Design and implementation of an "approximate" communication system for wireless media applications

Abstract

All practical wireless communication systems are prone to errors. At the symbol level such wireless errors have a well-defined structure: when a receiver decodes a symbol erroneously, it is more likely that the decoded symbol is a good "approximation" of the transmitted symbol than a randomly chosen symbol among all possible transmitted symbols. Based on this property, we define approximate communication, a method that exploits this error structure to natively provide unequal error protection to data bits. Unlike traditional (FEC-based) mechanisms of unequal error protection that consumes additional network and spectrum resources to encode redundant data, the approximate communication technique achieves this property at the PHY layer without consuming any additional network or spectrum resources (apart from a minimal signaling overhead) . Approximate communication is particularly useful to media delivery applications that can benefit significantly from unequal error protection of data bits. We show the usefulness of this method to such applications by designing and implementing an end-to-end media delivery system, called Apex. Our Software Defined Radio (SDR)-based experiments reveal that Apex can improve video quality by 5 to 20 dB (PSNR) across a diverse set of wireless conditions, when compared to traditional approaches. We believe that mechanisms such as Apex can be a cornerstone in designing future wireless media delivery systems under any errorprone channel condition.

SoftCast: Clean-slate scalable wireless video

“…Recent years have witnessed much interest in making video quality scale with channel quality [3,26,28,45]. The general approach so far has been to divide the video stream into a base layer that is necessary for decoding the video, and an enhancement layer that improves its quality [8,13,16,36,37,48]. Proposals in this area differ mainly in how they generate the two layers and the code they use to protect them.…”

“…Proposals in this area differ mainly in how they generate the two layers and the code they use to protect them. For example, some proposals consider the I (reference) frames as the base layer and the P and B (differential) frames as the enhancement layer [37,48]. Recent approaches create an explicit base layer by quantizing the video to a coarse representation, which is refined by the enhancement layers [13,36].…”

“…Others employ embedded diversity coding [1,9,13], where a high-rate code allows the enhancement layer to harness good channel realizations, while the embedded high-diversity code provides guarantees that at least the base layer is received reliably. Hierarchical modulation and super-position coding are examples of this approach [7,23,37]. Motivated by this prior work, SoftCast takes scalable video one step further; it disposes of the coarse granularity of layers in favor of a continuously scalable design.…”

MISC: Merging incorrect symbols using constellation diversity for 802.11 retransmission

“…Most of the them fall within the neighborhood of the transmitted symbol point on the constellation map. Such error "locality" pattern has been used in previous communication designs, e.g., Gray mapping and Unequal Error Protetion (UEP) [11]. In this paper, we leverage such locality in a different way in retransmissions to create constellation diversity for error recovery.…”

“…We note that a low symbol error rate does not directly translate to a low bit error rate, as constellation maps normally encode bits to symbols differ- ently. In our experiment, we use the Gray-code constellation map, i.e., the default constellation map in 802.11 [11] for retransmission schemes that do not alter constellation map and the first transmission of MISC. In a Gray-code constellation map, adjacent constellation points only differ in one bit, which can reduce bit errors according to symbol error locality.…”