Showing papers by "Hussein Al-Shatri published in 2015"

Computation offloading in wireless multi-hop networks: Energy Minimization via multi-dimensional knapsack problem

Abstract: Computation offloading is an upcoming approach to increase battery life of mobile devices overburdened by resource-consuming applications. In multi-hop networks, computation offloading poses new challenges since intermediate devices are required to relay tasks of others along the path to the server. The decision of a device about whether to offload or not depends thus on the provided energy of relay devices and on the decisions of other offloading devices since relay resources need to be shared. This also implies that for energy minimization, optimal decisions are topology-dependent. This paper introduces a novel theoretical framework for energy minimization of computation offloading in multi-hop wireless networks which formulates the energy minimization problem as a binary linear problem. Proving its equivalence to a multi-dimensional knapsack problem allows us to specify a greedy heuristic, which shows very good performance, with a maximal deviation of less than 5% from the optimal results. From simulations and analytical results for different topologies, we derive under which conditions computation offloading in multi-hop networks is beneficial.

Energy-efficient data dissemination in Ad Hoc networks: Mechanism design with potential game

Abstract: In this paper, a mechanism is designed based on game theory which aims at minimizing the transmit power in a multi-hop wireless broadcast network. There are multiple nodes in a network and among them, there is a source node which has a common message for all other nodes. For the sake of energy efficiency, the source's message should be forwarded to all nodes by a collaboration between different nodes in a multi-hop manner. Minimizing the total transmit power in the network is the goal of this paper. To this end, the nodes in the network are modeled as rational players and a mechanism is designed based on a potential game model. In this game, the action set of each node changes during the game based on the action of other players. Besides, it is proposed to exploit the weakly dominant strategy at the nodes such that the nodes change their actions even if a new action with the same cost exists. Simulation results show that the proposed decentralized mechanism significantly outperforms other conventional decentralized algorithms. Moreover, when the network is not dense, our algorithm can outperform centralized algorithms on average.

Application-aware cross-layer framework: Video content distribution in wireless multihop networks

Abstract: Scalable video coding (SVC) can overcome the user heterogeneity issue, e.g., different screen resolutions or different connectivities, in video-streaming. In wireless multihop networks, the performance of SVC is not adequate, because SVC cannot adapt the lower layers. In order to adapt to changing environmental conditions, e.g., network topology, available resources or channel conditions, a cross-layer framework is required. We propose a new application-aware cross-layer framework which utilizes SVC, network structures and communication types at APP, NET, DLL and PHY layers together. Further, our application-aware cross-layer framework performs transitions at different layers to find the best combination of mechanisms. This is achieved by the following steps. First, we apply a graph-based approach to integrate all mechanisms on the different layers in a single graph. Secondly, video layers are modeled in the graph as virtual sources. Thirdly, we perform an optimal mapping from video layer data rates to physical layer rates. Fourthly, we formulate a multi-source sum rate optimization problem which chooses the best video layer distribution among users and the best combination of mechanisms at all layers. Finally, we demonstrate that our application-aware cross-layer framework outperforms current approaches.

Game-based multi-hop broadcast including power control and MRC in wireless networks

Abstract: A wireless Ad Hoc network consisting of a source and multiple receiving nodes is considered. The source wants to transmit a common message throughout the whole network. The message has to be spread in a multi-hop fashion, as the transmit powers at the source and the nodes are limited. The goal of this paper is to find the multi-hop broadcast tree with a minimum energy consumption in the network. To reach this goal, a new decentralized game theoretic approach is proposed which considers the following two aspects jointly for the first time: Firstly, it optimizes the transmit powers at the source and at the individual intermediate nodes. Secondly, it employs maximum ratio combining at the receiving nodes following the fact that a node can receive several copies of the message from different sources in different time slots. The game is modeled such that the nodes are incentivized to forward the message to their neighbors. In terms of the total transmit energy, the results show that the proposed algorithm outperforms other conventional algorithms.

