LoRaWAN

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The lorawan library provides structures and tools for reading and writing LoRaWAN 1.0.2 messages from and to slices of bytes.

Sample Packet manipulation

Use the library

toml [dependencies] lorawan = "0.5.0"

Packet generation

```rust use lorawan::{creator, keys, maccommands}; use heapless;

fn main() { let mut phy = creator::JoinAcceptCreator::new(); let key = keys::AES128([1; 16]); let appnoncebytes = [1; 3]; phy.setappnonce(&appnoncebytes); phy.setnetid(&[1; 3]); phy.setdevaddr(&[1; 4]); phy.setdlsettings(2); phy.setrxdelay(1); let mut freqs: heapless::Vec = heapless::Vec::new(); freqs.push(maccommands::Frequency::new(&[0x58, 0x6e, 0x84,]).unwrap()).unwrap(); freqs.push(maccommands::Frequency::new(&[0x88, 0x66, 0x84,]).unwrap()).unwrap(); phy.setcf_list(freqs).unwrap(); let payload = phy.build(&key).unwrap(); println!("Payload: {:x?}", payload); } ```

Packet parsing

```rust use lorawan::parser::; use lorawan::keys::;

fn main() { let data = vec![0x40, 0x04, 0x03, 0x02, 0x01, 0x80, 0x01, 0x00, 0x01, 0xa6, 0x94, 0x64, 0x26, 0x15, 0xd6, 0xc3, 0xb5, 0x82]; if let Ok(PhyPayload::Data(DataPayload::Encrypted(phy))) = parse(data) { let key = AES128([1; 16]); let decrypted = phy.decrypt(None, Some(&key), 1).unwrap(); if let Ok(FRMPayload::Data(datapayload)) = decrypted.frmpayload() { println!("{}", String::fromutf8lossy(data_payload)); } } else { panic!("failed to parse data payload"); } } ```

Benchmarks

Ran on Intel i7-8550U CPU @ 1.80GHz with 16GB RAM running Ubuntu 18.04.

pkg: github.com/brocaar/lorawan BenchmarkDecode-8 40410 150498 ns/op BenchmarkValidateMic-8 2959 2026736 ns/op BenchmarkDecrypt-8 9390 648402 ns/op

``` Running target/release/deps/lorawan-32e80b41705c7d41 Gnuplot not found, using plotters backend

datapayloadheaders_parsing time: [30.354 ns 30.430 ns 30.497 ns] change: [-5.5657% -5.1359% -4.7052%] (p = 0.00 < 0.05) Performance has improved. Found 1 outliers among 100 measurements (1.00%) 1 (1.00%) high mild

Approximate memory usage per iteration: 1 from 303847227

datapayloadmic_validation time: [2.2334 us 2.2388 us 2.2476 us] change: [-3.7708% -3.3970% -2.8941%] (p = 0.00 < 0.05) Performance has improved. Found 20 outliers among 100 measurements (20.00%) 2 (2.00%) low severe 5 (5.00%) low mild 2 (2.00%) high mild 11 (11.00%) high severe

Approximate memory usage per iteration: 114 from 4349451

datapayloaddecrypt time: [1.1179 us 1.1186 us 1.1193 us] change: [-0.8167% -0.4650% -0.1514%] (p = 0.00 < 0.05) Change within noise threshold. Found 8 outliers among 100 measurements (8.00%) 2 (2.00%) low severe 2 (2.00%) low mild 3 (3.00%) high mild 1 (1.00%) high severe

Approximate memory usage per iteration: 57 from 8668603 ```