Transmitting Important Bits and Sailing High Radio Waves: A Decentralized Cross-Layer Approach to Cooperative Video Transmission

Abstract

We investigate the impact of cooperative relaying on uplink and downlink multi-user (MU) wireless video transmissions. The objective is to maximize the long-term sum of utilities across the video terminals in a decentralized fashion, by jointly optimizing the packet scheduling, the resource allocation, and the cooperation decisions, under the assumption that some nodes are willing to act as cooperative relays. A pricing-based distributed resource allocation framework is adopted, where the price reflects the expected future congestion in the network. Specifically, we formulate the wireless video transmission problem as an MU Markov decision process (MDP) that explicitly considers the cooperation at the physical layer and the medium access control sublayer, the video users' heterogeneous traffic characteristics, the dynamically varying network conditions, and the coupling among the users' transmission strategies across time due to the shared wireless resource. Although MDPs notoriously suffer from the curse of dimensionality, our study shows that, with appropriate simplications and approximations, the complexity of the MU-MDP can be significantly mitigated. Our simulation results demonstrate that integrating cooperative decisions into the MU-MDP optimization can increase the resource price in networks that only support low transmission rates and can decrease the price in networks that support high transmission rates. Additionally, our results show that cooperation allows users with feeble direct signals to achieve improvements in video quality on the order of 5 − 10 dB peak signal-to-noise ratio (PSNR), with less than 0.8 dB quality loss by users with strong direct signals, and with a moderate increase in total network energy consumption that is significantly less than the energy that a distant node would require to achieve an equivalent PSNR without exploiting cooperative diversity. Index TermsCooperative communications, cross-layer optimization, decode-and-forward relaying, Markov decision process (MDP), multi-user scheduling, resource allocation, wireless video transmission.

Video Transmission Over Lossy Wireless Networks: A Cross-Layer Perspective

“…While a detailed treatment of these approaches is out of the scope of this paper, we take cooperative relaying as an example to show how these technologies can be used to enhance wireless video quality [59], [67]. Cooperative relaying.…”

“…We found that a noticeable gain in sum PSNR can be achieved through cooperative relaying with in practice even lower average transmission power compared to using direct transmissions only. The effectiveness of cooperative relaying is also demonstrated in [67] by considering uplink wireless video streaming in cellular networks.…”

A cooperative protocol for video streaming in dense small cell wireless relay networks

“…Recently, there are some works towards this direction. In [11] the authors proposed relay selection in a cooperative system by modeling the system as a Markov decision process (MDP). The communication model considers both uplink and downlink cooperative transmissions towards an access point (AP).…”

“…The first difference is that we remove the assumption that the source requires the recruitment of relays with a type of request-to-send and clear-to-send (RTS/CTS) exchange like the schemes reported in [10,11]. The source in our proposal is agnostic to the small cell relays and how they select to cooperate.…”

Cross-layer transmission for video streaming in wireless relay networks

“…The method regards packet delay deadline and end-to-end distortion as the metric of scheduling scheme, and discusses the problem in multi-hop wireless networks. Moreover, the transmission problem is modeled as a multi-user Markov decision process (MU-MDP) in [10] and [11], and a Lagrangian relaxation method is used to divide it into local MDPs. these works schedule packets dynamically, and optimize the transmissions in wireless network with multiusers.…”