A cross-layer solution for enabling real-time video transmission over IEEE 802.15.4 networks

2010 ◽  
Vol 51 (3) ◽  
pp. 1069-1104 ◽  
Author(s):  
Antonio-Javier Garcia-Sanchez ◽  
Felipe Garcia-Sanchez ◽  
Joan Garcia-Haro ◽  
Fernando Losilla
2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Slavche Pejoski ◽  
Venceslav Kafedziski

We present a framework for cross-layer optimized real time multiuser encoding of video using a single layer H.264/AVC and transmission over MIMO wireless channels. In the proposed cross-layer adaptation, the channel of every user is characterized by the probability density function of its channel mutual information and the performance of the H.264/AVC encoder is modeled by a rate distortion model that takes into account the channel errors. These models are used during the resource allocation of the available slots in a TDMA MIMO communication system with capacity achieving channel codes. This framework allows for adaptation to the statistics of the wireless channel and to the available resources in the system and utilization of the multiuser diversity of the transmitted video sequences. We show the effectiveness of the proposed framework for video transmission over Rayleigh MIMO block fading channels, when channel distribution information is available at the transmitter.


Physical characteristics limits the capability of sensor network in case of underwater deployment. Factors like medium delay, doppler spreads and limited bandwidth are challengers to achieve a QoS (Quality of Service) guarantee in under water acoustic sensor networks. Under these conditions maximizing the bandwidth availability with consideration for application traffic requirements is important. This work proposes a service differentiated QOS guaranteed cross layer solution to maximize the available bandwidth and life time of the network under the constraints of application traffic requirements. At all different layers of IEEE 802.15.4 protocol stack, i.e., Application Layer, Session Layer, Network Layer, MAC Layer, and PHY Layer, the solution uses network parametes to optimize available bandwidth and also QoS. The solution involves redundancy and prediction based content coding at application layer, QoS based rate control at session layer, load based routing, transmission range adjustment at physical layer for guaranteed QoS delivery over acoustic sensor network.


2015 ◽  
Vol 17 (9) ◽  
pp. 1495-1507 ◽  
Author(s):  
Rui Deng ◽  
Guizhong Liu ◽  
Jian Yang

2007 ◽  
Vol 17 (5) ◽  
pp. 347-361 ◽  
Author(s):  
Dionysia Triantafyllopoulou ◽  
Nikos Passas ◽  
Apostolis K. Salkintzis ◽  
Alexandros Kaloxylos

Sign in / Sign up

Export Citation Format

Share Document