Cross-layer design and optimization of medium access control protocols for wlans

This thesis provides a contribution to the field of Medium Access Control (MAC) layer protocol design for wireless networks by proposing and evaluating mechanisms that enhance different aspects of the network performance. These enhancements are achieved through the exchange of information between different layers of the traditional protocol stack, a concept known as Cross-Layer (CL) design. The main thesis contributions are divided into two parts. The first part of the thesis introduces a novel MAC layer protocol named Distributed Queuing Collision Avoidance (DQCA). DQCA behaves as a reservation scheme that ensures collision-free data transmissions at the majority of the time and switches automatically to an Aloha-like random access mechanism when the traffic load is low. DQCA can be enriched by more advanced scheduling algorithms based on a CL dialogue between the MAC and other protocol layers, to provide higher throughput and Quality of Service (QoS) guarantees. The second part of the thesis explores a different challenge in MAC layer design, related to the ability of multiple antenna systems to offer point-to-multipoint communications. Some modifications to the recently approved IEEE 802.11n standard are proposed in order to handle simultaneous multiuser downlink transmissions. A number of multiuser MAC schemes that handle channel access and scheduling issues and provide mechanisms for feedback acquisition have been presented and evaluated. The obtained performance enhancements have been demonstrated with the help of both theoretical analysis and simulation obtained results

Future Wireless Networks: Towards Learning-driven Sixth-generation Wireless Communications

The evolution of wireless communication networks, from present to the emerging fifth-generation (5G) new radio (NR), and sixth-generation (6G) is inevitable, yet propitious. The thesis evolves around application of machine learning and optimization techniques to problems in spectrum management, internet-of-things (IoT), physical layer security, and intelligent reflecting surface (IRS). The first problem explores License Assisted Access (LAA), which leverages unlicensed resource sharing with the Wi-Fi network as a promising technique to address the spectrum scarcity issue in wireless networks. An optimal communication policy is devised which maximizes the throughput performance of LAA network while guaranteeing a proportionally fair performance among LAA stations and a fair share for Wi-Fi stations. The numerical results demonstrate more than 75 % improvement in the LAA throughput and a notable gain of 8-9 % in the fairness index. Next, we investigate the unlicensed spectrum sharing for bandwidth hungry diverse IoT networks in 5G NR. An efficient coexistence mechanism based on the idea of adaptive initial sensing duration (ISD) is proposed to enhance the diverse IoT-NR network performance while keeping the primary Wi-Fi network's performance to a bearable threshold. A Q-learning (QL) based algorithm is devised to maximize the normalized sum throughput of the coexistence Wi-Fi/IoT-NR network. The results confirm a maximum throughput gain of 51 % and ensure that the Wi-Fi network's performance remains intact. Finally, advanced levels of network security are critical to maintain due to severe signal attenuation at higher frequencies of 6G wireless communication. Thus, an IRS-based model is proposed to address the issue of network security under trusted-untrusted device diversity, where the untrusted devices may potentially eavesdrop on the trusted devices. A deep deterministic policy gradient (DDPG) algorithm is devised to jointly optimize the active and passive beamforming matrices. The results confirm a maximum gain of 2-2.5 times in the sum secrecy rate of trusted devices and ensure Quality-of-Service (QoS) for all the devices. In conclusion, the thesis has led towards efficient, secure, and smart communication and build foundation to address similar complex wireless networks

A Framework for Service Differentiation and Optimization in Multi-hop Wireless Networks

