M-health services are expected to become increasingly relevant in the management of emergency situations by enabling real-time support of remote medical experts. In this context, the transmission of multiple health-related video streams from an ambulance to a remote hospital can improve the efficacy of the teleconsultation service, but requires a large bandwidth to meet the desired quality, not always guaranteed by the mobile network. In order to deliver the multiple streams over a single bandwidth-limited wireless access channel, in this paper we propose a novel optimization framework that enables to classify the available video sources and to automatically select and adapt the best streams to transmit. The camera ranking algorithm jointly works with a cross-layer adaptation strategy for multiple scalable streams to achieve different objectives and/or tradeoffs in terms of number and target quality of the transmitted videos. The final goal of the optimization is to dynamically adjust the overall transmitted throughput to meet the actual available bandwidth, while being able to provide high quality to diagnostic video sequences and lower quality to less critical ambient videos. Numerical simulations considering a realistic emergency scenario with long term evolution advanced (LTE-A) connectivity show that the proposed content/context-aware solution is able to automatically select the best sources of information from a visual point of view and to achieve optimal end-to-end video quality for both the diagnostic and the ambient videos.

M-health services are expected to become increasingly relevant in the management of emergency situations, enabling real-time support of remote medical experts. In this context, the transmission of health-related information from an ambulance to a remote hospital is a challenging task, due to the variability and the limitations of the mobile radio link. In particular, the transmission of multiple video streams can improve the efficacy of the tele-consultation service, but requires a large bandwidth to meet the desired quality, not always guaranteed by the mobile network. In this paper we propose a novel cross-layer adaptation strategy for multiple SVC videos delivered over a single LTE channel, which dynamically adjusts the overall transmitted throughput to meet the actual available bandwidth, while being able to provide high quality to diagnostic video sequences and lower (but fair) quality to less critical ambient videos. After having introduced a realistic LTE uplink scenario, including an advanced resource allocation strategy, we show through numerical simulations that the proposed solution is capable to achieve an optimal end-to-end video quality for both the diagnostic and the ambient videos.

We describe an optimization technique for multiuser resource allocation assuming adaptive modulation and coding (AMC) in OFDMA radio downlink communications. The resource allocation process is based on the dual solution of a weighted sum-rate maximization problem. In particular, to realistically address IP-based video and data communications, the set of considered constraints include the number of bits actually present in the different transmission buffers. Furthermore, we propose an innovative AMC solution, based on M-QAM modulation and LDPC codes, jointly working with the scheduler and capable to maximize the throughput while guaranteeing a given set of performance requirements. A simple weight adaptation algorithm is introduced to properly tune the trade off between opportunistic transmissions and fairness among users. Several simulation results are presented to validate the proposed approach and a comparison with more traditional schemes is provided. In particular, we show that a good trade off between user fairness and opportunistic exploitation of the radio channel can be reached with the proposed strategies, improving the communication quality for both real-time video and non real-time data applications.

In this work we describe an optimization technique for multiuser resource allocation and adaptive modulation and coding (AMC) in OFDMA radio downlink communications. In particular, we propose an innovative AMC solution, based on M-QAM modulation and LDPC codes, jointly working with the scheduler and capable to maximize the achieved throughput while guaranteeing a given set of BER/FER requirements. Simulation results are presented to validate the proposed approach and a comparison with more traditional schemes is provided.

In this paper, packet-level coding is considered in the framework of H.264/AVC video transmission. Two distinct solutions are proposed and compared in different realistic communication scenarios. The first is based on classical Reed-Solomon (RS) codes applied at the RTP layer, while the second on modern LDPC codes implemented at the UDP-Lite layer. An end-to-end Quality of Experience (QoE) evaluation is presented, in terms of achieved peak signal-to-noise power ratio (PSNR). Our numerical results show that, in low-latency video applications across communication channels introducing errors and erasures, the adoption of a packet-level coding scheme becomes essential to guarantee a satisfactory quality. The solution based on LDPC codes exhibits better performances in presence of severe packet loss rates.

The architecture of a digital On-Channel Repeater (OCR) for DVB-T/H signals is described in this paper. The presence of a coupling channel between the transmitting and the receiving antennas gives origin to one or more echoes, having detrimental effects on the quality of the repeated signal and critically affecting the overall system stability. A low-complexity echo canceller unit is then proposed, performing a coupling channel estimation based on the local transmission of low-power training signals. In particular, in this paper we focus on the stability issues which arise due to the non perfect echo cancellation. An upper bound on the probability of instability of the system is analytically found, providing useful guidelines for conservative OCR design, and some performance figures concerning different propagation scenarios are provided.

M-health is an emerging area of research and one of the key challenges in future research in this area is medical video streaming over wireless channels. Contrasting requirements of almost lossless compression and low available bandwidth have to be tackled in medical quality video streaming in ultrasound and radiology applications. On one side, compression techniques need to be conservative, in order to avoid removing perceptively important information; on the other side, error resilience and correction should be provided, with the constraint of a limited bandwidth. A quality-driven, network-aware approach for joint source and channel coding based on a controller structure specifically designed for enhanced video streaming in a robotic teleultrasonography system is presented. The designed application based on robotic teleultrasonography is described and the proposed method is simulated in a wireless environment in two different scenarios; the video quality improvement achievable through the proposed scheme in such an application is remarkable, resulting in a peak signal-to-noise ratio (PSNR) improvement of more than 4 dB in both scenarios.

This paper proposes a simple co-decoding scheme for a Writing on Dirty Paper scenario, where the transmitted signal is affected by interference known by the transmitter and thermal noise. We focused on rate-1/2 codes, suitable for low SNR regions, but the scheme is easily generalizable to different code rates. In particular our approach involves a proper combination of an LDPCC and a vector quantizer based on a convolutional code and directly allows for iterative softinformation exchanges between the respective decoders. We show that it is possible to reach BER performance within 1.2-1.3 dB from the correspondent LDPCC's in AWGN channels. Moreover, the obtained performance are completely unaffected by the amount of interference.

Future wireless video transmission systems would consider OFDM (orthogonal frequency division multiplexing) as basic modulation technique due to its robustness and low complexity implementation in the presence of frequency selective channels. Recently, adaptive bit loading techniques have been applied to OFDM showing good performance gains in cable transmission systems. In this paper adaptive loading techniques are applied to an OFDM wireless system in the 5 GHz band for efficient layered multimedia traffic transmission. A low complexity scheme is introduced and compared with other solutions to realize unequal error protection both at coding and modulation level. The large impact of this technique in terms of video quality is evaluated for MPEG-4 video transmission.