The service broker provides service providers with virtualized services that can be initialized rapidly and scaled up or down on demand. This demonstration paper describes how a service provider can set up a new video distribution service to end users with a diminutive effort. Our proposal makes use of Docker lightweight virtualization technologies that pack services in containers. This makes it possible to implement video coding and content delivery networks that are scalable and consume resources only when needed. The demonstration showcases a scenario where a video service provider sets up a new live video distribution service to end users. After the setup, live 720p30 video camera feed is encoded in real-time, streamed in HEVC MPEG-DASH format over CDN network, and accessed with a HbbTV compatible set-top-box. This end-to-end system illustrates that virtualization causes no significant resource or performance overhead but is a perfect match for online video services.

A relay channel with orthogonal components in which the destination is affected by an interference signal that is non-causally available only at the source is studied. The interference signal has structure in that it is produced by another transmitter communicating with its own destination. Moreover, the interferer is not willing to adjust its communication strategy to minimize the interference. Knowledge of the interferer's signal may be acquired by the source, for instance, by exploiting HARQ retransmissions on the interferer's link. The source can then utilize the relay not only for communicating its own message, but also for cooperative interference mitigation at the destination by informing the relay about the interference signal. Proposed transmission strategies are based on partial decode-and-forward (PDF) relaying and leverage the interference structure. Achievable schemes are derived for discrete memoryless models, Gaussian and Ricean fading channels. Furthermore, optimal strategies are identified in some special cases. Finally, numerical results bring insight into the advantages of utilizing the interference structure at the source, relay or destination.

A cooperative network where the transmission between two nodes is assisted by many half-duplex relays over parallel Gaussian channels is considered. The parallel channel model is suitable for a broadband system, such as orthogonal frequency division multiplexing or a block fading channel. For the decode-and-forward protocol, an optimization problem for joint power, time and subchannel allocation under per-node power constraints is formulated to maximize the total transmission rate between the source and the destination. To solve this optimization problem, first the optimal power allocation for a given subchannel allocation is found. Then a greedy algorithm that jointly allocates subchannels and power is described. Finally, the time allocation is optimized by a numerical search procedure. The limiting case where the number of subchannels goes to infinity is also studied. Numerical results reveal that the achieved rate for the infinite number of subchannels is an upper bound for the finite subchannel case and the proposed greedy algorithm results in rates close to those for infinite number of subchannels when the number of subchannels is sufficiently large. Furthermore, most of the cooperative gains can be achieved by the use of a small number of relays.

Orthogonal frequency-division multiple access (OFDMA) exploits the frequency selective property of a wireless communication channel by allocating subchannels to individual users. Conventional multicast systems, however, suffer from diversified channel conditions among users. The main contribution of this paper is to maximize the multicast rate of one multicast session while being fair among users and build a general framework for resource allocation for multi multicast sessions. By assuming availability of channel state information, we study resource allocation in a multicast OFDMA system. We first study one multicast session system and solve the resource allocation problem in two steps. We first propose a novel subchannel allocation algorithm by allocating each subchannel to a group of users in the multicast session based on their subchannels gains. Second, a bit loading algorithm is also proposed. We further study multiple multicast transmission systems and propose a greedy algorithm for resource allocation to achieve proportional fairness among sessions. Finally, we numerically show that proposed algorithms outperform conventional multicast schemes and previous works for one multicast scenario and conventional multicast schemes for multi multicast scenario.