In resource-constrained networks such as multi-hop wireless networks (MHWNs), service differentiation algorithms designed to address end users' interests (e.g. user satisfaction, QoS, etc.) should also consider efficient utilization of the scarce network resources in order to maximize the network's interests (e.g. revenue). For this very reason, service differentiation in MHWNs is quite different from the wired network scenario. We propose a service differentiation tool called the ``Investment Function'', which essentially captures the network's cumulative resource investment in a given packet at a given time. This investment value can be used by the network algorithm to implement specific service differentiation principles. As proof-of-concept, we use the investment function to improve fairness among simultaneous flows that traverse varying number of hops in a MHWN (multihop flow fairness). However, to attain the optimal value of a specific service differentiation objective, optimal service differentiation and investment function parameters may need to be computed. The optimal parameters can be computed by casting the service differentiation problem as a network flow problem in MHWNs, with the goal of optimizing the service differentiation objective. The capacity constraints for these problems require knowledge of the adjacent-node interference values, and constructing these constraints could be very expensive based on the transmission scheduling scheme used. As a result, even formulating the optimization problem may take unacceptable computational effort or memory or both. Under optimal scheduling, the adjacent node interference values (and thus the capacity constraints) are not only very expensive to compute, but also cannot be expressed in polynomial form. Therefore, existing optimization techniques cannot be directly applied to solve optimization problems in MHWNs. To develop an efficient optimization framework, we first model the MHWN as a Unit Disk Graph (UDG). The optimal transmission schedule in the MHWN is related to the chromatic number of the UDG, which is very expensive to compute. However, the clique number, which is a lower bound on the chromatic number, can be computed in polynomial time in UDGs. Through an empirical study, we obtain tighter bounds on the ratio of the chromatic number to clique number in UDGs, which enables us to leverage existing polynomial time clique-discovery algorithms to compute very close approximations to the chromatic number value. This approximation not only allows us to quickly formulate the capacity constraints in polynomial form, but also allows us to significantly deviate from the traditional approach of discovering all or most of the constraints \textit{a priori}; instead, we can discover the constraints as needed. We have integrated this approach of constraint-discovery into an active-set optimization algorithm (Gradient Projection method) to solve network flow problems in multi-hop wireless networks. Our results show significant memory and computational savings when compared to existing methods

ORLA/OLAA: Orthogonal Coexistence of LAA and WiFi in Unlicensed Spectrum

Future mobile networks will exploit unlicensed spectrum to boost capacity and meet growing user demands cost-effectively. The 3rd Generation Partnership Project (3GPP) has recently defined a License Assisted Access (LAA) scheme to enable global Unlicensed LTE (U-LTE) deployment, aiming at 1) ensuring fair coexistence with incumbent WiFi networks, i.e., impacting on their performance no more than another WiFi device; and 2) achieving superior airtime efficiency as compared with WiFi. We show the standardized LAA fails to simultaneously fulfill these objectives, and design an alternative orthogonal (collision-free) listen-before-talk coexistence paradigm that provides a substantial improvement in performance, yet imposes no penalty on existing WiFi networks. We derive two optimal transmission policies, ORLA and OLAA, that maximize LAA throughput in both asynchronous and synchronous (i.e., with alignment to licensed anchor frame boundaries) modes of operation, respectively. We present a comprehensive evaluation through which we demonstrate that, when aggregating packets, IEEE 802.11ac WiFi can be more efficient than LAA, whereas our proposals attains 100% higher throughput, without harming WiFi. We further show that long U-LTE frames incur up to 92% throughput losses on WiFi when using 3GPP LAA, whilst ORLA/OLAA sustain >200% gains at no cost, even in the presence of non-saturated WiFi and/or in multi-rate scenarios.This work was supported in part by the EC H2020 5G-Transformer Project under Grant 761536

Flexible Spectrum Assignment for Local Wireless Networks

In this dissertation, we consider the problem of assigning spectrum to wireless local-area networks (WLANs). In line with recent IEEE 802.11 amendments and newer hardware capabilities, we consider situations where wireless nodes have the ability to adapt not only their channel center-frequency but also their channel width. This capability brings an important additional degree of freedom, which adds more granularity and potentially enables more efficient spectrum assignments. However, it also comes with new challenges; when consuming a varying amount of spectrum, the nodes should not only seek to reduce interference, but they should also seek to efficiently fill the available spectrum. Furthermore, the performances obtained in practice are especially difficult to predict when nodes employ variable bandwidths. We first propose an algorithm that acts in a decentralized way, with no communication among the neighboring access points (APs). Despite being decentralized, this algorithm is self-organizing and solves an explicit tradeoff between interference mitigation and efficient spectrum usage. In order for the APs to continuously adapt their spectrum to neighboring conditions while using only one network interface, this algorithm relies on a new kind of measurement, during which the APs monitor their surrounding networks for short durations. We implement this algorithm on a testbed and observe drastic performance gains compared to default spectrum assignments, or compared to efficient assignments using a fixed channel width. Next, we propose a procedure to explicitly predict the performance achievable in practice, when nodes operate with arbitrary spectrum configurations, traffic intensities, transmit powers, etc. This problem is notoriously difficult, as it requires capturing several complex interactions that take place at the MAC and PHY layers. Rather than trying to find an explicit model acting at this level of generality, we explore a different point in the design space. Using a limited number of real-world measurements, we use supervised machine-learning techniques to learn implicit performance models. We observe that these models largely outperform other measurement-based models based on SINR, and that they perform well, even when they are used to predict performance in contexts very different from the context prevailing during the initial set of measurements used for learning. We then build a second algorithm that uses the above-mentioned learned models to assign the spectrum. This algorithm is distributed and collaborative, meaning that neighboring APs have to exchange a limited amount of control traffic. It is also utility-optimal -- a feature enabled both by the presence of a model for predicting performance and the ability of APs to collaboratively take decisions. We implement this algorithm on a testbed, and we design a simple scheme that enables neighboring APs to discover themselves and to implement collaboration using their wired backbone network. We observe that it is possible to effectively gear the performance obtained in practice towards different objectives (in terms of efficiency and/or fairness), depending on the utility functions optimized by the nodes. Finally, we study the problem of scheduling packets both in time and frequency domains. Such ways of scheduling packets have been made possible by recent progress in system design, which make it possible to dynamically tune and negotiate the spectrum band [...

