Kazem Sohraby

Resource allocation for intercell device-to-device communication underlaying cellular network: A game-theoretic approach

Device-to-Device (D2D) communication is envisioned as a promising technology to significantly improve the performance of current cellular infrastructures. Allocating resources to the D2D link, however, raises an enormous challenge to the co-existing D2D and cellular communications due to mutual interference. While there have been many resource allocation solutions proposed for D2D underlaying cellular network, they have primarily focused on the intracell scenario while leaving the intercell settings untouched. In this paper, we investigate the resource allocation problem for intercell D2D communications underlaying cellular networks, where D2D link is located in the overlapping area of two neighboring cells. We present three inter-cell D2D scenarios regarding the resource allocation problem. To address this problem, we develop a repeated game model under these scenarios. Distinct from existing works, we characterize the communication infrastructure, namely Base Stations (BSs), as players competing resource allocation quota for D2D demand, and define the utility of each player as the payoff from both cellular and D2D communications using radio resources. We also propose a resource allocation algorithm and protocol based on the equilibrium derivations. Numerical results indicate that the developed model not only significantly enhances the system performance including sum rate and sum rate gain, but also sheds lights on resource configurations for intercell D2D scenarios.

Multimedia Sensing as a Service (MSaaS): Exploring Resource Saving Potentials of at Cloud-Edge IoT and Fogs

With the popularity of multimedia sensing at cloud edges and the reducing cost of the Internet of Things (IoT) fog devices and systems, new challenges have been posed to efficiently deal with the big data multimedia traffic generated from IoT sensing units. Specifically, in this paper we introduce the concept of multimedia sensing as a service (MSaaS), and propose a generalized premium prioritization-based quality of experience paradigm for wireless big-volumes-of-data (BVDs) multimedia communications, with significant energy saving potentials for future multimedia IoT devices and systems. The key contribution of this new framework is its data diversity flexibility at the application layer, which could be flexibly adopted by future multimedia communication systems. Data dependencies in spatial, frequency and temporal domains are analyzed, and interaction with uplink resource allocation optimization are investigated with regards to wireless communication energy cost estimation. Extensive simulation results demonstrate that the proposed prioritization-based communication paradigm has significant energy saving potentials for BVD MSaaS wireless multimedia communications at cloud edges and fogs.

IoT security (IoTSec) considerations, requirements, and architectures

This article looks at some of the challenges related to the deployment of the Internet Of Things (IoT), specifically to ascertain that security becomes an integral part of the technology rather than a bolted-on wrapper of limited efficacy. IoT security (IoTSec) is needed at all ‘layers’ of the IoT environment and may be specific to the IoT ‘layer’ in question.

An optimal MIMO mode selection method for D2D transmission in cellular networks

Device-to-Device (D2D) communication is one of the new features introduced for Long Term Evolution-Advanced (LTE-A) and beyond networks. In this paper we address the problem of communication mode selection for a pair of User Equipments (UEs). In particular we assume that the paired UEs can choose from the reuse, dedicated, and cellular modes. While this problem was treated in the literature for Single-Input-Single-Output (SISO) case, we derive models for networks where UEs and evolved-Node-Bs (eNBs) exploit Multiple-Input-Multiple-Output (MIMO) techniques with four antennas at each side. This approach requires design of the pre-coding matrices at each node which poses a challenge in the reuse mode due to the non-convexity problem. To solve this issue we propose a distributed iterative algorithm. The numerical study compares the performance of the MIMO based approach with that of the SISO case, and the results show that the presented MIMO based mode selection method provides significantly higher network throughput than that of the SISO based mode selection method for the same D2D transmission range.

Game-Theoretic Resource Allocation for Intercell Device-to-Device Communication Underlaying Cellular Network

Device-to-Device (D2D) communication is an emerging technology that has been introduced as a beneficial complement of cellular infrastructure. Allocating resources to the D2D link, however, raises an enormous challenge to the co-existing D2D and cellular communications due to the mutual interference. While there have been many resource allocation solutions proposed for D2D under laying cellular network, they have primarily focused on the intracell scenario while leaving the intercell settings untouched. In this paper, we address the resource allocation problem for intercell D2D communication under laying cellular network. Unlike most of prior works allocating resource in a single cell, we consider the scenario that D2D link locates in the common area of two neigh boring cells. We formulate the problem by developing a Cournot competition game, in which the base stations (BSs) are modeled as players to compete for resource supply quota from D2D demand under three dedicated cases. Our analysis and numerical results show that the the derived resource allocation solution is an equilibrium, thus offering a global insight into resource configurations of two cells.

