Roya Arab Loodaricheh

Robust Resource Optimization for Cooperative Cognitive Radio Networks with Imperfect CSI

We develop robust resource-allocation schemes for a cognitive radio network (CRN), where the secondary users (SUs) try to communicate with each other from different small cell primary user (PU) networks. User cooperation technique is considered for communication among the SUs since PUs are in close proximity and there are tight interference constraints on the PU bands. Power allocation and relay selection schemes are optimized with the provision of quality of service to each SU considering different channel uncertainty models. We incorporate the channel outage events that have resulted from the imperfect channel state information under slow-fading channels in our resource optimization algorithms. We maximize the system goodput of the CRN while satisfying the interference constraints of the PU bands both probabilistically and for the worst case scenario. The original probabilistic optimization problem is approximated and transformed into a convex deterministic form, and a closed-form analytical solution for power allocation is derived. The closed-form power allocation solution helps us to develop an efficient relay selection scheme based on Hungarian algorithm. Simulation results reveal the effectiveness of our proposed schemes and the implications of ignoring the imperfectness among different channels when developing resource-allocation algorithms for CRNs.

On Multiuser Resource Allocation in Relay-Based Wireless-Powered Uplink Cellular Networks

We propose relay-based wireless-powered uplink cellular networks in which users first harvest energy from RF transmissions of base station/relay nodes and then use that energy for uplink transmission. Given the limited total transmission time and available energy at the relay node, we propose different resource allocation frameworks for the proposed relay-based networks considering two different relay-based harvest-then-transmit scenarios. We first propose iterative algorithm to determine time and relay node power allocation (for downlink wireless charging and uplink data transmission/relaying) for both scenarios. We then perform joint optimal time and power allocation for one scenario. Resource allocation results show that most of the available resources (transmission time and relay node energy) are allocated for wireless energy harvesting which is similar to that observed for downlink simultaneous wireless information and power transfer (SWIPT) in the existing literature. Simulation results on comparison of different relay-based scenarios reveal interesting insights and demonstrate remarkable improvement of different performance metrics of wireless-powered cellular networks in the presence of relay node.

Joint resource optimization for OFDMA cellular networks with user cooperation and QoS provisioning

In this paper, a joint resource optimization scheme is designed for orthogonal frequency division multiple access (OFDMA) cellular wireless networks with multi-user cooperation. Joint relay selection, subcarrier allocation and pairing and power allocation algorithms are developed with the objective of maximizing the total capacity of the system considering the quality of service (QoS) requirements of the users. The optimization problem is a mixed integer nonlinear program (MINLP), which is often very difficult to solve in its original form. We provide a novel optimization framework to solve such non-linear optimization problems. The joint relay selection and subcarrier allocation problem is modified to a linear assignment problem and an efficient algorithm is developed to obtain the optimal assignment solution based on the Hungarian method. We propose computationally efficient solution to the joint resource optimization problem via dual decomposition method. Numerical results demonstrate the effectiveness of our proposed scheme.

QoS Provisioning Based Resource Allocation for Energy Harvesting Systems

In this paper, we propose quality-of-service (QoS) based resource allocation (RA) schemes for energy harvesting (EH) systems. We consider a system model with a single source and multiple destination nodes or users, in which the source node harvests energy from the environment. Our goal is to develop efficient RA policies for EH systems when the harvested energy at the source node is uncertain and insufficient to satisfy the QoS of the users completely. We develop two different schemes and RA policies to address this problem. In the first scheme, we minimize the total dissatisfaction of the users over a finite period of time through goal programming approach. In the second scheme, we maximize the number of admitted users and provide guaranteed QoS to them. For both schemes, we first develop offline algorithms assuming the availability of perfect and complete information about the harvested energy and channel state information (CSI). Next, we devise online algorithms based on dynamic programming (DP) considering the availability of causal information about the harvested energy and CSI. Numerical results demonstrate the effectiveness of our proposed algorithms and the importance of QoS provisioning based RA schemes in EH systems.

