arXiv subjects

Ekram Hossain

Publications and source records attributed to Ekram Hossain.

At least 145 records · Page 8Linked to original sources

arXiv2017

Downlink Power Allocation for CoMP-NOMA in Multi-Cell Networks

This work considers the problem of dynamic power allocation in the downlink of multi-cell networks, where each cell utilizes non-orthogonal multiple access (NOMA)-based resource allocation. Also, coordinated multi-point (CoMP) transmission is utilized among multiple cells to serve users experiencing severe inter-cell interference (ICI). More specifically, we consider a two-tier heterogeneous network (HetNet) consisting of a high-power macro cell underlaid with multiple low-power small cells each of which uses the same resource block. Under this {\em CoMP-NOMA framework}, CoMP transmission is applied to a user experiencing high channel gain with multiple base stations (BSs)/cells, while NOMA is utilized to schedule CoMP and non-CoMP users over the same transmission resources, i.e., time, spectrum and space. Different CoMP-NOMA models are discussed, but focus is primarily on the joint transmission CoMP-NOMA (JT-CoMP-NOMA) model. For the JT-CoMP-NOMA model, an optimal joint power allocation problem is formulated and the solution is derived for each CoMP-set consisting of multiple cooperating BSs (i.e., CoMP BSs). To overcome the substantial computational complexity of the joint power optimization approach, we propose a distributed power optimization problem at each cooperating BS whose optimal solution is independent of the solution of other coordinating BSs. The validity of the distributed solution for the joint power optimization problem is provided and numerical performance evaluation is carried out for the proposed CoMP-NOMA models including JT-CoMP-NOMA and coordinated scheduling CoMP-NOMA (CS-CoMP-NOMA). The obtained results reveal significant gains in spectral and energy efficiency in comparison with conventional CoMP-orthogonal multiple access (CoMP-OMA) systems.

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arXiv2017

Multi-tier Drone Architecture for 5G/B5G Cellular Networks: Challenges, Trends, and Prospects

Drones (or unmanned aerial vehicles [UAVs]) are expected to be an important component of fifth generation (5G)/beyond 5G (B5G) cellular architectures that can potentially facilitate wireless broadcast or point-to-multipoint transmissions. The distinct features of various drones such as the maximum operational altitude, communication, coverage, computation, and endurance impel the use of a multi-tier architecture for future drone-cell networks. In this context, this article focuses on investigating the feasibility of multi-tier drone network architecture over traditional single-tier drone networks and identifying the scenarios in which drone networks can potentially complement the traditional RF-based terrestrial networks. We first identify the challenges associated with multi-tier drone networks as well as drone-assisted cellular networks. We then review the existing state-of-the-art innovations in drone networks and drone-assisted cellular networks. We then investigate the performance of a multi-tier drone network in terms of spectral efficiency of downlink transmission while illustrating the optimal intensity and altitude of drones in different tiers numerically. Our results demonstrate the specific network load conditions (i.e., ratio of user intensity and base station intensity) where deployment of drones can be beneficial (in terms of spectral efficiency of downlink transmission) for conventional terrestrial cellular networks.

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arXiv2017

Mobile Edge Computation Offloading Using Game Theory and Reinforcement Learning

Due to the ever-increasing popularity of resource-hungry and delay-constrained mobile applications, the computation and storage capabilities of remote cloud has partially migrated towards the mobile edge, giving rise to the concept known as Mobile Edge Computing (MEC). While MEC servers enjoy the close proximity to the end-users to provide services at reduced latency and lower energy costs, they suffer from limitations in computational and radio resources, which calls for fair efficient resource management in the MEC servers. The problem is however challenging due to the ultra-high density, distributed nature, and intrinsic randomness of next generation wireless networks. In this article, we focus on the application of game theory and reinforcement learning for efficient distributed resource management in MEC, in particular, for computation offloading. We briefly review the cutting-edge research and discuss future challenges. Furthermore, we develop a game-theoretical model for energy-efficient distributed edge server activation and study several learning techniques. Numerical results are provided to illustrate the performance of these distributed learning techniques. Also, open research issues in the context of resource management in MEC servers are discussed.

