Auralization of High-Order Directional Sources from First-Order RIR Measurements

Can auralization of a highly directional source in a room succeed if it employs a room impulse response (RIR) measurement or simulation relying on a first-order directional source, only? This contribution presents model and evaluation of a source-and-receiver-directional Ambisonics RIR capture and processing approach (SRD ARIR) based on a small set of responses from a first-order source to a first-order receiver. To enhance the directional resolution, we extend the Ambisonic spatial decomposition method (ASDM) to upscale the first-order resolution of both source and receiver to higher orders. To evaluate the method, a listening experiment was conducted based on first-order SRD-ARIR measurements, into which the higher-order directivity of icosahedral loudspeaker’s (IKO) was inserted as directional source of well-studied perceptual effects. The results show how the proposed method performs and compares to alternative rendering methods based on measurements taken in the same acoustic environment, e.g., multiple-orientation binaural room impulse responses (MOBRIRs) from the physical IKO to the KU-100 dummy head, or higher-order SRD ARIRs from IKO to em32 Eigenmike. For optimal externalization, our experiments exploit the benefits of virtual reality, using a highly realistic visualization on head-mounted-display, and a user interface to report localization by placing interactive visual objects in the virtual space.

Research on Cooperative Communication Strategy and Intelligent Agent Directional Source Grouping Algorithms for Internet of Things

In order to improve the network layer of the Internet of things to improve transmission reliability, save time delay and energy consumption, the Internet of things cooperative communication and intelligent agent technology were studied in this paper. In cooperative communication, a new cooperative communication algorithm KCN (k-cooperative node), and a reliability prediction model are proposed. The k value is determined by the end-to-end reliability. After k cooperative nodes are selected, other nodes enter dormancy. In aggregate traffic allocation, game theory is used to model the traffic equilibrium and end-to-end delay optimization scenarios. In practice, the optimal duty cycle can be calculated, which makes some cooperative nodes enter an idle state to save energy. Under the premise of guaranteeing end-to-end delay, it is shown that the reliability of the proposed KCN algorithm is better than that of the other existing routing protocols. In the aspect of intelligent agent, a directional source grouping algorithm D-MIP is proposed. This algorithm studies the routing problem of multi-agent parallel access to multiple source nodes. A directed source packet multi-agent routing planning algorithm is proposed. The iterative algorithm of each source node is limited to a sector, and the optimal intelligent agent route is obtained by selecting an appropriate angle. Compared with other algorithms, it is shown through a lot of simulated results that energy consumption and time delay has been saved by the proposed D-MIP algorithm.