Analysis of Dynamic Channel Bonding in Dense Networks of WLANs

Dynamic Channel Bonding (DCB) allows for the dynamic selection and use of multiple contiguous basic channels in Wireless Local Area Networks (WLANs). A WLAN operating under DCB can enjoy a larger bandwidth, when available, and therefore achieve a higher throughput. However, the use of larger bandwidths also increases the contention with adjacent WLANs, which can result in longer delays in accessing the channel and consequently, a lower throughput. In this paper, a scenario consisting of multiple WLANs using DCB and operating within carrier-sensing range of one another is considered. An analytical framework for evaluating the performance of such networks is presented. The analysis is carried out using a Markov chain model that characterizes the interactions between adjacent WLANs with overlapping channels. An algorithm is proposed for systematically constructing the Markov chain corresponding to any given scenario. The analytical model is then used to highlight and explain the key properties that differentiate DCB networks of WLANs from those operating on a single shared channel. Furthermore, the analysis is applied to networks of IEEE 802.11ac WLANs operating under DCB-which do not fully comply with some of the simplifying assumptions in our analysis-to show that the analytical model can give accurate results in more realistic scenarios

Enhanced Collision Resolution for the IEEE 802.11 Distributed Coordination Function

The IEEE 802.11 standard relies on the Distributed Coordination Function (DCF) as the fundamental medium access control method. DCF uses the Binary Exponential Backoff (BEB) algorithm to regulate channel access. The backoff period determined by BEB depends on a contention window (CW) whose size is doubled if a station suffers a collision and reset to its minimum value after a successful transmission. BEB doubles the CW size upon collision to reduce the collision probability in retransmission. However, this CW increase reduces channel access time because stations will spend more time sensing the channel rather than accessing it. Although resetting the CW to its minimum value increases channel access, it negatively affects fairness because it favours successfully transmitting stations over stations suffering from collisions. Moreover, resetting CW leads to increasing the collision probability and therefore increases the number of collisions. % Quality control editor: Please ensure that the intended meaning has been maintained in the edits of the previous sentence. Since increasing channel access time and reducing the probability of collisions are important factors to improve the DCF performance, and they conflict with each other, improving one will have an adverse effect on the other and consequently will harm the DCF performance. We propose an algorithm, \gls{ECRA}, that solves collisions once they occur without instantly increasing the CW size. Our algorithm reduces the collision probability without affecting channel access time. We also propose an accurate analytical model that allows comparing the theoretical saturation and maximum throughputs of our algorithm with those of benchmark algorithms. Our model uses a collision probability that is dependent on the station transmission history and thus provides a precise estimation of the probability that a station transmits in a random timeslot, which results in a more accurate throughput analysis. We present extensive simulations for fixed and mobile scenarios. The results show that on average, our algorithm outperformed BEB in terms of throughput and fairness. Compared to other benchmark algorithms, our algorithm improved, on average, throughput and delay performance

Tiheiden Wi-Fi verkkojen optimointi Markov-ketjumallien ja simuloidun jäähdytyksen avulla

