Nowadays, throughputs, average path utilization and transmission efficiency are still the important factors which affect the
quality of satellite communication. Recently, MORE (MAC-independence Opportunistic Routing) protocol was put forward
to improve the throughput and transmission efficiency in ground wireless network. However, MORE is not appropriate for
satellites network because satellites available do not have the monitor ability which is necessary in MORE and it is also too
expensive to monitor in satellites. In this paper, an improved MORE protocol was proposed to apply to satellites, which is
called path scalable network coding (PSNC) protocol. The theoretical analysis reveals the feasibility and effectiveness of the
proposed algorithm. The simulation results show that the algorithm can effectively increase the average path utilization and
the innovative packet ratio over satellite networks.
Satellite communications have been rapidly developed due to its advantageous of wide coverage and large capacity.
However, an efficient and robust transmission scheme still needs carefully designed due to the time-varying and
unreliable nature of links of the satellite networks. In this paper, we consider cooperative communications by selecting
relays dynamically via setting an appropriate threshold according to the real-time channel conditions to avoid error
propagation and then apply opportunistic network coding (ONC) to further enhance network throughput. Considering the
sparse representation of natural images, block based compressive sensing (BCS) and the proposed ONC are combined in
a novel way forming an energy-efficient image processing system which is easy to be implemented. Simulation results
show that the scheme we proposed can gain better performances compared with traditional cooperative and network
Recently, providing reliable transmission over satellite networks is still a challenging problem due to the dynamic changes of the satellite topology, the large delay and the high error rate of the satellites’ links. The benefits of network coding are well understood to solve those problems above for a large class of wireless networks. In this paper, a new coding-aware routing algorithm is proposed to decrease the large delay and improve the transmission efficiency by performing network coding opportunistically instead of using network coding always or using the shortest path routing only. The theoretical analysis and simulation results show the correctness and effectiveness of the proposed algorithm.
Nowadays, providing reliable broadcast and multicast transmission over wireless networks is still a challenging problem,
due to the erratic and time-varying nature of a wireless channel. An efficient retransmission strategy is very important to
the reliability of transmission and the bandwidth utility of the wireless network. In this paper, an opportunistic network
coding retransmission algorithm based on packet loss pattern is proposed to improve the transmission efficiency of
broadcast and multicast over wireless networks. The theoretical analysis reveals the feasibility and effectiveness of the
proposed algorithm. The simulation results show that the algorithm can effectively reduce the retransmission times and
increase the transmission efficiency over wireless networks.
In EDCA-based wireless networks, all video packets are identically mapped without differentiation into one of four
access categories to be transmitted so that the delivery performance is restricted. Even though some researches remapped
video packets by differentiating their significance according to packets types, they refrained from more gains since they
adopted a type of fixed significance model and mapping scheme. In this paper, a new model for video packet
significance is built and then a dynamically mapping algorithm based on the packet significance model is proposed to
improve the performance of video delivery over EDCA-based wireless networks. The proposed algorithm detects
periodically the available resources of each AC and makes full use of the all ACs to transmit video packets. Simulation
results demonstrate that the proposed algorithm improves performance of video delivery and increases the image quality.
One of the most challenging issues in video transmission over wireless networks is to address the rigid time bounded
constraint for video delivery. We propose in this paper a deadline-aware transmission framework (DATF) for video over
IEEE 802.11e EDCA wireless networks. In this new framework, we estimate the deadline for time bounded video
delivery for each packet in queues at MAC layer according to the sequence number of a frame a given video data packet
belonging to as well as the current network delay. Then, the MAC layer determines whether a packet should be sent or
should be dropped based on the estimated deadline information. To accomplish the scheme of DATF, we propose to
modify the mapping scheme in IEEE 802.11e EDCA to facilitate unequal deadline requirement of video packets. Instead
of mapping all video packets into class AC_VI, which is defined for video data in IEEE 802.11e EDCA, we differentiate
video packets further based on the dependency characteristics of a given frame type. The proposed DATF scheme has
been implemented with NS-2 simulation based on the scenario of wired-cum-wireless network architecture. We compare
the proposed approach with several competing schemes and the simulation results show that the proposed scheme
outperforms these competing schemes in terms of both wireless networking metrics and received video quality.
In this paper, we present a novel data partitioning method, based on motion estimation, aiming at preventing error
propagation when transmitting video streaming over wireless networks. Macroblock is treated as basic unit in this
method, and all macroblocks of a coded frame are differentiated into different levels of importance according to their
own impact factor which is defined based on combination of two types of impact: one is the impact of a macroblock on
the quality of next frame and the other is the impact on the quality of current frame. The first impact is evaluated by
counting the total of referred times of all pixel within the macroblock and the second one is evaluated by calculating
difference between original and predicted macroblock. Then, combined with header information, all macroblocks of a
coded frame is partitioned into three types of partitions. Finally, different rates of FEC channel code are applied to
different partitions such that the important data can be protected strongly. While improving the quality of video like
other data partitioning methods, an advantage of the proposed method is to balance the quality of the current and the
next frame. Compared with other data partitioning methods such as in H.263++ and H.264, the proposed method can
efficiently limit error and prevent error propagation. Experimental results show the proposed method has obtained stable
quality for entire video sequence and achieve better PSNR under the two-state Markov channel model.