Multihop Rate Adaptive Wireless Scalable Video Using Syndrome-Based Partial Decoding

Abstract

The overall channel capacity of a multihop wireless path drops progressively over each hop due to the cascading effect of noise and interference. Hence, without optimal rate adaptation, the video quality is expected to degrade significantly at any client located at a far-edge of an ad-hoc network. To overcome this limitation, decoding and forwarding (DF), which fully decodes codewords at each intermediate node, can be employed to provide the best video quality. However, complexity and memory usage for DF are significantly high. Consequently, we propose syndrome-based partial decoding (SPD). In the SPD framework an intermediate node partially decodes a codeword and relays the packet along with its syndromes if the packet is corrupted. We demonstrate the efficacy of the proposed scheme by simulations using actual 802.11b wireless traces. The trace-driven simulations show that the proposed SPD framework, which reduces the overall processing requirements of intermediate nodes, provides reasonably high goodput when compared to simple forwarding and less complexity and memory requirements when compared to DF.