Ghasem Naddafzadeh Shirazi

A Cooperative Retransmission Scheme for IR-UWB networks

We design a cooperative retransmission scheme in the MAC layer which utilizes the UWB unique properties such as fine ranging and immunity to small scale fading in order to exploit the multiuser diversity in UWB networks. We analyze the optimal cooperation strategy to maximize the system throughput in proactive and reactive settings. We also perform simulations to show that the proposed UWB-based coperative retransmission scheme, (UCoRS), achieves a considerable diversity gain in spite of its implementation simplicity. UCoRS also minimizes the number of control packets that is required for cooperation in order to provide energy efficiency in the UWB receivers.

A Cooperative Retransmission Scheme in Wireless Networks with Imperfect Channel State Information

A transmitted packet that fails to reach its intended destination may be correctly received by neighbor nodes due to the broadcast nature of the wireless medium. In a cooperative retransmission scheme, these neighbor nodes, known as relays, can retransmit the failed packet on behalf of the original source node. The challenge is that multiple concurrent transmissions may lead to collision at the destination, and thus the problem is to decide which relay should help in retransmitting the failed packet so that the destination can successfully receive it. This paper proposes a decentralized partially observable Markov decision process (DEC-POMDP) model for selecting the relays to perform the cooperative retransmission. The proposed DEC-POMDP model does not require global channel state information (CSI). In addition, it is robust to noise in CSI measurements. Furthermore, the proposed DEC-POMDP scheme utilizes the gradient descent learning method to eliminate the need for a wireless channel model. We show that the proposed learning method based on the DEC-POMDP model can perform near optimally in the absence of a channel model and despite its implementation simplicity.

Cost-efficient data aggregation point placement for advanced metering infrastructure

This paper investigates the problem of placement of data aggregation points (DAPs) in advanced metering infrastructures (AMIs). The specific constraints are that DAPs are to be located on utility poles and that communication is done over wireless links. While the resulting optimization problem is an integer program, we propose to adapt the K-means algorithm to obtain an efficient and less-complex method to solve the DAP placement problem. Simulations of the developed optimization method illustrate the effects of smart-meter density and communication range on the selection of DAP locations.

Robust Spatial Reuse Scheduling in Underwater Acoustic Communication Networks

Resource assignment in underwater acoustic communication (UWAC) networks has recently drawn much attention in the research community. Although in most applications the number of nodes in the UWAC network is relatively small, the long propagation delay of acoustic signals underwater motivates the application of spatial reuse in channel access protocols for throughput enhancement. In this paper, we address the problem of spatial-reuse scheduling in UWAC networks that support frequent transmission of broadcast packets and require robustness to inaccurate topology information. Taking the possibility of outdated network topology information into account is of great importance for UWAC applications due to time-varying topologies in the underwater environment. Our main contribution is the derivation of a broadcast scheduling algorithm that combines topology-transparent and topology-dependent spatial-reuse scheduling methodologies to achieve high throughput in static and dynamic topology scenarios. Simulation results demonstrate that our protocol provides a favorable tradeoff between network throughput and robustness to outdated topology information due to topology changes, and that it also achieves fairness in terms of per-node throughput.

Lifetime Maximization in UWB Sensor Networks for Event Detection

The operational lifetime of a wireless sensor network (WSN) for event detection is determined by the maximum time that the network is able to meet given detection requirements (DRs), i.e., the probabilities of detection and false alarm demanded by the application. In this paper, we address the problem of maximizing lifetime of such WSNs through optimizing quantization and routing of event measurements. In particular, we consider the task of monitoring multiple events and reporting the observations to a sink, whereby sensor nodes adapt their data generation rate and the data flow distribution in the network for the purpose of lifetime maximization. We make use of ultra-wideband (UWB) signaling at the physical layer, which is well-suited for event-detection WSNs, because of the low-energy consumption for data transmission and relative robustness to multiuser interference. Expressing the DRs as convex constraints in the optimization variables, we present a convex-optimization framework for lifetime maximization of event detection UWB-based WSNs. Furthermore, based on the dual decomposition approach, we propose a decentralized algorithm, which makes it possible to solve the lifetime-maximization problem in a distributed manner and thus shares the computational complexity among network nodes and is robust to artifacts like node failures. Numerical results show that the proposed joint adaptation of quantization and routing leads to significant improvements in network operational lifetime compared to benchmark approaches known from literature.

