Erlang Network
Popular repositories
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dumb_v_smart
dumb_v_smart PublicCan Dumb Beat Smart? Can the best and smartest multiuser channel access and Collision-avoidance algorithms beat the dumbest multiuser channel access scheme?
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5G-air-simulator
5G-air-simulator PublicForked from telematics-lab/5G-air-simulator
An open-source system-level simulator modeling the 5G air interface
C++ 1
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cloud
cloud PublicForked from tensorflow/cloud
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
Python
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plasma-pstate
plasma-pstate PublicForked from jsalatas/plasma-pstate
Intel P-state and CPUFreq Manager Widget
QML 1
Repositories
- NYUSIM_in_ns3 Public Forked from hiteshPoddar/NYUSIM_in_ns3
ns-3 files for NYUSIM in ns-3. See https://arxiv.org/pdf/2305.01828.pdf for reference.
- SUPL-3GPP-LPP-client Public Forked from Ericsson/SUPL-3GPP-LPP-client
Example SUPL 3GPP LPP client for connecting and requesting assistance information. Including support for converting 3GPP LPP assistance data to RTCM.
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- sionna Public Forked from NVlabs/sionna
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
- 6G-Edge-Computing-Simulation-Deployment Public Forked from mobinets/6G-Edge-Computing-Simulation-Deployment
Simulation code for EdgeGO -- A resource sharing framework for 6G edge computing in massive IoT systems, https://ieeexplore.ieee.org/document/9375469/
- 6g_security Public Forked from ocatak/6g_security
6G and Security repository for telecommunications and AI research. We will share our implementations and publications in 5G and beyond technology, 6G, Security, Machine learning on 6G, Massive MIMO, THz communication and communication networks.
- BAC-COM-for-6G-umMTC Public Forked from zhiguo-ding/BAC-COM-for-6G-umMTC
On the Application of BAC-NOMA to 6G umMTC
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- cloud Public Forked from tensorflow/cloud
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
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