Uplink-Downlink Duality of Interference Alignment in Cellular Relay Networks

Abstract: This paper focuses on signal space interference alignment for the uplink and downlink transmissions in a cellular relay network with multiple cells where a single base station serves multiple mobile stations in each cell and several amplifyand-forward relays are deployed. We show that the interference alignment problems in the uplink and downlink transmissions are a pair of formally dual problems. Exploiting the reciprocity of the channels, a two-step procedure first nullifying the intercell interferences following the idea of relay-aided interference alignment and then designing a zero-forcing filter for each base station to suppress the intra-cell interferences is proposed to obtain the dual interference alignment solutions. Furthermore, the dual solutions also achieve the same sum rate in both the uplink and the reciprocal downlink transmissions with a sum transmit power constraint even if the power consumed by the relays and the relay retransmitted noises are considered.

Throughput maximization in two-hop energy harvesting communications

Abstract: Two-hop energy harvesting communications are considered. The scenario consists of a source node which wants to send data to a destination node through a half-duplex amplify-and-forward relay station. The source node and the relay station harvest energy from the environment several times and use it to transmit the data. Our goal is to find the optimal power allocation that maximizes the throughput at the destination node. We show that the use of a half-duplex amplify-and-forward relay station leads to a non-convex optimization problem. Therefore, to find the optimal power allocation we propose to reformulate the problem as the difference between two concave functions (D.C. programming). Moreover, a branch-and-bound algorithm is tailored to fit the energy harvesting constraints. We show that the feasible region has to be adapted to facilitate the branching process. Additionally, we reduce the complexity in the calculation of the bounds by relaxing the problem into a convex problem with a linear objective function. Numerical results compare the performance in different energy harvesting scenarios.

Towards a framework for cross layer incentive mechanisms for multihop video dissemination

Abstract: For transmitting data in scenarios showing a high user density, infrastructure based and multihop Ad hoc communication can be combined to benefit from the reliability of a stable backbone network and the increased coverage of multihop communication. Such scenarios have been investigated from a cross layer perspective in the recent years mainly focusing on pure performance optimization. However, the question of providing incentives to nodes to forward data has largely been ignored in the cross layer domain, even though providing incentives is vital for the network: each node represents a user comparing his or her satisfaction and the cost to decide on his or her participation. A likely reason for the gap in cross layer incentive research is the necessity to model users as well as the network in order to express a user's utility, which requires knowledge in both fields. In order to foster future research in the area of cross layer incentive schemes, this work proposes a general cross layer simulation model combining user and network models. Moreover, an instantiation of the simulation model for the use case of live video broadcasting is presented.

On the degrees of freedom of the three-user MIMO interference channel with delayed CSIT

Abstract: The three-user multiple-input multiple-output interference channel under i.i.d. fading is studied, where the transmitters have the delayed channel state information. The case where all transmitters and all receivers are equipped with M and N antennas, respectively, is considered. For this case, a new transmission scheme is proposed that achieves a number of degrees of freedom higher than previously reported for the range of 3/4 < M/N < 1, where the parameters of the scheme are determined as functions of the ratio M/N. The degrees of freedom gains compared to the previous approaches are due to the more effective use of transmit and receive antennas.

Maximizing the Sum Rate in Cellular Networks Using Multi-Convex Optimization

Abstract: In this paper, we propose a novel algorithm to maximize the sum rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise considering the signal-to-interference-plus-noise-ratio. It is known that the problem of adapting the transmit and receive filters of the users to maximize the sum rate with a sum transmit power constraint is non-convex. Our novel approach is to formulate the sum rate maximization problem as an equivalent multi-convex optimization problem by adding two sets of auxiliary variables. An iterative algorithm which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multi-convex optimization problem. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and a sum power constraint at the relays are assumed. Finally, we show that the proposed multi-convex formulation of the sum rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multi-affine functions of the system variables.