End-to-End Simulation of 5G mmWave Networks

Due to its potential for multi-gigabit and low latency wireless links, millimeter wave (mmWave) technology is expected to play a central role in 5th generation cellular systems. While there has been considerable progress in understanding the mmWave physical layer, innovations will be required at all layers of the protocol stack, in both the access and the core network. Discrete-event network simulation is essential for end-to-end, cross-layer research and development. This paper provides a tutorial on a recently developed full-stack mmWave module integrated into the widely used open-source ns--3 simulator. The module includes a number of detailed statistical channel models as well as the ability to incorporate real measurements or ray-tracing data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and highly customizable, making it easy to integrate algorithms or compare Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example. The module is interfaced with the core network of the ns--3 Long Term Evolution (LTE) module for full-stack simulations of end-to-end connectivity, and advanced architectural features, such as dual-connectivity, are also available. To facilitate the understanding of the module, and verify its correct functioning, we provide several examples that show the performance of the custom mmWave stack as well as custom congestion control algorithms designed specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and Tutorials (revised Jan. 2018

Experimenting with commodity 802.11 hardware: overview and future directions

The huge adoption of 802.11 technologies has triggered a vast amount of experimentally-driven research works. These works range from performance analysis to protocol enhancements, including the proposal of novel applications and services. Due to the affordability of the technology, this experimental research is typically based on commercial off-the-shelf (COTS) devices, and, given the rate at which 802.11 releases new standards (which are adopted into new, affordable devices), the field is likely to continue to produce results. In this paper, we review and categorise the most prevalent works carried out with 802.11 COTS devices over the past 15 years, to present a timely snapshot of the areas that have attracted the most attention so far, through a taxonomy that distinguishes between performance studies, enhancements, services, and methodology. In this way, we provide a quick overview of the results achieved by the research community that enables prospective authors to identify potential areas of new research, some of which are discussed after the presentation of the survey.This work has been partly supported by the European Community through the CROWD project (FP7-ICT-318115) and by the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919).Publicad

ABC: A Simple Explicit Congestion Controller for Wireless Networks

We propose Accel-Brake Control (ABC), a simple and deployable explicit congestion control protocol for network paths with time-varying wireless links. ABC routers mark each packet with an "accelerate" or "brake", which causes senders to slightly increase or decrease their congestion windows. Routers use this feedback to quickly guide senders towards a desired target rate. ABC requires no changes to header formats or user devices, but achieves better performance than XCP. ABC is also incrementally deployable; it operates correctly when the bottleneck is a non-ABC router, and can coexist with non-ABC traffic sharing the same bottleneck link. We evaluate ABC using a Wi-Fi implementation and trace-driven emulation of cellular links. ABC achieves 30-40% higher throughput than Cubic+Codel for similar delays, and 2.2X lower delays than BBR on a Wi-Fi path. On cellular network paths, ABC achieves 50% higher throughput than Cubic+Codel

Traffic Steering in Radio Level Integration of LTE and Wi-Fi Networks

A smartphone generates approximately 1, 614 MB of data per month which is 48 times of the data generated by a typical basic-feature cell phone. Cisco forecasts that the mobile data traffic growth will remain to increase and reach 49 Exabytes per month by 2021. However, the telecommunication service providers/operators face many challenges in order to improve cellular network capacity to match these ever-increasing data demands due to low, almost flat Average Revenue Per User (ARPU) and low Return on Investment (RoI). Spectrum resource crunch and licensing requirement for operation in cellular bands further complicate the procedure to support and manage the network. In order to deal with the aforementioned challenges, one of the most vital solutions is to leverage the integration benefits of cellular networks with unlicensed operation of Wi-Fi networks. A closer level of cellular and Wi-Fi coupling/interworking improves Quality of Service (QoS) by unified connection management to user devices (UEs). It also offloads a significant portion of user traffic from cellular Base Station (BS) to Wi-Fi Access Point (AP). In this thesis, we have considered the cellular network to be Long Term Evolution (LTE) popularly known as 4G-LTE for interworking with Wi-Fi. Third Generation Partnership Project (3GPP) defined various LTE and Wi-Fi interworking architectures from Rel-8 to Rel-11. Because of the limitations in these legacy LTE Wi-Fi interworking solutions, 3GPP proposed Radio Level Integration (RLI) architectures to enhance flow mobility and to react fast to channel dynamics. RLI node encompasses link level connection between Small cell deployments, (ii) Meeting Guaranteed Bit Rate (GBR) requirements of the users including those experiencing poor Signal to Interference plus Noise Ratio (SINR), and (iii) Dynamic steering of the flows across LTE and Wi-Fi links to maximize the system throughput. The second important problem addressed is the uplink traffic steering. To enable efficient uplink traffic steering in LWIP system, in this thesis, Network Coordination Function (NCF) is proposed. NCF is realized at the LWIP node by implementing various uplink traffic steering algorithms. NCF encompasses four different uplink traffic steering algorithms for efficient utilization of Wi-Fi resources in LWIP system. NCF facilitates the network to take intelligent decisions rather than individual UEs deciding to steer the uplink traffic onto LTE link or Wi-Fi link. The NCF algorithms work by leveraging the availability of LTE as the anchor to improvise the channel utilization of Wi-Fi. The third most important problem is to enable packet level steering in LWIP. When data rates of LTE and Wi-Fi links are incomparable, steering packets across the links create problems for TCP traffic. When the packets are received Out-of-Order (OOO) at the TCP receiver due to variation in delay experienced on each link, it leads to the generation of DUPlicate ACKnowledgements (DUP-ACK). These unnecessary DUP-ACKs adversely affect the TCP congestion window growth and thereby lead to poor TCP performance. This thesis addresses this problem by proposing a virtual congestion control mechanism (VIrtual congeStion control wIth Boost acknowLedgEment -VISIBLE). The proposed mechanism not only improves the throughput of a flow by reducing the number of unnecessary DUPACKs delivered to the TCP sender but also sends Boost ACKs in order to rapidly grow the congestion window to reap in aggregation benefits of heterogeneous links. The fourth problem considered is the placement of LWIP nodes. In this thesis, we have addressed problems pertaining to the dense deployment of LWIP nodes. LWIP deployment can be realized in colocated and non-colocated fashion. The placement of LWIP nodes is done with the following objectives: (i) Minimizing the number of LWIP nodes deployed without any coverage holes, (ii) Maximizing SINR in every sub-region of a building, and (iii) Minimizing the energy spent by UEs and LWIP nodes. Finally, prototypes of RLI architectures are presented (i.e., LWIP and LWA testbeds). The prototypes are developed using open source LTE platform OpenAirInterface (OAI) and commercial-off-the-shelf hardware components. The developed LWIP prototype is made to work with commercial UE (Nexus 5). The LWA prototype requires modification at the UE protocol stack, hence it is realized using OAI-UE. The developed prototypes are coupled with the legacy multipath protocol such as MPTCP to investigate the coupling benefits

