arXiv subjects

M. Majid Butt

Publications and source records attributed to M. Majid Butt.

36 records · Page 2Linked to original sources

arXiv2018

Joint User Association and BS Switching Scheme for Green Heterogeneous Cellular Network

A dense deployment of on-grid small cell base stations (SBSs) in a heterogeneous cellular network (HCN) results in large power consumption which can be reduced by utilizing harvested energy from scavenge sources. Recently, a new layout for HCN with energy harvesting-SBSs (EH-SBSs) has been proposed to reduce inter-cell interference and power consumption; and increase system energy efficiency. In this paper, an energy efficient joint user association and BS on-off scheme for an HCN having diverse energy source(s) is proposed, which aims at utilizing the harvested energy efficiently in order to reduce the on-grid power consumption. The scheme operates in two phases. First, it decides which BS should be in off, sleep or active mode and iteratively updates its transmit power based on energy arrival and consumption, to minimize interference and on-grid power consumption. Secondly, for further reduction in on-grid power consumption, the user discovers and associates itself with the nearest available EH-SBS. The system energy consumption for the proposed scheme is numerically evaluated using Monte Carlo simulations. Simulation results reveal that the proposed scheme shows significantly better results as compared to other schemes in the literature in terms of grid power consumption and energy efficiency.

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arXiv2018

Fair Dynamic Spectrum Management in Licensed Shared Access Systems

Licensed Shared Access (LSA) is a spectrum sharing mechanism where bandwidth is shared between a primary network, called incumbent, and a secondary mobile network. In this work, we address dynamic spectrum management mechanisms for LSA systems. We propose a fair spectrum management algorithm for distributing incumbent's available spectrum among mobile networks. Then, we adapt the proposed algorithm to take mobile network operator's regulatory compliance aspect into account and penalize the misbehaving network operators in spectrum allocation. We extend our results to the scenario where more than one incumbent offer spectrum to the mobile operators in a service area and propose various protocols, which ensure long term fair spectrum allocation within the individual LSA networks. Finally, we numerically evaluate the performance of the proposed spectrum allocation algorithms and compare them using various performance metrics. For the single incumbent case, the numerical results show that the spectrum allocation is fair when the mobile operators follow the spectrum access regulations. We demonstrate the effect of our proposed penalty functions on spectrum allocation when the operators do not comply with the regulatory aspects. For the multi-incumbent scenario, the results show a trade-off between efficient spectrum allocation and flexibility in spectrum access for our proposed algorithms.

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arXiv2018

On Minimizing Energy Consumption for D2D Clustered Caching Networks

We formulate and solve the energy minimization problem for a clustered device-to-device (D2D) network with cache-enabled mobile devices. Devices are distributed according to a Poisson cluster process (PCP) and are assumed to have a surplus memory which is exploited to proactively cache files from a library. Devices can retrieve the requested files from their caches, from neighboring devices in their proximity (cluster), or from the base station as a last resort. We minimize the energy consumption of the proposed network under a random prob- abilistic caching scheme, where files are independently cached according to a specific probability distribution. A closed-form expression for the D2D coverage probability is obtained. The energy consumption problem is then formulated as a function of the caching distribution, and the optimal probabilistic caching distribution is obtained. Results reveal that the proposed caching distribution reduces energy consumption up to 33% as compared to caching popular files scheme.

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arXiv2018

Spectrum Matching in Licensed Spectrum Sharing

Spectrum sharing is one of the promising solutions to meet the spectrum demand in 5G networks that results from the emerging services like machine to machine and vehicle to infrastructure communication. The idea is to allow a set of entities access the spectrum whenever and wherever it is unused by the licensed users. In the proposed framework, different spectrum provider (SP) networks with surplus spectrum available may rank the operators requiring the spectrum, called spectrum users (SUs) hereafter, differently in terms of their preference to lease spectrum, based for example on target business market considerations of the SUs. Similarly, SUs rank SPs depending on a number of criteria, for example based on coverage and availability in a service area. Ideally, both SPs and SUs prefer to provide/get spectrum to/from the operator of their first choice, but this is not necessarily always possible due to conflicting preferences. We apply matching theory algorithms with the aim to resolve the conflicting preferences of the SPs and SUs and quantify the effect of the proposed matching theory approach on establishing preferred (spectrum) provider-user network pairs. We discuss both one-to-one and many-to-one spectrum sharing scenarios and evaluate the performance using Monte Carlo simulations. The results show that comprehensive gains in terms of preferred matching of the provider-user network pairs can be achieved by applying matching theory for spectrum sharing as compared to uncoordinated spectrum allocation of the available spectrum to the SUs.

