This change removes the cudaDevAttrIntegrated check and only requires
pageable memory access. This change allows to run GPU accelerated
channel convolution on GH machines.
Added two versions of channel convolution and noise generation:
- accelerated via threadpool
- accelerated using CUDA
The main difference between this and previous versions of channel
convolution implementations is that these functions take a real-world
approach to input/output where both could be split unevenly over a set of
buffers, e.g. ring buffers used in vrtsim.
The CUDA-accelerated version only works on systems with unified memory, e.g. NVidia
DGX Spark or GH
- all RAN code, CI code, configuration files, dockerfiles, in CSSL v1.0
- all deployment code (openshift, charts, ancillary files like shell
scripts), in MIT
- documentation in CC-BY-4.0
- exceptions might apply and are listed in NOTICE
- there is a new LICENSES folder with all licenses
- CONTRIBUTIONS.md has been updated accordingly
For automated changes based on OAI PL v1.1:
perl -i~ -0pe 's/\/\*.*Licensed to the OpenAirInterface.*openairinterface.org\n#?/\/*\n * SPDX-License-Identifier: LicenseRef-CSSL-1.0\n/s' **/*.{c,h,cpp}
perl -i~ -0pe 's/\/\*.*Licensed to the OpenAirInterface.*openairinterface.org\n#?/\/*\n * SPDX-License-Identifier: LicenseRef-CSSL-1.0\n/s' **/*.ts
perl -i~ -0pe 's/<!--.*Licensed to the OpenAirInterface.*openairinterface.org\n.*-->/<!-- SPDX-License-Identifier: LicenseRef-CSSL-1.0 -->/s' **/*.xml
The rest (cmake, files with missing license, cmake) manually.
GPU Channel Simulation: nr_dlsim/nr_ulsim Integration + CI Test
This MR is a follow-up to !3886 (merged) and extends CUDA-based channel
simulation support to nr_dlsim and nr_ulsim, together with the
corresponding CI tests.
The MR incorporates:
- Cherry-picked commits e0c204f7 and 5f344876 from !3588
- Integration of new CI physim tests using GPU-accelerated channel
simulation in nr_dlsim and nr_ulsim tests, see commit c727b3bb
New CI job: RAN-Channel-Simulation
https://jenkins-oai.eurecom.fr/job/RAN-Channel-Simulation/
Prior to this commit, constants NB_ANTENNAS_RX/TX are provided on the
command line to each compiler invocation. This has the drawback (1) that
also files that don't need that get the constants, and (2) it is not
easy to find them using ctags or similar, as the only definition is in
CMakeLists.txt (where it is not found).
In this commit, use cmake configure_file() to write a header file with
these constants. The file will be generated during cmake invocation, and
written to <build-dir>/common/cmake_defs.h. The relevant files that
need this definition will pick it from the header.
This has been used previously also in a commit to write git information.
See-also: 8bffd1666d ("Avoid complete rebuild on cmake run with git info change")
This commit integrates the CUDA-based channel simulation pipeline into
the nr_dlsim.
A new `--cuda` command-line flag is added to enable the GPU path at
runtime. When activated, the simulator will:
- Allocate all necessary GPU and pinned host memory via the new
`init_cuda_chsim_buffers` helper function.
- In the main simulation loop, call the `run_channel_pipeline_cuda`
function to perform the channel simulation on the GPU, bypassing the
CPU-based functions.
- Clean up all CUDA resources on exit using the
`free_cuda_chsim_buffers` helper.
Additionally, dlsim is now using the float version of channel_multipath and add_noise functions.
Also, The input data is formatted as interleaved IQ, with separate antennas to ensure a fair comparison with the GPU operation.
This commit extends the CUDA API with new functions designed for
high-throughput scalability testing and advanced concurrency.
Key additions include:
- Batched versions of the kernels (`..._batched`) that use the
`blockIdx.z` grid dimension to process many independent channel
simulations in parallel.
- A C-callable wrapper, `run_channel_pipeline_cuda_batched`, to
orchestrate the execution of these new kernels.
- A "streamed" version of the pipeline,
`run_channel_pipeline_cuda_streamed`, which accepts a
`cudaStream_t` as an argument. This allows the calling
application to manage the execution stream, enabling overlap
with other GPU or CPU tasks.
This commit introduces the main C-callable pipeline function,
`run_channel_pipeline_cuda`, located in a new `channel_pipeline.cu`
file.
