Reliable Broadcast to A User Group with Limited Source Transmissions

In order to reduce the number of retransmissions and save power for the source node, we propose a two-phase coded scheme to achieve reliable broadcast from the source to a group of users with minimal source transmissions. In the first phase, the information packets are encoded with batched sparse (BATS) code, which are then broadcasted by the source node until the file can be cooperatively decoded by the user group. In the second phase, each user broadcasts the re-encoded packets to its peers based on their respective received packets from the first phase, so that the file can be decoded by each individual user. The performance of the proposed scheme is analyzed and the rank distribution at the moment of decoding is derived, which is used as input for designing the optimal BATS code. Simulation results show that the proposed scheme can reduce the total number of retransmissions compared with the traditional single-phase broadcast with optimal erasure codes. Furthermore, since a large number of transmissions are shifted from the source node to the users, power consumptions at the source node is significantly reduced.Comment: ICC 2015. arXiv admin note: substantial text overlap with arXiv:1504.0446

Using p2p networks for error recovery in mbms applications

The wireless networks are notoriously error prone and all errors cannot be prevented in real-time communications. The problem of error correction becomes even more challenging in mobile multicast/broadcast applications. The mobile devices are being equipped with multiple modems that could work simultaneously; for example, devices with both GSM (WAN) and WLAN networks such as WiFi. These multi-modal devices can use the second network to improve their error resilience. We propose a P2P approach to establish and utilize an error recovery channel on a secondary network for multi-user video applications. The mobile devices within the vicinity can utilize the WLAN network to form a P2P network for error recovery purpose. We developed and evaluated three error recovery models for error recovery over secondary networks. The proposed models balance the response time, bandwidth utilization, fairness, and unnecessary data received. 1