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arXiv2018

On Optimizing Power Allocation For Reliable Communication over Fading Channels with Uninformed Transmitter

We investigate energy efficient packet scheduling and power allocation problem for the services which require reliable communication to guarantee a certain quality of experience (QoE). We establish links between average transmit power and reliability of data transfer, which depends on both average amount of data transfer and short term rate guarantees. We consider a slow-fading point-to-point channel without channel state information at the transmitter side (CSIT). In the absence of CSIT, the slow fading channel has an outage probability associated with every transmit power. As a function of data loss tolerance parameters, and minimum rate and peak power constraints, we formulate an optimization problem that adapts rate and power to minimize the average transmit power for the user equipment (UE). Then, a relaxed optimization problem is formulated where transmission rate is assumed to be fixed for each packet transmission. We use Markov chain to model constraints of the optimization problem. The corresponding problem is not convex for both of the formulated problems, therefore a stochastic optimization technique, namely the simulated annealing algorithm, is used to solve them. The numerical results quantify the effect of various system parameters on average transmit power and show significant energy savings when the service has less stringent requirements on timely and reliable communication.

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arXiv2018

Inter-cluster Cooperation for Wireless D2D Caching Networks

Proactive wireless caching and device to device (D2D) communication have emerged as promising techniques for enhancing users' quality of service and network performance. In this paper, we propose a new architecture for D2D caching with inter-cluster cooperation. We study a cellular network in which users cache popular files and share them with other users either in their proximity via D2D communication or with remote users using cellular transmission. We characterize the network average delay per request from a queuing perspective. Specifically, we formulate the delay minimization problem and show that it is NP-hard. Furthermore, we prove that the delay minimization problem is equivalent to the minimization of a non-increasing monotone supermodular function subject to a uniform partition matroid constraint. A computationally efficient greedy algorithm is proposed which is proven to be locally optimal within a factor 0.63 of the optimum. We analyze the average per request throughput for different caching schemes and conduct the scaling analysis for the average sum throughput. We show how throughput scaling depends on video content popularity when the number of files grows asymptotically large. Simulation results show a delay reduction of 45% to 80% compared to a D2D caching system without inter-cluster cooperation.

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arXiv2018

Performance of Massive MIMO Self-Backhauling for Ultra-Dense Small Cell Deployments

A key aspect of the fifth-generation wireless communication network will be the integration of different services and technologies to provide seamless connectivity. In this paper, we consider using massive multiple-input multiple-output (mMIMO) to provide backhaul links to a dense deployment of self-backhauling (s-BH) small cells (SCs) that provide cellular access within the same spectrum resources of the backhaul. Through a comprehensive system-level simulation study, we evaluate the interplay between access and backhaul and the resulting end-to-end user rates. Moreover, we analyze the impact of different SCs deployment strategies, while varying the time resource allocation between radio access and backhaul links. We finally compare the above mMIMO-based s-BH approach to a mMIMO direct access (DA) architecture accounting for the effects of pilot reuse schemes, together with their associated overhead and contamination mitigation effects. The results show that dense SCs deployments supported by mMIMO s-BH provide significant rate improvements for cell-edge users (UEs) in ultra-dense deployments with respect to mMIMO DA, while the latter outperforms mMIMO s-BH from the median UEs' standpoint.

