This paper focuses on the QoS-constrained jointly optimal adaptive distributed source coding, channel coding, network coding and power control for Co-Channel Interference (CCI)-limited wireless multiple class multicast networks, such as, for example, Wireless Sensor Networks (WSNs). The goal is to allocate the available system-wide resources by jointly performing Loss-Less Distributed Source Coding (LLDSC) and Intra-Session Network Coding (ISNC), while leveraging channel coding and power control for CCI-mitigation. Due to the presence of CCI, the resulting cross-layer optimization problem is inherently nonconvex. Hence, we develop a distributed, iterative and asynchronous algorithm for the optimal adaptive QoS management of the available bandwidth/power/flow resources. Actual performance and adaptive capability of the proposed resource management algorithm in the presence of: i) abrupt changes of the statistics of the source flows; ii) failures of the interior network nodes; and, iii) fast fading, are numerically tested.
Interference Management for Multiple Multicasts with Joint Distributed Source/Channel/Network Coding / Cordeschi, Nicola; Polli, Valentina; Baccarelli, Enzo. - In: IEEE TRANSACTIONS ON COMMUNICATIONS. - ISSN 0090-6778. - STAMPA. - 61:12(2013), pp. 5176-5183. [10.1109/tcomm.2013.111113.120904]
Interference Management for Multiple Multicasts with Joint Distributed Source/Channel/Network Coding
CORDESCHI, Nicola;POLLI, VALENTINA;BACCARELLI, Enzo
2013
Abstract
This paper focuses on the QoS-constrained jointly optimal adaptive distributed source coding, channel coding, network coding and power control for Co-Channel Interference (CCI)-limited wireless multiple class multicast networks, such as, for example, Wireless Sensor Networks (WSNs). The goal is to allocate the available system-wide resources by jointly performing Loss-Less Distributed Source Coding (LLDSC) and Intra-Session Network Coding (ISNC), while leveraging channel coding and power control for CCI-mitigation. Due to the presence of CCI, the resulting cross-layer optimization problem is inherently nonconvex. Hence, we develop a distributed, iterative and asynchronous algorithm for the optimal adaptive QoS management of the available bandwidth/power/flow resources. Actual performance and adaptive capability of the proposed resource management algorithm in the presence of: i) abrupt changes of the statistics of the source flows; ii) failures of the interior network nodes; and, iii) fast fading, are numerically tested.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.