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arXiv2017

Computation Offloading and Activation of Mobile Edge Computing Servers: A Minority Game

With the ever-increasing popularity of resource-intensive mobile applications, Mobile Edge Computing (MEC), e.g., offloading computationally expensive tasks to the cellular edge, has become a prominent technology for the next generation wireless networks. Despite its great performance in terms of delay and energy, MEC suffers from restricted power allowance and computational capability of the edge nodes. Therefore, it is imperative to develop distributed mechanisms for computation offloading, so that not only the computational servers are utilized at their best capacity, but also the users' latency constraints are fulfilled. In this paper, by using the theory of Minority Games, we develop a novel distributed server activation mechanism for computational offloading. Our scheme guarantees energy-efficient activation of servers as well as satisfaction of users' quality-of-experience (QoE) requirements in terms of latency.

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arXiv2017

Coverage and Rate Analysis for Co-Existing RF/VLC Downlink Cellular Networks

This paper provides a stochastic geometry framework to perform the coverage and rate analysis of a typical user in co-existing VLC and RF networks covering a large indoor area. The developed framework can be customized to capture the performance of a typical user in various network configurations such as (i) RF-only, in which only small base-stations (SBSs) are available to provide the coverage to a user, (ii) VLC-only, in which only optical BSs (OBSs) are available to provide the coverage to a user, (iii) opportunistic RF/VLC, where a user selects the network with maximum received signal power, and (iv) hybrid RF/VLC, where a user can simultaneously utilize the available resources from both RF and VLC networks. The developed model for VLC network precisely captures the impact of the field-of-view (FOV) of the photo-detector (PD) receiver on the number of interferers, distribution of the aggregate interference, association probability, and the coverage of a typical user. Closed-form approximations are presented for special cases of practical interest and for asymptotic scenarios such as when the intensity of SBSs becomes very low. The derived expressions enable us to obtain closed-form solutions for various network design parameters (such as intensity of OBSs and SBSs, transmit power, and/or FOV) such that the number of active users can be distributed optimally among RF and VLC networks. Also, we optimize the network parameters in order to prioritize the association of users to VLC network. Finally, simulations are carried out to verify the derived analytical solutions. Important trade-offs between height and intensity of OBSs are highlighted to optimize the performance of a user in VLC networks.

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arXiv2017

Infrastructure Sharing for Mobile Network Operators: Analysis of Trade-offs and Market

The conflicting problems of growing mobile service demand and underutilization of dedicated spectrum has given rise to a paradigm where mobile network operators (MNOs) share their infrastructure among themselves in order to lower their operational costs, while at the same time increase the usage of their existing network resources. We model and analyze such an infrastructure sharing system considering a single buyer MNO and multiple seller MNOs. Assuming that the locations of the BSs can be modeled as a homogeneous Poisson point process, we find the downlink signal-to-interference-plus-noise ratio (SINR) coverage probability for a user served by the buyer MNO in an infrastructure sharing environment. We analyze the trade-off between increasing the transmit power of a BS and the intensity of BSs owned by the buyer MNO required to achieve a given quality-of-service (QoS) in terms of the SINR coverage probability. Also, for a seller MNO, we analyze the power consumption of the network per unit area (i.e., areal power consumption) which is shown to be a piecewise continuous function of BS intensity, composed of a linear and a convex function. Accordingly, the BS intensity of the seller MNO can be optimized to minimize the areal power consumption while achieving a minimum QoS for the buyer MNO. We then use these results to formulate a single-buyer multiple-seller BS infrastructure market. The buyer MNO is concerned with finding which seller MNO to purchase from and what fraction of BSs to purchase. On the sellers' side, the problem of pricing and determining the fraction of infrastructure to be sold is formulated as a Cournot oligopoly market. We prove that the iterative update of each seller's best response always converges to the Nash Equilibrium.

