72 research outputs found
An Economic Aspect of Device-to-Device Assisted Offloading in Cellular Networks
Traffic offloading via device-to-device (D2D) communications
has been proposed to alleviate the traffic burden
on base stations (BSs) and to improve the spectral and energy
efficiency of cellular networks. The success of D2D communications
relies on the willingness of users to share contents. In
this paper, we study the economic aspect of traffic offloading via
content sharing among multiple devices and propose an incentive
framework for D2D assisted offloading. In the proposed incentive
framework, the operator improves its overall profit, defined as
the network economic efficiency (ECE), by encouraging users
to act as D2D transmitters (D2D-Txs) which broadcast their
popular contents to nearby users. We analytically characterize
D2D assisted offloading in cellular networks for two operating
modes: 1) underlay mode and 2) overlay mode. We model the
optimization of network ECE as a two-stage Stackelberg game,
considering the densities of cellular users and D2D-Tx’s, the
operator’s incentives and the popularity of contents. The closedform
expressions of network ECE for both underlay and overlay
modes of D2D communications are obtained. Numerical results
show that the achievable network ECE of the proposed incentive
D2D assisted offloading network can be significantly improved
with respect to the conventional cellular networks where the D2D
communications are disabled
An Economic Aspect of Device-to-Device Assisted Offloading in Cellular Networks
Traffic offloading via device-to-device (D2D) communications
has been proposed to alleviate the traffic burden
on base stations (BSs) and to improve the spectral and energy
efficiency of cellular networks. The success of D2D communications
relies on the willingness of users to share contents. In
this paper, we study the economic aspect of traffic offloading via
content sharing among multiple devices and propose an incentive
framework for D2D assisted offloading. In the proposed incentive
framework, the operator improves its overall profit, defined as
the network economic efficiency (ECE), by encouraging users
to act as D2D transmitters (D2D-Txs) which broadcast their
popular contents to nearby users. We analytically characterize
D2D assisted offloading in cellular networks for two operating
modes: 1) underlay mode and 2) overlay mode. We model the
optimization of network ECE as a two-stage Stackelberg game,
considering the densities of cellular users and D2D-Tx’s, the
operator’s incentives and the popularity of contents. The closedform
expressions of network ECE for both underlay and overlay
modes of D2D communications are obtained. Numerical results
show that the achievable network ECE of the proposed incentive
D2D assisted offloading network can be significantly improved
with respect to the conventional cellular networks where the D2D
communications are disabled
Survey on the state-of-the-art in device-to-device communication: A resource allocation perspective
Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spectral efficiency of the system. Nevertheless, frequency reuse introduces significantly high interference levels thus necessitating efficient resource allocation algorithms that can enable simultaneous communication sessions through effective channel and/or power allocation. This survey paper presents a comprehensive investigation of the state-of-the-art resource allocation algorithms in D2D communication underlaying cellular networks. The surveyed algorithms are evaluated based on heterogeneous parameters which constitute the elementary features of a resource allocation algorithm in D2D paradigm. Additionally, in order to familiarize the readers with the basic design of the surveyed resource allocation algorithms, brief description of the mode of operation of each algorithm is presented. The surveyed algorithms are divided into four categories based on their technical doctrine i.e., conventional optimization based, Non-Orthogonal-MultipleAccess (NOMA) based, game theory based and machine learning based techniques. Towards the end, several open challenges are remarked as the future research directions in resource allocation for D2D communication
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
Resource Allocation and Mode Selection in 5G Networks Based on Energy Efficient Game Theory Approach
With the advent of next-generation cellular networks, energy efficiency is becoming increasingly important. To tackle this issue, this paper investigates energy efficiency in D2D-enabled heterogeneous cellular networks. Boosting the longterm energy efficiency of wireless 5G communication networks is being explored through mode selection and resource allocation. The study proposed a three-stage process for energy-efficient mode selection and resource allocation. The process starts with cellular users who switch to D2D emitting a beacon and cellular users within close proximity reacting to it. A proposed auction mechanism will be enacted inside the group in the second state ( in this paper, the group size will be four). Next, each cellular user was classified according to SINR values, distance, and battery life, so that they could dynamically transition between standard cellular mode and D2D mode. For stage three, direct-hop hybrid D2D communication, we developed a TAMM double auction game model that efficiently splits resources. To identify the true bidders in our game model, we compute the median and mode values of the ASK and BID values received by both seller and buyer cellular users. A simulation study shows that the proposed method is energy-efficient in a heterogeneous network enabled by D2D
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Energy Efficient Two-hop D2D Communications Underlay 5G Networks: A Stackelberg Game Approach
Although coverage and capacity are the key elements of the 5G user experience, a dominant part of the population living in rural areas still experience inferior connectivity. Several solutions have been proposed to address this issue. They include deploying small cells, increasing the number of sectors per eNodeB, and reusing signal repetition. However, most of them require complex deployment and expensive fees. Accordingly, many efforts have been deployed on coverage extension software. Even so, many critical issues related to public safety, relay capacity, and devices power constraints are still challenging. As a contribution, we propose in this paper a spectral and energy-efficient two-hop device to device (D2D) relay selection algorithm. Our main goal is to extend the connectivity to the out-of-coverage (OOC) devices. Contrarily to previous solutions in which the relay is selected centrally or individually, we propose a distributed two-stage algorithm based on the Stackelberg game to involve all the competing devices. In the first stage, the OOC devices (OCDUs) are matched with the relays maximizing their spectral efficiency, and the required bandwidth for each one is determined. Then, a power control stage is investigated to calculate the optimal transmission power. The numerical and simulation analysis shows that the proposed schema outperforms the former solutions in total system capacity, spectral efficiency (SE), and energy efficiency (EE) while reducing the complexity
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