Coexistence of Wi-Fi and 5G NR-U in the Unlicensed Band

The communications industry continues to evolve to meet the ever-growing demands of fast connectivity and higher energy-efficiency and has emerged the concept of Internet of Things (IoT) systems. IoT devices can be run on Wi-Fi or cellular network, helping businesses to receive higher return on investments. As billions of devices on cellular networks operate on the limited licensed spectrum, it is becoming scarcer. Mobile network operators are investigating to access the immense unlicensed spectrum, on which Wi-Fi is prominently operated. Managing this coexistence between the cellular and Wi-Fi networks poses several challenges. One challenge is the spectrum sharing that affects the network capacity and the spectrum efficiency by properly allocating the available resources for each technology. A second challenge is to maintain the quality of service (QoS) while maximizing the aggregated throughput. A final challenge is to reduce the power consumption of cellular base stations by creating a sleep/wakeup policy, thereby lowering the capital and operating expenses for the mobile network operators. To this end, this thesis proposes various optimization modeling for the coexistence mechanisms in the unlicensed spectrum, as well as intelligent techniques to manage the increasing power consumption with increased usage. First, this thesis develops optimization modeling techniques to properly allocate resources for the coexistence of the Wi-Fi and cellular networks by improving the aggregate throughput, while maintaining the minimum required power consumption. Next, this thesis implements the coexistence mechanism by simulating real-time traffic information to maximize the aggregate throughput, while satisfying the QoS for each user. Finally, this thesis investigates the use of machine learning techniques to predict the traffic behaviour of base stations; this will determine the sleep/wakeup schedule, thereby minimizing the power consumption while maintaining the QoS for each cellular user

Towards Efficient and Enhanced Wireless Coexistence in the Unlicensed Spectrum

The 3rd Generation Partnership Project (3GPP) is developing the fifth generation (5G) of wireless broadband technology and has identified the unlicensed spectrum as a principal item on the plan of action. Listen-Before-Talk (LBT) has been recognized as the starting development point for the channel access scheme of future 5G New Radio-Unlicensed (NR-U) networks. Recent technical reports suggest that all sub-7 GHz unlicensed spectrum is targeted for 5G NR-U operation, including the 2.4 GHz Industrial, Scientific, and Medical (ISM) band. Literature is inundated with research on Wi-Fi and LBT-based long-term evolution License-Assisted Access (LTE-LAA) wireless coexistence analysis. While a treasure trove of radio spectrum has been approved for license-exempt use in the 6 GHz band, industry and standard organizations must make sure it is well utilized by enhancing their coexistence schemes. A proper assessment of the homogeneous LBT deployment is imperative under the new use cases and regulatory circumstances. The work presented herein aimed to fill the gap and underline the importance of improving channel access mechanisms in next-generation wireless systems. The research in this dissertation first analyzed the LBT channel access scheme and analytically evaluated its performance in terms of a metrics set, such as effective channel utilization, collision probability, mean access delay, and temporal fairness among coexisting nodes. Outcomes of the developed analytical model revealed inefficiencies in various cases. For example, high priority classes generally hinder overall effective channel utilization, exhibit a high collision rate, and incur long latencies compared to lower priorities; and low priority classes sustain longer delays in class-heterogeneous scenarios. The developed framework was then utilized to investigate wireless coexistence in a 5G-enabled intensive care unit, employing remote patient monitoring over 5G NR-U. A modified LBT scheme is then proposed in this work to enhance overall channel efficiency in homogeneous LBT deployments by reducing the collision probability among coexisting stations based on the analytical investigation of the LBT mechanism. It is expected that low-power, narrowband frequency hoppers will be allowed to operate in the 6 GHz spectrum based on recent European Communications Committee (ECC) mandates, which raises speculation around coexistence with incumbent radio access technologies (RATs). To address the potential operation of cellular LBT in the 2.4 GHz and frequency hopping systems in the 5- and 6-GHz bands, the coexistence of Bluetooth Low Energy (BLE) 5 and LBT was investigated empirically in an anechoic chamber. The mutual impact was explored by means of throughput, packet error rate, and interframe delays. Empirical evaluation results demonstrated how BLE throughput dropped as the intended-to-unintended signal ratio decreased and the way in which LBT classes exhibited a diminishing effect as the class priority descended. Long Range BLE physical layer (PHY) was found to sustain longer gap times (i.e., delay) than the other two PHYs; however, the LR PHY showed less susceptibility to interference. Results also demonstrated that low data rate BLE PHYs hindered LBT throughput performance since they correspond to longer airtime durations

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)