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arXiv2017

Complex Systems Science meets 5G and IoT

We propose a new paradigm for telecommunications, and develop a framework drawing on concepts from information (i.e., different metrics of complexity) and computational (i.e., agent based modeling) theory, adapted from complex system science. We proceed in a systematic fashion by dividing network complexity understanding and analysis into different layers. Modelling layer forms the foundation of the proposed framework, supporting analysis and tuning layers. The modelling layer aims at capturing the significant attributes of networks and the interactions that shape them, through the application of tools such as agent-based modelling and graph theoretical abstractions, to derive new metrics that holistically describe a network. The analysis phase completes the core functionality of the framework by linking our new metrics to the overall network performance. The tuning layer augments this core with algorithms that aim at automatically guiding networks toward desired conditions. In order to maximize the impact of our ideas, the proposed approach is rooted in relevant, near-future architectures and use cases in 5G networks, i.e., Internet of Things (IoT) and self-organizing cellular networks.

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arXiv2017

Delay Analysis for Wireless D2D Caching with Inter-cluster Cooperation

Proactive wireless caching and D2D communication have emerged as promising techniques for enhancing users' quality of service and network performance. In this paper, we propose a new architecture for D2D caching with inter-cluster cooperation. We study a cellular network in which users cache popular files and share them with other users either in their proximity via D2D communication or with remote users using cellular transmission. We characterize the network average delay per request from a queuing perspective. Specifically, we formulate the delay minimization problem and show that it is NP-hard. Furthermore, we prove that the delay minimization problem is equivalent to minimization of a non-increasing monotone super modular function subject to a partition matroid constraint. A computationally efficient greedy algorithm is proposed which is proven to be locally optimal within a factor 2 of the optimum. Simulation results show more than 45% delay reduction compared to a D2D caching system without inter-cluster cooperation.

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arXiv2017

Energy Efficient Scheduling for Loss Tolerant IoT Applications with Uninformed Transmitter

In this work we investigate energy efficient packet scheduling problem for the loss tolerant applications. We consider slow fading channel for a point to point connection with no channel state information at the transmitter side (CSIT). In the absence of CSIT, the slow fading channel has an outage probability associated with every transmit power. As a function of data loss tolerance parameters and peak power constraints, we formulate an optimization problem to minimize the average transmit energy for the user equipment (UE). The optimization problem is not convex and we use stochastic optimization technique to solve the problem. The numerical results quantify the effect of different system parameters on average transmit power and show significant power savings for the loss tolerant applications.

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arXiv2016

Energy and Bursty Packet Loss Tradeoff over Fading Channels: A System Level Model

Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross layer design framework when channel state information is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance trade-off numerically and show the effect of channel uncertainty on the packet scheduler design.

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arXiv2016

Minimizing Outage Probability by Exploiting CSI in Wireless Powered Cooperative Networks

In this work, we address the relay selection problem for the wireless powered communication networks, where the relays harvest energy from the source radio frequency signals. A single source-destination pair is considered without a direct link. The connecting relay nodes are equipped with storage batteries of infinite size. We assume that the channel state information (CSI) on the source-relay link is available at the relay nodes. Depending on the availability of the CSI on the relay-destination link at the relay node, we propose different relay selection schemes and evaluate the outage probability. The availability of the CSI at the relay node on the relay-destination link considerably improves the performance due to additional flexibility in the relay selection mechanism. We numerically quantify the performance for the proposed schemes and compare the outage probability for fixed and equal number of wireless powered forwarding relays.

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arXiv2016

Energy-Aware Cooperative Wireless Networks with Multiple Cognitive Users

In this paper, we study and analyze cooperative cognitive radio networks with arbitrary number of secondary users (SUs). Each SU is considered a prospective relay for the primary user (PU) besides having its own data transmission demand. We consider a multi-packet transmission framework which allows multiple SUs to transmit simultaneously thanks to dirty-paper coding. We propose power allocation and scheduling policies that optimize the throughput for both PU and SU with minimum energy expenditure. The performance of the system is evaluated in terms of throughput and delay under different opportunistic relay selection policies. Towards this objective, we present a mathematical framework for deriving stability conditions for all queues in the system. Consequently, the throughput of both primary and secondary links is quantified. Furthermore, a moment generating function (MGF) approach is employed to derive a closed-form expression for the average delay encountered by the PU packets. Results reveal that we achieve better performance in terms of throughput and delay at lower energy cost as compared to equal power allocation schemes proposed earlier in literature. Extensive simulations are conducted to validate our theoretical findings.