This function serves as the primary entry point for the GPU channel
simulation. It orchestrates the entire sequence of operations:
- Manages Host-to-Device data transfers for the input signal and
channel coefficients.
- Launches the `multipath_channel_kernel` and the
`add_noise_and_phase_noise_kernel` in the correct order.
- Manages the Device-to-Host data transfer for the final output signal.
- Synchronizes to ensure completion before returning.
This commit adds the CUDA implementation for adding Additive White
Gaussian Noise (AWGN) and phase noise to the signal. The code is
located in phase_noise.cu.
- The `add_noise_and_phase_noise_kernel` uses the NVIDIA cuRAND
library for efficient parallel random number generation.
- Helper functions are included to create, initialize, and destroy
the cuRAND states required by the kernel.
- Placeholder for a C-callable wrapper, `add_noise_cuda`, is also
provided.
This commit introduces the CUDA implementation of the multipath channel
model in `multipath_channel.cu`.
- Implements `multipath_channel_kernel` using shared memory for
efficient, high-performance convolution.
- Provides a C-callable wrapper, `multipath_channel_cuda`, to
orchestrate the full pipeline of data transfers and kernel
launches.
- The wrapper includes support for multiple memory models (Explicit
Copy, Unified Memory, ATS) via preprocessor directives to adapt to
different build configurations.
- Adds a `interleave_channel_output_cuda` utility to convert signal
data from the CPU's planar format to the GPU's interleaved format.
This commit refactors the CPU-based channel model for improved reusability and extends it with single-precision floating-point support.
This serves as a performance and correctness baseline for the new CUDA implementation.
Key changes include:
- The original double-based multipath_channel function is refactored to remove hardcoded antenna dimensions from its signature. It now accepts dynamically sized arrays, making it more flexible for use in simulators like dlsim and ulsim.
- A new multipath_channel_float function is introduced to operate on float data types, matching the GPU's native format.
- A corresponding add_noise_float function is also added to complete the floating-point CPU pipeline.
- The new float-based functions are designed to work with an interleaved IQ sample format ([I, Q, I, Q]), which is more suitable for vectorized (SSE) and GPU processing.
This commit adds the initial infrastructure for building accelerated simulation components.
- Adds the CUDA_ENABLE option and logic to find the CUDA toolkit.
- Adds the CHANNEL_SSE option to enable SSE-specific code paths.
- Sets required properties on the SIMU target to allow linking with CUDA-compiled objects.
- Creates the initial oai_cuda.h header for the public API.
NR UE: add support for multiple RF frontends
This MR adds basic support for multiple RF-frontends at the UE.
There are multiple reasons why we might want this:
1. There might be different antennas needed for different bands (e.g. NTN or
TN antennas). These antennas might be connected to different RF-frontends.
In case of Handover, the UE needs to dynamically switch between these
RF-frontends.
2. Each rf-simulator connection carries baseband I/Q samples. To be able to
perform a handover between two cells at different frequencies, there must
be two rf-simulator connections, as the baseband channels should not
interfere and thus cannot simply be added.
3. When we want to support multiple UE simulation within one instance of
nr-uesoftmodem, and allow multiple cells and probably even handover between
these cells, we need either:
1. dedicated RF-frontends for each simulated UE, or
2. dedicated RF-frontends for each connected cell and dynamically assign
simulated UEs accordingly.
This MR implements what is needed for 1., 2. and 3.1.
