WiFi networks have been globally deployed and most mobile devices are currently WiFi-enabled. While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. In this paper, we present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast services. AMuSe is based on accurate receiver feedback and incurs a small control overhead. In particular, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information about the channel quality to the multicast sender. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. AMuSe does not require any changes to the standards or any modifications to the WiFi devices. We implemented AMuSe on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi devices, both with and without interference sources. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions.

IEEE 802.11-based wireless local area networks, referred to as WiFi, have been globally deployed and the vast majority of mobile devices are currently WiFi-enabled. While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. We propose AMuSe, a scalable and adaptive interference mitigation solution for WiFi multicast services which is based on accurate receiver feedback and that incurs a small control overhead. Specifically, we develop a scheme for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information, such as channel quality or received packet statistics, to the multicast sender. This feedback information is used by the multicast sender to optimize the multicast service quality, e.g., by dynamically adjusting the transmission bit-rate. Our proposed solution does not require any changes to the standards or any modifications to the WiFi devices. We have implemented the proposed solution in the ORBIT testbed and evaluated its performance in large groups with approximately 250 receivers, both with and without interference sources. Our online experiments demonstrate that our system provides practical multicast services that can accommodate hundreds of receivers.

In this paper we explore the concept of self-organized location management in large-scale networks of femtocells (NoFs). A NoF is a mesh network that provides multi-hop connectivity amongst femtocells and, in turn, to the Evolved Packet Core. One of the most challenging issues in NoFs is location management, i.e., the process of determining the location of a User Equipment (UE) in the network. Standard 3GPP location management mechanisms are not well suited for large-scale NoFs due to the overhead generated by frequent handovers and cell reselections. In this paper we propose a self-organized Tracking Area List (TAL) mechanism that seamlessly monitors the mobility state of each UE in order to adjust the size of its individual TAL dynamically. Analytical results show that our mechanism reduces location signalling traffic in the cellular network compared to standard 3GPP schemes. In addition, the self-organized TAL mechanism is fully compliant with 3GPP LTE Technical Specifications, which facilitates its implementation in a commercial scenario.

In this paper we explore the concept of an all-wireless Network of Femtocells (NoF). A NoF can be seen as a wireless mesh network providing multi-hop connectivity amongst femtocells and, in turn, to the Evolved Packet Core (EPC). As specified by 3GPP Technical Specifications (TS), IP networks are used to transport data through any interface and, in particular, through the S1 interface in the Evolved Packet System (EPS). More specifically, the transport network layer of the NoF acts as transport for the control- and user-plane data through the S1-MME and S1-U interfaces, respectively. This novel scenario requires specific algorithms for the optimal routing of packets through the S1 interface within the NoF. In order to do so, we propose DiPUMP, a distributed and stateless routing protocol based on backpressure theory. Up to our knowledge, DiPUMP is the first protocol proposed to support control- and user-plane data routing in an all-wireless NoF. We also compare DiPUMP to AODV-ST, a tree-based routing protocol taken as representative for routing protocols commonly found in data networking scenarios that are equivalent to NoFs. Our evaluation results show that, on average, DiPUMP is able to transfer up to a 30% more traffic load than AODV-ST. Finally, we describe the implications of the NoF paradigm and DiPUMP in the 3GPP architecture.