Design and Analysis of Medium Access Control Protocols for Broadband Wireless Networks

The next-generation wireless networks are expected to integrate diverse network architectures and various wireless access technologies to provide a robust solution for ubiquitous broadband wireless access, such as wireless local area networks (WLANs), Ultra-Wideband (UWB), and millimeter-wave (mmWave) based wireless personal area networks (WPANs), etc. To enhance the spectral efficiency and link reliability, smart antenna systems have been proposed as a promising candidate for future broadband access networks. To effectively exploit the increased capabilities of the emerging wireless networks, the different network characteristics and the underlying physical layer features need to be considered in the medium access control (MAC) design, which plays a critical role in providing efficient and fair resource sharing among multiple users. In this thesis, we comprehensively investigate the MAC design in both single- and multi-hop broadband wireless networks, with and without infrastructure support. We first develop mathematical models to identify the performance bottlenecks and constraints in the design and operation of existing MAC. We then use a cross-layer approach to mitigate the identified bottleneck problems. Finally, by evaluating the performance of the proposed protocols with analytical models and extensive simulations, we determine the optimal protocol parameters to maximize the network performance. In specific, a generic analytical framework is developed for capacity study of an IEEE 802.11 WLAN in support of non-persistent asymmetric traffic flows. The analysis can be applied for effective admission control to guarantee the quality of service (QoS) performance of multimedia applications. As the access point (AP) becomes the bottleneck in an infrastructure based WLAN, we explore the multiple-input multiple-output (MIMO) capability in the future IEEE 802.11n WLANs and propose a MIMO-aware multi-user (MU) MAC. By exploiting the multi-user degree of freedom in a MIMO system to allow the AP to communicate with multiple users in the downlink simultaneously, the proposed MU MAC can minimize the AP-bottleneck effect and significantly improve the network capacity. Other enhanced MAC mechanisms, e.g., frame aggregation and bidirectional transmissions, are also studied. Furthermore, different from a narrowband system where simultaneous transmissions by nearby neighbors collide with each other, wideband system can support multiple concurrent transmissions if the multi-user interference can be properly managed. Taking advantage of the salient features of UWB and mmWave communications, we propose an exclusive region (ER) based MAC protocol to exploit the spatial multiplexing gain of centralized UWB and mmWave based wireless networks. Moreover, instead of studying the asymptotic capacity bounds of arbitrary networks which may be too loose to be useful in realistic networks, we derive the expected capacity or transport capacity of UWB and mmWave based networks with random topology. The analysis reveals the main factors affecting the network (transport) capacity, and how to determine the best protocol parameters to maximize the network capacity. In addition, due to limited transmission range, multi-hop relay is necessary to extend the communication coverage of UWB networks. A simple, scalable, and distributed UWB MAC protocol is crucial for efficiently utilizing the large bandwidth of UWB channels and enabling numerous new applications cost-effectively. To address this issue, we further design a distributed asynchronous ER based MAC for multi-hop UWB networks and derive the optimal ER size towards the maximum network throughput. The proposed MAC can significantly improve both network throughput and fairness performance, while the throughput and fairness are usually treated as a tradeoff in other MAC protocols