Relay-based harvest-then-transmit protocol for uplink cellular networks

We propose a relay-based harvest-then-transmit (HTT) protocol for time division multiple access uplink cellular networks. In the HTT protocol, the base stations transmit downlink wireless energy harvesting (DWEH) signals to users at the beginning of uplink time frame while the remaining time is used for uplink wireless information transfer (UWIT). Relay nodes are designed to independently broadcast energy harvesting signals for cell-edge users in the downlink while they relay information signals from cell-edge users to the base stations in the uplink. We jointly optimize DWEH and UWIT time of all users to maximize the total throughput of the system. Numerical results demonstrate that incorporation of relay nodes enhances the performance in terms of cell-edge user throughput, throughput fairness, and total network throughput.

Resource allocation with QoS provisioning for energy harvesting systems: A goal programming approach

In this paper, we address the problem of resource allocation with quality-of-service (QoS) provisioning for an energy harvesting system with a single source node and multiple users (destination nodes). We consider that the source node harvests energy from the environment, which is insufficient to satisfy the QoS of the users due to its random nature. We develop resource allocation schemes to minimize the dissatisfaction of the users through goal programming approach. First, we develop an offline scheme assuming that complete information about the harvested energy and channel state information (CSI) is available. The optimization problem is formulated as convex and efficient solution is provided based on dual decomposition algorithm. Next, we devise an online scheme considering the availability of causal and incomplete information about the harvested energy and CSI. We propose an algorithm based on dynamic programming to obtain the online optimal solution. Numerical results demonstrate the effectiveness of our proposed schemes in terms of fairness and the importance of QoS provisioning in energy harvesting systems.

Distributed subcarrier pairing and relay selection for OFDM based cooperative relay networks

In this paper, we propose distributed subcarrier pairing and relay selection for OFDM based cooperative systems. Our objective is to maximize the throughput of the network using minimal signaling overhead when uniform power allocation is performed at the subcarriers. Since the optimal centralized solution for the formulated problem requires high signaling overhead and processing complexity, we propose two suboptimal distributed algorithms scalable and suitable for practical implementation. The first proposed algorithm is based on Hungarian method and is efficient in terms of signaling overhead reduction. The performance of this algorithm is extremely close to the optimal solution for large number of subcarriers. The second proposed distributed algorithm has lower complexity and it significantly reduces the signaling overhead at the expense of a small degradation in performance. Numerical results reveal the effectiveness of the proposed algorithms and demonstrate the superiority over other existing algorithms in the literature.

Resource Allocation for Cooperative D2D Communication Networks

Device-to-device (D2D) communications technology is currently being investigated as a potential enabler for the fifth generation (5G) communication networks. Significant performance gains are achievable in a cooperative D2D framework, wherein the user equipments (UEs) cooperate with each other to enable a variety of low-latency proximity-based services or to establish indirect communication links with the Base Station (BS) whenever direct service coverage is not possible. This chapter is focused on the throughput gains achievable in the latter scenario, i.e., when few UEs perform relaying operations to provide indirect service coverage to other UEs. In this direction, resource allocation problems are formulated for a variety of system models operating under the orthogonal frequency division multiple access (OFDMA) cellular or cognitive radio (CR) access architectures. The performance of mobile D2D relaying under different scenarios is evaluated. The system models are designed to study the benefits of incorporating additional capabilities at the devices, such as packet storage (using buffers), energy-harvesting, and cognitive spectrum access within the cooperative D2D framework. Depending on the system model, efficient algorithms are proposed to obtain optimal power allocation, subcarrier assignment, subcarrier pairing, and relay-UE selection policies which maximize the system throughput under a variety of system-dependant constraints. Simulation results demonstrate the effectiveness of our proposed algorithms and the performance improvement of mobile D2D-relaying networks over conventional networks.