Optimal Cooperative Relaying Schemes in IR-UWB Networks

Cooperation between wireless nodes to retransmit data for the other users introduces multiuser diversity to a wireless network and increases the system throughput. In this paper, the optimal cooperative relaying strategies in the MAC layer are analyzed while considering the UWB unique properties such as fine ranging and immunity to small scale fading. Specifically, the optimal cooperation strategies in the absence of coordination message passing between relays are determined in order to maximize the system throughput while reducing the control packet overhead. Mobile networks are also considered, in which the relays should exchange their ranging information together in some update intervals. The optimal update interval length is calculated in order to maximize the system throughput. More importantly, we show that if this optimal update interval is used, the optimal cooperation strategies in the mobile case will be similar to those in the static network. Two different relay selection schemes, namely proactive and reactive settings, are considered. Analysis and simulations confirm that the proposed UWB-based Cooperative Relaying Scheme, UCoRS, can achieve a considerable diversity gain in spite of its implementation simplicity. UCoRS also minimizes the number of control packets that are required for the optimal cooperation, which leads to the energy efficiency in the UWB costly data-receiving process.

Second order cone programming for sensor network localization with anchor position uncertainty

We consider the problem of node localization in sensor networks, and we focus on networks in which the ranging measurements are subject to errors and anchor positions are subject to uncertainty. We consider a statistical model for the uncertainty in the anchor positions and formulate the robust localization problem that finds a maximum likelihood estimation of the node positions. To overcome the non-convexity of the resulting optimization problem, we obtain a convex relaxation that is based on the second order cone programming (SOCP). We also propose a possible distributed implementation using the SOCP convex relaxation. We present numerical studies that compare the presented approach to other existing convex relaxations for the robust localization problem in terms of positioning error and computational complexity.

A Low-Overhead Cooperative Retransmission Scheme for IR-UWB Networks

The UWB unique properties such as fine ranging and immunity to small scale fading are utilized in order to exploit the multiuser diversity in UWB networks. The optimal cooperation strategies in the absence of control packet overhead are analyzed in the proactive and reactive settings. It is shown that the proposed method achieves a considerable diversity gain while minimizing the overhead of control packet exchange that is required for coordination among the relays.

Markov Decision Process Frameworks for Cooperative Retransmission in Wireless Networks

The challenging problem of cooperative retransmission in the wireless networks is investigated in this paper. This paper introduces the centralized and distributed Markov decision process (MDP) frameworks in the context of cooperative retransmission. Specifically, a MDP model with the global channel information is first constructed for the cooperation problem in the MAC layer. It is shown that this global MDP is able to perform optimally, where the objective is to minimize the total number of required transmissions for a successful packet delivery to the destination. When the global information is unavailable, we show that the suitable distributed MDP models can replace the global model for a near-optimal performance. Furthermore, the reinforcement learning methods are investigated when the MDP model is unavailable. Interestingly, simulation results confirm that the learning methods also provide an acceptable performance despite their simplicity and low overhead.

Cooperative retransmissions using Markov decision process with reinforcement learning

In cooperative retransmissions, nodes with better channel qualities help other nodes in retransmitting a failed packet to its intended destination. In this paper, we propose a cooperative retransmission scheme where each node makes local decision to cooperate or not to cooperate at what transmission power using a Markov decision process with reinforcement learning. With the reinforcement learning, the proposed scheme avoids solving an Markov decision process with a large number of states. Through simulations, we show that the proposed scheme is robust to collisions, is scalable with regard to the network size, and can provide significant cooperative diversity.