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arXiv2015

Maximizing Energy Efficiency in Multiple Access Channels by Exploiting Packet Dropping and Transmitter Buffering

Quality of service (QoS) for a network is characterized in terms of various parameters specifying packet delay and loss tolerance requirements for the application. The unpredictable nature of the wireless channel demands for application of certain mechanisms to meet the QoS requirements. Traditionally, medium access control (MAC) and network layers perform these tasks. However, these mechanisms do not take (fading) channel conditions into account. In this paper, we investigate the problem using cross layer techniques where information flow and joint optimization of higher and physical layer is permitted. We propose a scheduling scheme to optimize the energy consumption of a multiuser multi-access system such that QoS constraints in terms of packet loss are fulfilled while the system is able to maximize the advantages emerging from multiuser diversity. Specifically, this work focuses on modeling and analyzing the effects of packet buffering capabilities of the transmitter on the system energy for a packet loss tolerant application. We discuss low complexity schemes which show comparable performance to the proposed scheme. The numerical evaluation reveals useful insights about the coupling effects of different QoS parameters on the system energy consumption and validates our analytical results.

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arXiv2014

Trading Wireless Information and Power Transfer: Relay Selection to Minimize the Outage Probability

This paper studies the outage probability minimization problem for a multiple relay network with energy harvesting constraints. The relays are hybrid nodes used for simultaneous wireless information and power transfer from the source radio frequency (RF) signals. There is a trade-off associated with the amount of time a relay node is used for energy and information transfer. Large intervals of information transfer implies little time for energy harvesting from RF signals and thus, high probability of outage events. We propose relay selection schemes for a cooperative system with a fixed number of RF powered relays. We address both causal and non-causal channel state information cases at the relay--destination link and evaluate the trade-off associated with information/power transfer in the context of minimization of outage probability.

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arXiv2014

Effective Capacity of Cognitive Radio Links: Accessing Primary Feedback Erroneously

We study the performance of a cognitive system modeled by one secondary and one primary link and operating under statistical quality of service (QoS) delay constraints. We analyze the effective capacity (EC) to quantify the secondary user (SU) performance under delay constraints. The SU intends to maximize the benefit of the feedback messages on the primary link to reduce SU interference for primary user (PU) and makes opportunistic use of the channel to transmit his packets. We assume that SU has erroneous access to feedback information of PU. We propose a three power level scheme and study the tradeoff between degradation in EC of SU and reliability of PU defined as the success rate of the transmitted packets. Our analysis shows that increase in error in feedback access causes more interference to PU and packet success rate decreases correspondingly.

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arXiv2014

Energy Efficient Multiuser Scheduling: Statistical Guarantees on Bursty Packet Loss

In this paper, we consider energy efficient multiuser scheduling. Packet loss tolerance of the applications is exploited to minimize average system energy. There is a constraint on average packet drop rate and maximum number of packets dropped successively (bursty loss). A finite buffer size is assumed. We propose a scheme which schedules the users opportunistically according to the channel conditions, packet loss constraints and buffer size parameters. We assume imperfect channel state information at the transmitter side and analyze the scheme in large user limit using stochastic optimization techniques. First, we optimize system energy for a fixed buffer size which results in a corresponding statistical guarantee on successive packet drop. Then, we determine the minimum buffer size to achieve a target (improved) energy efficiency for the same (or better) statistical guarantee. We show that buffer size can be traded effectively to achieve system energy efficiency for target statistical guarantees on packet loss parameters.

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arXiv2010

Linear Finite-Field Deterministic Networks With Many Sources and One Destination

We find the capacity region of linear finite-field deterministic networks with many sources and one destination. Nodes in the network are subject to interference and broadcast constraints, specified by the linear finite-field deterministic model. Each node can inject its own information as well as relay other nodes' information. We show that the capacity region coincides with the cut-set region. Also, for a specific case of correlated sources we provide necessary and sufficient conditions for the sources transmissibility. Given the "deterministic model" approximation for the corresponding Gaussian network model, our results may be relevant to wireless sensor networks where the sensing nodes multiplex the relayed data from the other nodes with their own data, and where the goal is to decode all data at a single "collector" node.

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