Introduce SRS physical simulator and improvements
This MR consists of two parts:
- Introduces SRS physical simulator to test different configurations of
SRS
- Improvements in the SRS channel estimation (Addressing the comments
from old, unfinished MR !2875)
- rewrite nr_srs_channel_estimation() to loop over rx antennas and
antenna ports to be able to parallelize
- Improvements in timing_advance_offset and timing_advance_offset_nsec
computation
- Introduce SRS multi-symbol channel estimation
- The channel impulse response is estimated from the averaged
channel frequency response over multiple symbols
- The channel frequency estimates are left as they are to be able to
estimate doppler in the future
- Simplify SRS channel estimation to handle memory alignment in the
case of different SRS configurations (eg: comboffset)
To use multiple symbols when running gNB, the following parameters needs
to be edited in the function get_srs_resource()
- srs_res->resourceMapping.startPosition with a range from {0,1,..,5}
corresponds to the start symbol {13, 12, .. 8} with in a slot
- srs_res->resourceMapping.nrofSymbols indicates the number of symbols
{n1, n2, and n4}
Make sure the that start symbol + number of symbols is < 14
The timing results for SRS in develop and srs_phy_simulator are as follows:
Command used: sudo ./nr_ulsim -n1000 -s50 -S50 -R273 -W2 -y2 -z2 -E 1 -P
develop
|__ RX SRS time 124.94 us (1000 trials) (124.94 total [ms])
|__ Generate SRS sequence time 0.05 us (1000 trials) ( 0.05 total [ms])
|__ Get SRS signal time 19.41 us (1000 trials) ( 19.41 total [ms])
|__ SRS channel estimation time 89.11 us (1000 trials) ( 89.11 total [ms])
|__ SRS timing advance estimation time 13.10 us (1000 trials) ( 13.10 total [ms])
|__ SRS report TLV build time 2.80 us (1000 trials) ( 2.80 total [ms])
|__ SRS beam report build time 0.00 us ( 0 trials)
|__ SRS IQ matrix build time 2.73 us (1000 trials)
srs_phy_simulator
|__ RX SRS time 211.93 us (1000 trials) (211.93 total [ms])
|__ Generate SRS sequence time 0.04 us (1000 trials) ( 0.04 total [ms])
|__ Get SRS signal time 19.55 us (1000 trials) ( 19.55 total [ms])
|__ SRS channel estimation time 152.05 us (1000 trials) (152.05 total [ms])
|__ SRS timing advance estimation time 36.67 us (1000 trials) ( 36.67 total [ms])
|__ SRS report TLV build time 2.96 us (1000 trials) ( 2.96 total [ms])
|__ SRS beam report build time 0.00 us ( 0 trials)
|__ SRS IQ matrix build time 2.88 us (1000 trials)
Note that in srs_phy_simulator, to compute timing offset ns, an
oversampling factor of 2 is performed. Also, for peak detection, we
average the channel estimates for every port.
atoi() used previously does not capture all of unsigned long (so we
could not reproduce a high seed), and its use is discouraged as it does
not detect errors. Use strtoul() instead, which allows to also use other
bases (so we can e.g., write OAI_RNGSEED=0x1234)
Hide normal table initialization of Ziggurat generator from outside to
force the usage of randominit() for RNG initialization. In this step,
remove the randominit() seed parameter and only rely on OAI_RNGSEED for
a consistent RNG initialization, as this parameter was used differently
("0" as fixed number or to force a random seed).
Now, only use OAI_RNGSEED env variable to force the usage of a fixed
seed.
Since there is no UCI on PUSCH implementation in gNB, it is good to test
UE's implementation with matlab.
This commit allows to test with matlab in two ways:
1. generate OFDM waveform from ulsim and decode it in matlab using
uci_on_pusch_decode.m
2. generate codeword in matlab using uci_on_pusch_encode.m read it in
ulsim and compare the bits. ulsim option -o is used
Added a libary that can connect to a channel emulator and provide taps
as they are generated.
- Enable connection from vrtsim to channel emulation server
- Depends on flatbuffers definition file from raytracing-channel-emulator
- Depends on libanomsg-dev and flatbuffers-compiler (Ubuntu) or equivalent
- Added a compile time option ENABLE_TAPS_CLIENT to prevent other users
from being affected by additional dependencies
Use `rfsimu_channel_ue1`, `rfsimu_channel_ue2`, etc. if you want to
use different channel models for each client. The client connection
order determines its channel model name.
Added new command line option to channelmod: noise_power_dBFS. This options
allows the user to configure noise power in dBFS added instead of the per-channel
value.
This makes it so noise is not accumulated per channel reaching higher than expected
values.
The dBFS unit allows easy configuration. The gNB by default uses -36 dBFS setting.
To reach 3dB SNR one should set the noise_power_dBFS value to -39.
To configure using command line use --channelmod.noise_power_dBFS -50. Using this
setting the gNB and nrUE connect without issue.
Add the option `--rfsimulator.prop_delay` to specify the simulated receive-path (gNB: UL, UE: DL) propagation delay in ms.
This option can be used e.g. to simulate a simple GEO satellite channel by specifying `--rfsimulator.prop_delay 238.74` to both, the gNB and the UE.
This is part of the work developed by Fraunhofer IIS within the ESA-funded project 5G-GOA (https://connectivity.esa.int/projects/5ggoa).
- deleted: ../../../executables/rfsim.c
- removed unused command line options to set SINR and SNR
- removed unused functions to get SINR and SNR
- removed unused RFSIM struct members
maki
francescomani