Abstract-The increasingly dense deployments of wireless CSMA networks arising from applications of Internet-of-things call for an improvement to mitigate the interference among simultaneous transmitting wireless devices. For cost efficiency and backward compatibility with legacy transceiver hardware, a simple approach to address interference is by appropriately configuring the carrier sensing thresholds in wireless CSMA protocols, particularly in dense wireless networks. Most prior studies of the configuration of carrier sensing thresholds are based on a simplified conflict graph model, whereas this paper considers a realistic signal-to-interference-and-noise ratio model. We provide a comprehensive study for two effective wireless CSMA protocols: Cumulative-interference-Power Carrier Sensing and Incremental-interference-Power Carrier Sensing, in two aspects: (1) static approach that sets a universal carrier sensing threshold to ensure interference-safe transmissions regardless of network topology, and (2) adaptive approach that adjusts the carrier sensing thresholds dynamically based on the feedback of nearby transmissions. We also provide simulation studies to evaluate the starvation ratio, fairness, and goodput of our approaches.

No abstract

This paper studies the application of physical-layer network coding (PNC) in vehicleto-everything communications to accommodate the time-critical nature of vehicular ad-hoc networks (VANETs). The idea can theoretically reduce the transmission latency by 50%, thus alleviating the short contact time issues caused by high-speed vehicle motion. Conventional studies of PNC primarily considered static networks. In highly mobile networks like VANETs, the carrier frequency offsets (CFOs) due to high-speed motion will lead to inter-carrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems. Moreover, the vehicular environment with time-frequency-selective channels further undermines accurate channel estimation for multiple users. It is also worth noting that the CFO that exists in OFDM modulated PNC cannot be completely eliminated through CFO tracking and equalization as in conventional point-to-point transmissions. These critical issues can significantly increase the bit error rate at the receiver. To address these challenges, this paper proposes an ICI-aware approach that jointly achieves accurate channel estimation, signal detection, and channel decoding. We express the channel estimation and detection and decoding as two optimization problems and resolve them with the expectation-maximization algorithm and the belief propagation algorithm, respectively. The proposed approach can efficiently mitigate the negative effect of ICI by exploiting both pilot and data tones in channel estimation, detection, and decoding. Both simulation and experiment are conducted to evaluate the proposed approach, and the results reveal that the proposed algorithm outperforms the benchmark that simply treats ICI as Gaussian noise.

No abstract

No abstract