1,485 research outputs found

    On Modeling Heterogeneous Wireless Networks Using Non-Poisson Point Processes

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    Future wireless networks are required to support 1000 times higher data rate, than the current LTE standard. In order to meet the ever increasing demand, it is inevitable that, future wireless networks will have to develop seamless interconnection between multiple technologies. A manifestation of this idea is the collaboration among different types of network tiers such as macro and small cells, leading to the so-called heterogeneous networks (HetNets). Researchers have used stochastic geometry to analyze such networks and understand their real potential. Unsurprisingly, it has been revealed that interference has a detrimental effect on performance, especially if not modeled properly. Interference can be correlated in space and/or time, which has been overlooked in the past. For instance, it is normally assumed that the nodes are located completely independent of each other and follow a homogeneous Poisson point process (PPP), which is not necessarily true in real networks since the node locations are spatially dependent. In addition, the interference correlation created by correlated stochastic processes has mostly been ignored. To this end, we take a different approach in modeling the interference where we use non-PPP, as well as we study the impact of spatial and temporal correlation on the performance of HetNets. To illustrate the impact of correlation on performance, we consider three case studies from real-life scenarios. Specifically, we use massive multiple-input multiple-output (MIMO) to understand the impact of spatial correlation; we use the random medium access protocol to examine the temporal correlation; and we use cooperative relay networks to illustrate the spatial-temporal correlation. We present several numerical examples through which we demonstrate the impact of various correlation types on the performance of HetNets.Comment: Submitted to IEEE Communications Magazin

    Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

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    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

    ASK-based spatial multiplexing RGB scheme using symbol-dependent self-interference for detection

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    We propose a vsible light communication scheme utilizing red, green and blue lightemitting diodes (LEDs) and three color-Tuned photodiodes. Amplitude shift keying modulation is considered, and its effect on light emission in terms of flickering, dimming, and color rendering is discussed. The presence of interference at each photodiode generated by the other two colors is used to improve detection since interference is symbol-dependent. Moreover, the capability of the photodiodes to follow the LEDs speed is considered by analyzing the possibility of equalizing the received signal, and also self-interference mitigation is proposed. The system performance is evaluated both with computer simulations and tests on an Arduino board implementation

    Realistic geometry-based stochastic channel models for advanced wireless MIMO systems

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    The employment of multiple antennas at both the Transmitter (Tx) and Receiver (Rx) enables the so-called Multiple-Input Multiple-Output (MIMO) technologies to greatly improve the link reliability and increase the overall system capacity. MIMO has been recommended to be employed in various advanced wireless communication systems, e.g., the Fourth Generation (4G) wireless systems and beyond. For the successful design, performance test, and simulation of MIMO wireless communication systems, a thorough understanding of the underlying MIMO channels and corresponding models are indispensable. The approach of geometry-based stochastic modelling has widely been used due to its advantages, such as convenience for theoretical analysis and mathematical tractability. In addition, wireless Vehicle-to-Vehicle (V2V) communications play an important role in mobile relay-based cellular networks, vehicular ad hoc networks, and intelligent transportation systems. In V2V communication systems, both the Tx and Rx are in motion and equipped with low elevation antennas. This is di erent from conventional Fixed-to-Mobile (F2M) cellular systems, where only one terminal moves. This PhD project is therefore devoted to the modelling and simulation of wireless MIMO channels for both V2V and F2M communication systems. In this thesis, we rst propose a novel narrowband Three Dimensional (3D) theoretical Regular-Shape Geometry Based Stochastic Model (RS-GBSM) and the corresponding Sum-of-Sinusoids (SoS) simulation model for non-isotropic MIMO V2V Ricean fading channels. The proposed RS-GBSM has the ability to study the impact of the Vehicular Tra c Density (VTD) on channel statistics and jointly considers the azimuth and elevation angles by using the von Mises-Fisher (VMF) distribution. Moreover, a novel parameter computation method is proposed for jointly calculating the azimuth and elevation angles in the SoS channel simulator. Based on the proposed 3D theoretical RS-GBSM and its SoS simulation model, statistical properties are derived and thoroughly investigated. The impact of the elevation angle in the 3D model on key statistical properties is investigated by comparing with those of the corresponding Two Dimensional (2D) model. It is demonstrated that the 3D model is more practical to characterise real V2V channels, in particular for pico-cell scenarios. Secondly, actual V2V channel measurements have shown that the modelling assumption of Wide Sense Stationary (WSS) is valid only for very short time intervals. This fact inspires the requirement of non-WSS V2V channel models. Therefore, we propose a novel 3D theoretical wideband MIMO non-WSS V2V RS-GBSM and corresponding SoS simulation model. Due to the dynamic movement of both the Tx and Rx, the Angle of Departure (AoD) and Angle of Arrival (AoA) are time-variant, which makes our model non-stationary. The proposed RS-GBSMs are su ciently generic and adaptable to mimic various V2V scenarios. Furthermore, important local channel statistical properties are derived and thoroughly investigated. The impact of non-stationarity on these channel statistical properties is investigated by comparing with those of the corresponding WSS model. The proposed non-WSS RS-GBSMs are validated by measurements in terms of the channel stationary time. Thirdly, realistic MIMO channel models with a proper trade-o between accuracy and complexity are indispensable for the practical application. By comparing the accuracy and complexity of two latest F2M standardised channel models (i.e., LTE-A and IMT-A channel models), we employ some channel statistical properties as the accuracy metrics and the number of Real Operations (ROs) as the complexity metric. It is shown that the LTE-A MIMO channel model is simple but has signi cant aws in terms of the accuracy. The IMT-A channel model is complicated but has better accuracy. Therefore, we focus on investigating various complexity reduction methods to simplify the IMT-A channel model. The results have shown that the proposed methods do not degrade much the accuracy of the IMT-A channel model, whereas they can signi cantly reduce the complexity in terms of the number of ROs and channel coe cients computing time. Finally, to investigate the non-stationarity of the IMT-A MIMO channel model, we further propose a non-WSS channel model with time-varying AoDs and AoAs. The proposed time-varying functions can be applied to various scenarios according to moving features of Moving Clusters (MCs) and a Mobile Station (MS). Moreover, the impacts of time-varying AoDs and AoAs on local statistical properties are investigated thoroughly. Simulation results prove that statistical properties are varied with time due to the non-stationarity of the proposed channel model. In summary, the proposed reference models and channel simulators are useful for the design, testing, and performance evaluation of advanced wireless V2V and F2M MIMO communication systems

    CHANNEL MODELING FOR FIFTH GENERATION CELLULAR NETWORKS AND WIRELESS SENSOR NETWORKS

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    In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance
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