QoS optimized and energy efficient power control for deep space multimedia communications in InterPlaNetary networks

In this paper, we propose a QoS optimized power control approach to achieve an optimum multimedia communication quality over the InterPlaNetary (IPN) Internet with a strict energy consumption budget. The transmission power to send each frame is optimized by jointly considering the unequal distortion reduction gain of the multimedia data, energy consumption budget, and overall multimedia communication quality. Simulation results show that the proposed Unequal Error Protection (UEP) adaptive power control approach improves multimedia data transmission quality and achieves the energy utilization efficiency in energy-constrained IPNs.

A Weight-Optimized Source Rate Optimization approach in Energy Harvesting Wireless Sensor Networks

Using harvestable energy in Wireless Sensor Networks (WSNs) has gained considerable popularity recently. However, how to utilize the unstable power supply to achieve quality performance is still a challenge. In this paper, we propose a Weight-Optimized Source Rate Optimization (WOSRO) approach which allows the WSN system to adaptively control source coding rates by choosing the most valuable data packets to transmit. In this approach, the packet selection strategy is optimized by considering multimedia distortion reduction, energy cost, energy neutrality constraint and power saving efficiency. Simulation results show that the proposed data packet selecting strategy significantly improves data transmission quality by exploring harvesting-storage energy neutrality and multimedia data packet importance.

Mobility impact on mode selection map in D2D networks — An analytical approach

Device-to-Device (D2D) transmission is a promising technology which enables the User Equipments (UE) in 5G cellular networks to directly communicate without going through the evolved Node-B (eNB). In such networks UEs should select a Transmission Mode (TM) amongst reuse, dedicated, and cellular modes by maximizing the overall transmission throughput or referring to a mode selection map. The selection map identifies the mode which results in the highest data rate given the current state of the network. This paper presents a new analytical framework for the derivation of the selection map of D2D enabled cellular networks. While this problem was treated in the literature through numerical simulations, our approach is analytical and consequently fast and precise.

A study of application layer paradigm for lower layer energy saving potentials in cloud-edge social user wireless image sharing

Energy saving becomes critical in modern cloud wireless multimedia and mobile communication systems. In this paper we propose to study a new paradigm named application layer Position-Value diversity for wireless image sharing for cloud-edge communications, which has significant energy saving potentials for modern wireless networking systems. In this new paradigm, saving energy is achieved by looking into application layer imaging traffic, in stead of MAC-PHY protocols at lower layers, and partitioning it into important positions and unimportant values. This paradigm could be integrated to existing wavelet-based tree compression, and truncation of image bit streams could be performed with regards to wireless communication energy budget estimation. Simulation results demonstrated that there are significant potentials of communication energy efficiency gain and Quality of Experience (QoE) enhancement in wireless image communication systems.

AoA Based Sensing and Performance Analysis in Cognitive Radio Networks

In the traditional research on spectrum sensing in cognitive radio networks, a channel is determined occupied by a primary user (PU) once a signal is detected, but this is not always true. There is a fair likelihood that the channel is being used by a secondary user (SU). To accurately reflect the channel status, it is significant to distinguish whether a signal from a PU or an SU on a busy channel. In this paper, we propose an Angle of Arrival (AoA) based sensing approach using the smart antenna technology. Specifically, an SU is equipped with a smart antenna and hence is capable of distinguishing the arrival angles from all incoming signals. Therefore, if the angle/direction information of the target PU is provided in advance, an SU is able to determine that a received signal is from the PU or other users by analyzing the incoming angles. We select the CAPON AoA algorithm as an example to demonstrate the effectiveness. Further, we comprehensively investigate the sensing performance including false alarm probability and miss detection probability, which has received limited attention. Extensive simulations are conducted and results demonstrate the effectiveness of the AoA based spectrum sensing approach. The limitation of this approach is pointed out as well.