Multi-Dimensional Constellation for OTFS-Based Vehicular-IoT in Time-Variant Channel

The Internet of Things (IoT) is a promising application for 5G networks because it provides connected vehicle networks with an optimal blend of cost, latency, and speed. The IoT devices involved with vehicles are called vehicular IoT (V-IoT), requiring a dependable wireless communication system for safe and efficient operation. Compared to conventional waveforms like orthogonal frequency division multiplexing, the orthogonal time frequency space (OTFS) is superior due to its delay-Doppler domain modulation in high-mobility circumstances of V-IoTs. Integrating the $N$-dimensional ($N$-D) mapper with the improved minimum Euclidean distance (MED) into the conventional OTFS modulation technique for V-IoT can considerably enhance the bit error rate (BER) at higher modulation orders. So, we present an ND-OTFS-based V-IoT system with the proposed system's detector complexity analysis and the minimum Euclidean distance of the $N$-D signal constellations. The simulation findings demonstrate that for higher modulation orders in various time-variant channels, the proposed ND-OTFS-based V-IoT system outperforms the conventional OTFS-based V-IoT system regarding BER performance.