Currently, the demand for wireless communication capacity is rising rapidly due to challenging applications such as video streaming and the emerging Internet of things. In meeting these ambitious requirements, the most important factor is predicted to be network densification, which refers to increasing the geographical density of simultaneously communicating devices. A natural choice for implementing dense networks is the wireless local area network technology Wi-Fi, characterized by being cheap and easy to deploy. Network density aggravates the harmful effects of interference and causes scarcity of free transmission bandwidth. To counter this, dense networks need radio resource management algorithms. This thesis presents a Wi-Fi radio resource management algorithm, which jointly optimizes access point channels, user association and transmission power. It estimates future throughput using a continuous time Markov chain based model, and finds solutions maximizing this estimate via a discrete search metaheuristic called simulated annealing. The algorithm is validated through a wide range of simulations where for instance network density is varied. The algorithm is found to be highly versatile, yielding good performance in all scenarios. Moreover, the general design approach places few restrictions on further algorithm improvement and extension. Markov chain modeling, although accurate in an idealized setting, turns out to be inaccurate with real-world Wi-Fi, with a simpler model offering similar accuracy but lighter computational load.Nykyisin vaatimukset langattoman tiedonsiirron kapasiteetille ovat voimakkaassa kasvussa johtuen haastavista sovelluksista kuten videon suoratoistosta ja tulossa olevasta esineiden Internetistä. Näiden vaatimusten täyttämiseksi tärkein keino on langattomien tiedonsiirtoverkkojen tihentäminen, mikä tarkoittaa yht’aikaa samalla maantieteellisellä alueella kommunikoivien laitteiden määrän kasvattamista. Luonnollinen valinta tiheiden verkkojen toteuttamiseen on langattomien lähiverkkojen teknologia Wi-Fi, jonka etuja ovat edullisuus ja asennuksen helppous. Langattoman verkon tiheys lisää haitallista interferenssiä ja aikaansaa pulaa vapaista lähetystaajuuksista. Näiden ongelmien ratkaisemiseksi tarvitaan radioresurssien hallinta-algoritmeja. Tässä työssä suunnitellaan Wi-Fiä varten radioresurssien hallinta-algoritmi, joka optimoi samanaikaisesti tukiasemien kanavia, käyttäjien allokaatiota tukiasemille sekä lähetystehoja. Se estimoi tulevia tiedonsiirtonopeuksia jatkuvan ajan Markov-ketjuihin pohjautuvan mallin avulla ja löytää tämän estimaatin maksimoivia ratkaisuja hyödyntämällä diskreettiä hakumenetelmää nimeltä simuloitu jäähdytys. Algoritmi validoidaan käyttäen monipuolista joukkoa simulaatioita, jossa vaihtelee esimerkiksi verkon tiheys. Algoritmi osoittautuu erittäin monipuoliseksi, sillä sen suorituskyky on hyvä kaikissa simulaatioskenaarioissa. Käytetyn lähestymistavan etuna on myös se, että se asettaa varsin vähän rajoituksia algoritmin jatkokehitykselle. Markov-ketjumallit osoittautuvat todellisen Wi-Fin tapauksessa epätarkoiksi, vaikka ne idealisoidussa ympäristössä ovatkin tarkkoja. Käy ilmi, että yksinkertaisemmalla mallilla saadaan vastaava tarkkuus, mutta laskentatehoa tarvitaan vähemmän

Throughput Analysis of IEEE 802.11bn Coordinated Spatial Reuse

Multi-Access Point Coordination (MAPC) is becoming the cornerstone of the IEEE 802.11bn amendment, alias Wi-Fi 8. Among the MAPC features, Coordinated Spatial Reuse (C-SR) stands as one of the most appealing due to its capability to orchestrate simultaneous access point transmissions at a low implementation complexity. In this paper, we contribute to the understanding of C-SR by introducing an analytical model based on Continuous Time Markov Chains (CTMCs) to characterize its throughput and spatial efficiency. Applying the proposed model to several network topologies, we show that C-SR opportunistically enables parallel high-quality transmissions and yields an average throughput gain of up to 59% in comparison to the legacy 802.11 Distributed Coordination Function (DCF) and up to 42% when compared to the 802.11ax Overlapping Basic Service Set Packet Detect (OBSS/PD) mechanism

Enabling Techniques Design for QoS Provision in Wireless Communications

Guaranteeing Quality of Service (QoS) has become a recognized feature in the design of wireless communications. In this thesis, the problem of QoS provision is addressed from different prospectives in several modern communication systems. In the first part of the thesis, a wireless communication system with the base station (BS) associated by multiple subscribers (SS) is considered, where different subscribers require different QoS. Using the cross-layer approach, the conventional single queue finite state Markov chain system model is extended to multiple queues\u27 scenario by combining the MAC layer queue status with the physical layer channel states, modeled by finite state Markov channel (FSMC). To provide the diverse QoS to different subscribers, a priority-based rate allocation (PRA) algorithm is proposed to allocate the physical layer transmission rate to the multiple medium access control (MAC) layer queues, where different queues are assigned with different priorities, leading to their different QoS performance and thus, the diverse QoS are guaranteed. Then, the subcarrier allocation in multi-user OFDM (MU-OFDM) systems is stuied, constrained by the MAC layer diverse QoS requirements. A two-step cross-layer dynamic subcarrier allocation algorithm is proposed where the MAC layer queue status is firstly modeled by a finite state Markov chain, using which MAC layer diverse QoS constraints are transformed to the corresponding minimum physical layer data rate of each user. Then, with the purpose of maximizing the system capacity, the physical layer OFDM subcarriers are allocated to the multiple users to satisfy their minimum data rate requirements, which is derived by the MAC layer queue status model. Finally, the problem of channel assignment in IEEE 802.11 wireless local area networks (WLAN) is investigated, oriented by users\u27 QoS requirements. The number of users in the IEEE 802.11 channels is first determined through the number of different channel impulse responses (CIR) estimated at physical layer. This information is involved thereafter in the proposed channel assignment algorithm, which aims at maximum system throughput, where we explore the partially overlapped IEEE 802.11 channels to provide additional frequency resources. Moreover, the users\u27 QoS requirements are set to trigger the channel assignment process, such that the system can constantly maintain the required QoS