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arXiv2017

Low-Dimensionality of Noise-Free RSS and its Application in Distributed Massive MIMO

We examine the dimensionality of noise-free uplink received signal strength (RSS) data in a distributed multiuser massive multiple-input multiple-output system. Specifically, we apply principal component analysis to the noise-free uplink RSS and observe that it has a low-dimensional principal subspace. We make use of this unique property to propose RecGP - a reconstruction-based Gaussian process regression (GP) method which predicts user locations from uplink RSS data. Considering noise-free RSS for training and noisy test RSS for location prediction, RecGP reconstructs the noisy test RSS from a low- dimensional principal subspace of the noise-free training RSS. The reconstructed RSS is input to a trained GP model for location prediction. Noise reduction facilitated by the reconstruction step allows RecGP to achieve lower prediction error than standard GP methods which directly use the test RSS for location prediction.

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arXiv2017

On User Association in Multi-Tier Full-Duplex Cellular Networks

We address the user association problem in multi-tier in-band full-duplex (FD) networks. Specifically, we consider the case of decoupled user association (DUA) in which users (UEs) are not necessarily served by the same base station (BS) for uplink (UL) and downlink (DL) transmissions. Instead, UEs can simultaneously associate to different BSs based on two independent weighted path-loss user association criteria for UL and DL. We use stochastic geometry to develop a comprehensive modeling framework for the proposed system model where BSs and UEs are spatially distributed according to independent point processes. We derive closed-form expressions for the mean rate utility in FD, half-duplex (HD) DL, and HD UL networks as well as the mean rate utility of legacy nodes with only HD capabilities in a multi-tier FD network. We formulate and solve an optimization problem that aims at maximizing the mean rate utility of the FD network by optimizing the DL and UL user association criteria. We investigate the effects of different network parameters including the spatial density of BSs and power control parameter. We also investigate the effect of imperfect self-interference cancellation (SIC) and show that it is more severe at UL, where there exist minimum required SIC capabilities for BSs and UEs for which FD networks are preferable to HD networks; otherwise, HD networks are preferable. In addition, we discuss several special cases and provide guidelines on the possible extensions of the proposed framework. We conclude that DUA outperforms coupled user association (CUA) in which UEs associate to the same BS for both UL and DL transmissions.

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arXiv2017

SINR Outage Evaluation in Cellular Networks: Saddle Point Approximation (SPA) Using Normal Inverse Gaussian (NIG) Distribution

Signal-to-noise-plus-interference ratio (SINR) outage probability is among one of the key performance metrics of a wireless cellular network. In this paper, we propose a semi-analytical method based on saddle point approximation (SPA) technique to calculate the SINR outage of a wireless system whose SINR can be modeled in the form $\frac{\sum_{i=1}^M X_i}{\sum_{i=1}^N Y_i +1}$ where $X_i$ denotes the useful signal power, $Y_i$ denotes the power of the interference signal, and $\sum_{i=1}^M X_i$, $\sum_{i=1}^N Y_i$ are independent random variables. Both $M$ and $N$ can also be random variables. The proposed approach is based on the saddle point approximation to cumulative distribution function (CDF) as given by \tit{Wood-Booth-Butler formula}. The approach is applicable whenever the cumulant generating function (CGF) of the received signal and interference exists, and it allows us to tackle distributions with large skewness and kurtosis with higher accuracy. In this regard, we exploit a four parameter \tit{normal-inverse Gaussian} (NIG) distribution as a base distribution. Given that the skewness and kurtosis satisfy a specific condition, NIG-based SPA works reliably. When this condition is violated, we recommend SPA based on normal or symmetric NIG distribution, both special cases of NIG distribution, at the expense of reduced accuracy. For the purpose of demonstration, we apply SPA for the SINR outage evaluation of a typical user experiencing a downlink coordinated multi-point transmission (CoMP) from the base stations (BSs) that are modeled by homogeneous Poisson point process. We characterize the outage of the typical user in scenarios such as (a)~when the number and locations of interferers are random, and (b)~when the fading channels and number of interferers are random. Numerical results are presented to illustrate the accuracy of the proposed set of approximations.

