

Task

As shown in Fig. 1. The task considers utilize AI based method to realize the big set of wireless

channel data generation which is seeded from a small set of real channel data. The similarity and

diversity of the generated data are jointly used to perform the evaluation, in more detail:

a. Given a small set of real channel data, contestants design the AI based method to realize the

big set of wireless channel data generation which is seeded from the small real channel set.

b. The similarity between the distributions of the generated dataset and the real dataset is

evaluated.

c. Diversity of the generated dataset is evaluated.

d. The design and evaluation are performed on two types of real channel datasets, where the

complexity of the second type of channel is higher than that of the first type of channel.

Fig. 1 Illustration of competition task

Dataset

The competition provides two types of real datasets, i.e., H1_32T4R.mat with 500 samples and

H2_32T4R.mat with 4000 samples, in which the samples are full MIMO channel tensors with the

form of complex numbers and the shape of Nreal （number of samples）× 4 (receiving antennas) ×

32 (transmitting antennas) × 32 (delay paths).

Direct or indirect use of external datasets or pre-trained models are not allowed. After

the online evaluation phase, it is necessary for the winning teams to illustrate the training

process during the reviewing phase. The reproduce of training process will be conducted if

necessary. In the event of non-reproducible performance, illegal use of external data, etc., the

results will be cancelled.

Result Submission

Contestants should design the model according to the following rules, and upload the zip

package of the model to the scoring system of the competition platform.

Recommended programming language version: Python 3.7，

Recommended package version: tensorflow 2.4.2(2.1.0+), pytorch>1.7.0, Numpy 1.18.1, h5py

2.10.0,

Maximum upload file size: 400MB,

Maximum data generation time: 400s.

The scoring system supports the submission of model using TensorFlow or Pytorch. We

provide the reference code generatorFun.py and evaluation.py for both versions, where

1. generatorFun.py: Contains the functions of generator_1 and generator_2 for the two types

of channels, respectively, which are evaluated on the platform. Specifically, the inputs of the

function include the number of generated data, the generator model file and the real channel

dataset file. The output is the generated channel set with corresponding number samples.

2. evaluation.py: For evaluation offline. The code calls the functions generator_1 and

generator_2 defined in generatorFun.py and generate channel data fake_1 and fake_2

respectively, which are used to compare with real data and evaluate the performance and

score of the generated data (online evaluation will use independent real datasets) )

Files need to be submitted:

1.generatorFun.py (for TensorFlow) or generatorFun.py（for Pytorch）

2.generator_1.h5 (for TensorFlow) or generator_1.pth.tar（for Pytorch）

3.generator_2.h5 (for TensorFlow) or generator_2.pth.tar（for Pytorch）

Submission Example

Zip the files with the following structure, name the zip package with the ID of the team and

upload it, i.e.,

123456.zip

┣━ generatorFun.py (for TensorFlow) or generatorFun.py（for Pytorch）

┣━ generator_1.h5 (for TensorFlow) or generator_1.pth.tar (for Pytorch)

┗━ generator_2.h5 (for TensorFlow) or generator_2.pth.tar (for Pytorch)

Score

1. Contestants need to train the models on two types of real datasets respectively and submit

to the platform. Different schemes can be designed for different real datasets. There are no

restrictions on the scheme design for the first type of channel, while the scheme design for the

second type of channel is limited to the deep learning based generating model, e.g., generative

adversarial network, variational autoencoder, etc.

2. For each type of channel, the similarity between the distribution of the generated data set

and the total real data set is evaluated by

𝑠𝑖𝑚 = 1

𝑁𝑓𝑎𝑘𝑒∑ max

1≤𝑖≤𝑵𝑟𝑒𝑎𝑙

‖𝒉𝑗H𝒉′𝑖‖

2

‖𝒉𝑗‖2

‖𝒉′𝑖‖2

𝑁𝑓𝑎𝑘𝑒

𝑗=1

where Nfake denotes the number of generated channel samples, Nreal denotes the number of real

channel samples, 𝒉𝑗 and 𝒉′𝑖 denote the vectorized j th generated channel sample and i th real

channel, respectively. For the first type of channel, Nfake =10000 and Nreal=10000. For the second

type of channel, Nfake =40000 and Nreal=40000.

3. For each type of channel, the diversity of the generated channel is evaluated by

𝑚𝑢𝑙𝑡𝑖 = √Var(𝒍)

where Var(·) calculates the variance of the input vector. The element 𝑙𝑖0 of 𝒍 = [𝑙1, 𝑙2, ⋯ , 𝑙𝑁𝑟𝑒𝑎𝑙

]

is defined as

𝑙𝑖0= 𝑁 (argmax

1≤𝑖≤𝑵𝑟𝑒𝑎𝑙

‖𝒉𝑗H𝒉′𝑖‖

2

‖𝒉𝑗‖2

‖𝒉′𝑖‖2= 𝑖0)

where N(·) denotes the total number of fake samples whose most similar real sample is the given

i_0 the real sample

For the first type of channel, Nfake =10000 and Nreal=10000. For the second type of channel, Nfake

=40000 and Nreal=40000.

4. Scoring

The first dataset The second dataset

Valid Score sim1>0.2 and multi1/sim1<20 sim2>0.1and multi2/sim2<40

Score score1=(20-multi1/sim1)/ 20 score2=(40-multi2/sim2)/40

Final Score score_final=(score1+score2)/2

Note1: sim1, multi1, sim2, multi2 and score_final are displayed on the scoring platform and ranking

is according to score_final.

Note2: score1=0 if score1 is invalid, score2=0 if score2 is invalid.