A random access MAC protocol for MPR satellite networks

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaRandom access approaches for Low Earth Orbit (LEO) satellite networks are usually incompatible with the Quality of Service (QoS) requirements of multimedia tra c, especially when hand-held devices must operate with very low power. Cross-Layered optimization architectures, combined with Multipacket Reception (MPR)schemes are a good choice to enhance the overall performance of a wireless system. Hybrid Network-assisted Diversity Multiple Access (H-NDMA) protocol, exhibits high energy e ciency, with MPR capability, but its use with satellites is limited by the high round trip time. This protocol was adapted to satellites, in Satellite-NDMA, but it required a pre-reservation mechanism that introduces a signi cant delay. This dissertation proposes a random access protocol that uses H-NDMA, for Low Earth Orbit (LEO) satellite networks, named Satellite Random-NDMA (SR-NDMA). The protocol addresses the problem inherent to satellite networks (large round trip time and signi cant energy consumption) de ning a hybrid approach with an initial random access plus possible additional scheduled retransmissions. An MPR receiver combines the multiple copies received, gradually reducing the error rate. Analytical performance models are proposed for the throughput, delay, jitter and energy e ciency considering nite queues at the terminals. It is also addressed the energy e ciency optimization, where the system parameters are calculated to guarantee the QoS requirements. The proposed system's performance is evaluated for a Single-Carrier with Frequency Domain Equalization (SC-FDE) receiver. Results show that the proposed system is energy e cient and can provide enough QoS to support services such as video telephony

Computational Models of Perceptual Organization and Bottom-up Attention in Visual and Audio-Visual Environments

Figure Ground Organization (FGO) - inferring spatial depth ordering of objects in a visual scene - involves determining which side of an occlusion boundary (OB) is figure (closer to the observer) and which is ground (further away from the observer). Attention, the process that governs how only some part of sensory information is selected for further analysis based on behavioral relevance, can be exogenous, driven by stimulus properties such as an abrupt sound or a bright flash, the processing of which is purely bottom-up; or endogenous (goal-driven or voluntary), where top-down factors such as familiarity, aesthetic quality, etc., determine attentional selection. The two main objectives of this thesis are developing computational models of: (i) FGO in visual environments; (ii) bottom-up attention in audio-visual environments. In the visual domain, we first identify Spectral Anisotropy (SA), characterized by anisotropic distribution of oriented high frequency spectral power on the figure side and lack of it on the ground side, as a novel FGO cue, that can determine Figure/Ground (FG) relations at an OB with an accuracy exceeding 60%. Next, we show a non-linear Support Vector Machine based classifier trained on the SA features achieves an accuracy close to 70% in determining FG relations, the highest for a stand-alone local cue. We then show SA can be computed in a biologically plausible manner by pooling the Complex cell responses of different scales in a specific orientation, which also achieves an accuracy greater than or equal to 60% in determining FG relations. Next, we present a biologically motivated, feed forward model of FGO incorporating convexity, surroundedness, parallelism as global cues and SA, T-junctions as local cues, where SA is computed in a biologically plausible manner. Each local cue, when added alone, gives statistically significant improvement in the model's performance. The model with both local cues achieves higher accuracy than those of models with individual cues in determining FG relations, indicating SA and T-Junctions are not mutually contradictory. Compared to the model with no local cues, the model with both local cues achieves greater than or equal to 8.78% improvement in determining FG relations at every border location of images in the BSDS dataset. In the audio-visual domain, first we build a simple computational model to explain how visual search can be aided by providing concurrent, co-spatial auditory cues. Our model shows that adding a co-spatial, concurrent auditory cue can enhance the saliency of a weakly visible target among prominent visual distractors, the behavioral effect of which could be faster reaction time and/or better search accuracy. Lastly, a bottom-up, feed-forward, proto-object based audiovisual saliency map (AVSM) for the analysis of dynamic natural scenes is presented. We demonstrate that the performance of proto-object based AVSM in detecting and localizing salient objects/events is in agreement with human judgment. In addition, we show the AVSM computed as a linear combination of visual and auditory feature conspicuity maps captures a higher number of valid salient events compared to unisensory saliency maps