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arXiv2017

Coordinated Multi-Point (CoMP) Transmission in Downlink Multi-cell NOMA Systems: Models and Spectral Efficiency Performance

We outline a general framework to use coordinated multi-point (CoMP) transmission technology in downlink multi-cell non-orthogonal multiple access (NOMA) systems considering distributed power allocation at each cell. In this framework, CoMP transmission is used for users experiencing strong receive-signals from multiple cells while each cell adopts NOMA for resource allocation to its active users. After a brief review of the working principles of different CoMP schemes, we identify their applicability and necessary conditions for their use in downlink multi-cell NOMA system. After that, we discuss different network scenarios with different spatial distributions of users and study the applicability of CoMP schemes in these network scenarios. To the end, a numerical performance evaluation is carried out for the proposed CoMP-NOMA systems and the results are compared with those for conventional orthogonal multiple access (OMA)-based CoMP systems. The numerical results quantify the spectral efficiency gain of the proposed CoMP-NOMA models over CoMP-OMA. Finally, we conclude this article by identifying the potential major challenges in implementing CoMP-NOMA in future cellular systems.

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arXiv2017

Analysis of Massive MIMO-Enabled Downlink Wireless Backhauling for Full-Duplex Small Cells

Using tools from stochastic geometry, we develop a framework to model the downlink rate coverage probability of a user in a given small cell network (SCN) with massive MIMO-enabled wireless backhauls. The considered SCN is composed of a mixture of small cells that are configured in either in-band or out-of-band backhaul modes with a certain probability. The performance of the user in the considered hierarchical network is limited by several sources of interference such as the backhaul interference, small cell base station (SBS)-to-SBS interference and the SI. Moreover, due to the channel hardening effect in massive MIMO, the backhaul links experience long term channel effects only, whereas the access links experience both the long term and short term channel effects. Consequently, the developed framework is flexible to characterize different sources of interference while capturing the heterogeneity of the access and backhaul channels. In specific scenarios, the framework enables deriving closed-form coverage probability expressions. Under perfect backhaul coverage, the simplified expressions are utilized to optimize the proportion of in-band and out-of-band small cells in the SCN in closed-form. Finally, few remedial solutions are proposed that can potentially mitigate the backhaul interference and in turn improve the performance of in-band FD wireless backhauling. Numerical results investigate the scenarios in which in-band wireless backhauling is useful and demonstrate that maintaining a correct proportion of in-band and out-of-band FD small cells is crucial in wireless backhauled SCNs.

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arXiv2017

Charging and Discharging of Plug-In Electric Vehicles (PEVs) in Vehicle-to-Grid (V2G) Systems: A Cyber Insurance-Based Model

In addition to being environment-friendly, vehicle-to-grid (V2G) systems can help the plug-in electric vehicle (PEV) users in reducing their energy costs and can also help stabilizing energy demand in the power grid. In V2G systems, since the PEV users need to obtain system information (e.g., locations of charging/discharging stations, current load and supply of the power grid) to achieve the best charging and discharging performance, data communication plays a crucial role. However, since the PEV users are highly mobile, information from V2G systems is not always available for many reasons, e.g., wireless link failures and cyber attacks. Therefore, in this paper, we introduce a novel concept using cyber insurance to "transfer" cyber risks, e.g., unavailable information, of a PEV user to a third party, e.g., a cyber insurance company. Under the insurance coverage, even without information about V2G systems, a PEV user is always guaranteed the best price for charging/discharging. In particular, we formulate the optimal energy cost problem for the PEV user by adopting a Markov decision process framework. We then propose a learning algorithm to help the PEV user make optimal decisions, e.g., to charge or discharge and to buy or not to buy insurance, in an online fashion. Through simulations, we show that cyber insurance is an efficient solution not only in dealing with cyber risks, but also in maximizing revenue of the PEV user.

