We consider the problem of multicasting from a single source to multiple destinations over the erasure channel. We are interested in energy efficient communication. Our performance metric is the number of bits sent per joule of energy spent until a finite amount of packets is delivered from the source to all the destinations. We compare the performance of Random Linear Network Coding (RLNC) and Automatic Repeat reQuest (ARQ) with respect to the above performance metric. Our numerical results illustrate that RLNC is more energy efficient than ARQ when the unreliability of links is high.

We consider the problem of multicasting from a single source to multiple destinations over an erasure channel model. We are interested in energy-efficient communication. Our performance metric is the number of bits that the source delivers successfully to all destinations per joule of the overall energy spent. We compare the performance of Random Linear Network Coding (RLNC) and Automatic Repeat reQuest (ARQ) with respect to the above performance metric in the presence and absence of Forward Error Correction (FEC). Our numerical results illustrate that RLNC is more energy-efficient than ARQ when the links are highly unreliable. However, as the reliability protection provided to the links through FEC increases the energy-efficiency performance of RLNC deteriorates and it becomes suboptimal compared to ARQ methods.

We consider the problem of multicasting from a single source to a set of destinations. We assume that the source can either reach the destinations directly or forward its traffic through a set of relays. Due to the non-linear attenuation of the signal with distance, employing the relays can help to improve the signal quality at the destinations. Meanwhile, relays also consume energy for retransmission of the received information and the rate of communication can be decreased due to the multi-hop transmission. Under the performance objective of maximizing the common amount of information (number of bits) that the source sends to all destinations per Joule of the total energy spent, we wish to identify whether direct transmission from the source to the destinations is preferable as opposed to multi-hop forwarding through the relays. In the latter case, we also identify a) which subset of the relays should be activated, b) for how long, and c) the respective destinations that each relay has to serve. Finally, we provide a set of numerical results to support our analysis.

The problem of optimal scheduling of multicast traffic in time-varying wireless networks is studied in the framework of utility maximization. Since the wireless channel cannot be known exactly, only scheduling policies that take decisions based on a possibly inaccurate estimate of the wireless channel state are considered. A stationary, on-line, gradient-based scheduling and rate control policy is introduced which identifies at every decision instant the sources that should access the wireless medium along with their respective transmission rates. Furthermore, in the case that more than one optimal rate allocation is possible, the one that requires the minimum sum-power expenditure is selected by the policy. The optimality of the proposed policy among all policies that have access to the same estimate of the current wireless channel state is established through stochastic approximation arguments.

In the above titled paper (ibid., vol. 57, no. 7, pp. 4333-4343, July 2011), the following corrections are necessary.

The problem of joint scheduling and rate control for multicast traffic in wireless networks is considered under the performance objectives of sum throughput maximization and proportional fairness. Our results are also valid for the special cases of unicast and broadcast traffic. First, the problem of maximizing the sum throughput of the network is studied and an optimal scheduling and rate control policy is obtained. Given the combinatorial complexity of providing an optimal policy, a simple, polynomial-time, suboptimal alternative scheme is introduced that restricts the space of scheduling and rate control decisions to operation one at a time or all together. The optimal policy to the problem of maximizing the sum throughput of the network with respect to this restricted action space is found. Next, the objective of proportional fairness is considered. Under this restricted space of actions, the resulting scheduling and rate control policy is explicitly characterized analytically and the effects of the current channel conditions are incorporated into the scheduling decisions. Furthermore, it is shown that the policy under this restricted action space is of threshold type. Finally, our analytical results are verified through a set of numerical experiments.

We consider a set of multicast sources, each multicasting a finite amount of data to its corresponding destinations. The objective is to minimize the time to deliver all traffic, i.e., to obtain schedules of minimum length. We consider time-varying wireless networks with imperfect side information at the sources. We model the minimum-length scheduling problem through partially observable stochastic shortest paths and provide an optimal solution. Due to the high complexity of computing the optimal solution, we finally provide a set of heuristics and illustrate their performance through numerical experiments.

In this paper we study the problem of scheduling through rate and power control for multicast traffic. Our objective is to maximize the total user utility where user utilities are measured in terms of the long term average received rates. Considering the fact that accurate knowledge of the wireless channel conditions may not be always available, we focus on policies that take decisions based only on inaccurate estimates of the wireless channel state. We introduce an on-line, stationary scheduling and rate control policy. We establish its optimality among all policies with the same knowledge regarding the current channel state through stochastic approximation arguments.

We characterize the stability region of wireless, single-hop networks with time-varying imperfect channels. We define a joint scheduling and transmission rate control policy that maximizes the set of stable rates the network can support. Since obtaining the optimal policy is computationally complex, we confine our attention on the specific case of pure time division multiple access (TDMA) based scheduling of the transmitters one at a time, combined with rate control and we identify the exact conditions under which a pure TDMA scheduling and rate control approach maximizes the stability region of the network.