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. © 2013 IEEE.
Interference management for multiple multicasts with joint distributed source/channel/network coding / Cordeschi, N.; Polli, V.; Baccarelli, E.. - In: IEEE TRANSACTIONS ON COMMUNICATIONS. - ISSN 0090-6778. - 61:12(2013), pp. 120904.5176-120904.5183. [10.1109/TCOMM.2013.111113.120904]
Interference management for multiple multicasts with joint distributed source/channel/network coding
Cordeschi N.;
2013-01-01
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. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.