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arXiv2016

Non-Orthogonal Multiple Access (NOMA) for Downlink Multiuser MIMO Systems: User Clustering, Beamforming, and Power Allocation

We investigate the application of non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the base station (BS). We first dynamically group the UE receive antennas into a number of clusters equal to or more than the number of BS transmit antennas. A single beamforming vector is then shared by all the receive antennas in a cluster. We propose a linear beamforming technique in which all the receive antennas can significantly cancel the inter-cluster interference. On the other hand, the receive antennas in each cluster are scheduled on power domain NOMA basis with SIC at the receiver ends. For inter-cluster and intra-cluster power allocation, we provide dynamic power allocation solutions with an objective to maximizing the overall cell capacity. An extensive performance evaluation is carried out for the proposed MIMO-NOMA system and the results are compared with those for conventional orthogonal multiple access (OMA)-based MIMO systems and other existing MIMO-NOMA solutions. The numerical results quantify the capacity gain of the proposed MIMO-NOMA model over MIMO-OMA and other existing MIMO-NOMA solutions.

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arXiv2016

Modeling and Analysis of Uplink Non-Orthogonal Multiple Access (NOMA) in Large-Scale Cellular Networks Using Poisson Cluster Processes

Non-orthogonal multiple access (NOMA) serves multiple users by superposing their distinct message signals. The desired message signal is decoded at the receiver by applying successive interference cancellation (SIC). Using the theory of Poisson cluster process (PCP), we provide a framework to analyze multi-cell uplink NOMA systems. Specifically, we characterize the rate coverage probability of a NOMA user who is at rank $m$ (in terms of the distance from its serving BS) among all users in a cell and the mean rate coverage probability of all users in a cell. Since the signal-to-interference-plus-noise ratio (SINR) of $m$-th user relies on efficient SIC, we consider three scenarios, i.e., perfect SIC (in which the signals of $m-1$ interferers who are stronger than $m$-th user are decoded successfully), imperfect SIC (in which the signals of of $m-1$ interferers who are stronger than $m$-th user may or may not be decoded successfully), and imperfect worst case SIC (in which the decoding of the signal of $m$-th user is always unsuccessful whenever the decoding of its relative $m-1$ stronger users is unsuccessful). The derived expressions are customized to capture the performance of a user at rank $m$ in an equivalent orthogonal multiple access (OMA) system. Finally, numerical results are presented to validate the derived expressions.

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arXiv2016

Minority Games With Applications to Distributed Decision Making and Control in Wireless Networks

Fifth generation (5G) dense small cell networks (SCNs) are expected to meet the thousand-fold mobile traffic challenge within the next few years. When developing solution schemes for resource allocation problems in such networks, conventional centralized control is no longer viable due to excessive computational complexity and large signaling overhead caused by the large number of users and network nodes in such a network. Instead, distributed resource allocation (or decision making) methods with low complexity would be desirable to make the network self-organizing and autonomous. Minority game (MG) has recently gained attention of the research community as a tool to model and solve distributed resource allocation problems. The main objective of this article is to study the applicability of the MG to solve the distributed decision making problems in future wireless networks. We present the fundamental theoretical aspects of basic MG, some variants of MG, and the notion of equilibrium. We also study the current state-of-the-art on the applications of MGs in communication networks. Furthermore, we describe an example application of MG to SCNs, where the problem of computation offloading by users in an SCN is modeled and analyzed using MG.

