Mahdy Nabaee

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—In this paper, we study joint network coding and distributed source coding of inter-node dependent messages, with the perspective of compressed sensing. Specifically, the theoretical guarantees for robust 1-min recovery of an under-determined set of linear network coded sparse messages are investigated. We discuss the guarantees for 1-min decoding of(More)
Non-adaptive joint source network coding of correlated sources is discussed in this paper. By studying the information flow in the network, we propose quantized network coding as an alternative for packet forwarding. This technique has both network coding and distributed source coding advantages, simultaneously. Quantized network coding is a combination of(More)
In this paper, mathematical bases for non-adaptive joint source network coding of correlated messages in a Bayesian scenario are studied. Specifically, we introduce one-step Quantized Network Coding (QNC), which is a hybrid combination of network coding and packet forwarding for transmission. Motivated by the work on Bayesian compressed sensing, we derive(More)
The falling trend in the revenue of traditional telephony services has attracted attention to new IP based services. The IP Multi-media System (IMS) is a key architecture which provides the necessary platform for delivery of new multimedia services. However, current implementations of IMS do not offer automatic scalability or elastisity for the growing(More)
Location information of sensor nodes has become an essential part of many applications in Wireless Sensor Networks (WSN). The importance of location estimation and object tracking has made them the target of many security attacks. Various methods have tried to provide location information with high accuracy, while lots of them have neglected the fact that(More)
To my family, Farideh, Parviz and Mona who always offered me unconditional love and support. To my best friend Azin without whose caring support it would not have been possible. Abstract This thesis concerns with recovery of compressive sampled images. Since many natural signals such as images are non-stationary, the sparse space varies in time/spatial(More)