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arXiv2016

Non-Orthogonal Multiple Access (NOMA) in Cellular Uplink and Downlink: Challenges and Enabling Techniques

By combining the concepts of superposition coding at the transmitter(s) and successive interference cancellation (SIC) at the receiver(s), non-orthogonal multiple access (NOMA) has recently emerged as a promising multiple access technique for 5G wireless technology. In this article, we first discuss the fundamentals of uplink and downlink NOMA transmissions and outline their key distinctions (in terms of implementation complexity, detection and decoding at the SIC receiver(s), incurred intra-cell and inter-cell interferences). Later, for both downlink and uplink NOMA, we theoretically derive the NOMA dominant condition for each individual user in a two-user NOMA cluster. NOMA dominant condition refers to the condition under which the spectral efficiency gains of NOMA are guaranteed compared to conventional orthogonal multiple access (OMA). The derived conditions provide direct insights on selecting appropriate users in two-user NOMA clusters. The conditions are distinct for uplink and downlink as well as for each individual user. Numerical results show the significance of the derived conditions for the user selection in uplink/downlink NOMA clusters and provide a comparison to the random user selection. A brief overview of the recent research investigations is then provided to highlight the existing research gaps. Finally, we discuss the potential applications and key challenges of NOMA transmissions.

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arXiv2016

LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities

Massive Machine-Type Communications (MTC) over cellular networks is expected to be an integral part of wireless "Smart City" applications. The Long Term Evolution (LTE)/LTE-Advanced (LTE-A) technology is a major candidate for provisioning of MTC applications. However, due to the diverse characteristics of payload size, transmission periodicity, power efficiency, and quality of service (QoS) requirement, MTC poses huge challenges to LTE/LTE-A technologies. In particular, efficient management of massive random access is one of the most critical challenges. In case of massive random access attempts, the probability of preamble collision drastically increases, thus the performance of LTE/LTE-A random access degrades sharply. In this context, this article reviews the current state-of-the-art proposals to control massive random access of MTC devices in LTE/LTE-A networks. The proposals are compared in terms of five major metrics, namely, access delay, access success rate, power efficiency, QoS guarantee, and the effect on Human-Type Communications (HTC). To this end, we propose a novel collision resolution random access model for massive MTC over LTE/LTE-A. Our proposed model basically resolves the preamble collisions instead of avoidance, and targets to manage massive and bursty access attempts. Simulations of our proposed model show huge improvements in random access success rate compared to the standard slotted-Aloha-based models. The new model can also coexist with existing LTE/LTE-A Medium Access Control (MAC) protocol, and ensure high reliability and time-efficient network access.

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arXiv2016

Dynamic User Clustering and Power Allocation for Uplink and Downlink Non-Orthogonal Multiple Access (NOMA) Systems

In this paper, first we briefly describe the differences in the working principles of uplink and downlink NOMA transmissions. Then, for both uplink and downlink NOMA, we formulate a sum-throughput maximization problem in a cell such that the user clustering (i.e., grouping users into a single cluster or multiple clusters) and power allocations in NOMA cluster(s) can be optimized under transmission power constraints, minimum rate requirements of the users, and SIC constraints. Due to the combinatorial nature of the formulated mixed integer non-linear programming (MINLP) problem, we solve the problem in two steps, i.e., by first grouping users into clusters and then optimizing their respective power allocations. In particular, we propose a low-complexity sub-optimal user grouping scheme. The proposed scheme exploits the channel gain differences among users in a NOMA cluster and group them into a single cluster or multiple clusters in order to enhance the sum-throughput of the system. For a given set of NOMA clusters, we then derive the optimal power allocation policy that maximizes the sum throughput per NOMA cluster and in turn maximizes the overall system throughput. Using KKT optimality conditions, closed-form solutions for optimal power allocations are derived for any cluster size, considering both uplink and downlink NOMA systems. Numerical results compare the performance of NOMA over orthogonal multiple access (OMA) and illustrate the significance of NOMA in various network scenarios.

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