Motivated by the aforementioned challenges and the research problem, we conduct an intensive and systematic research aiming to design energy-efficient and reliable com- munication protocols for WBANs. In this thesis, we focus on research problems of fun- damental and practical importance. Specifically, we address the following problems ranging from theoretical modeling and analysis to practical protocol design.
• Intra-WBAN interference mitigation and avoidance
• Cooperative Inter-WBAN interference mitigation and avoidance • Non-cooperative Inter-WBAN interference mitigation and avoidance • Interference mitigation and avoidance in WBANs with IoT
We provide the main contributions of our thesis in Chapter 3, 4, 5, and 6. The thesis is structured as follows:
• Chapter 2 – Background: in this chapter, we provide a brief survey of related prior work and conduct a comparative study of different interference mitigation and avoidance protocols for WBANs [11].
• Chapter 3 – Interference Mitigation in Multi-Hop WBANs: in this chapter, we address the problem of interference within a WBAN through dynamic time and spectrum allocation. Motivated by the benefits of two-hop communication, we firstly propose a time-based channel allocation mechanism, namely, CFTIM, that lowers the probability of interference within a WBAN. However, CFTIM incurs
additional energy consumption due to frequent channel hopping. Secondly, we propose another mechanism called IAA that dynamically adjusts the superframe length to lower the probability of interference and provides better scheduling of the medium access. IAA limits the number of channels to 2 to reduce the frequency of channel hopping and reduce the power consumption. We further analyze CFTIM and IAA and present a probabilistic model that proves the SINR outage proba- bility is reduced. Meantime, simulation results demonstrate the effectiveness and efficiency of CFTIM and IAA in terms of reducing the probability of interference, extending the network lifetime and improving the throughput [8,7,9,12].
• Chapter 4 – Cooperative Inter-WBAN Interference Mitigation Using Walsh-
Hadamard Codes: in this chapter, we address the problem of sensor-level co- channel interference among cooperative WBANs through orthogonal code allo- cation. Motivated by the distributed time provisioning supported in the IEEE 802.15.6 standard [2], we firstly propose a distributed time correlation reference scheme, namely, DTRC, that generates virtual time-based patterns to determine which superframes and which time-slots within those superframes interfere with each other. Secondly, we propose a cooperative code allocation scheme, namely, OCAIM, where each WBAN generates sensor interference lists and then all sensors belonging to these lists are allocated orthogonal codes to avoid the interference. Mathematically, we further analyze OCAIM and present a model that derives the success and collision probability for frames transmissions. Extensive simulations are conducted and results demonstrate that OCAIM can significantly diminish the inter-WBAN interference, improves the throughput and saves the power resource of the WBANs [6].
• Chapter 5 - Non-Cooperative Inter-WBAN Interference Mitigation Using Latin
Rectangles: in this chapter, we address the problem of sensor-level co-channel interference among non-cooperative WBANs through time-slot and channel hop- ping. Motivated by the availability of multiple channels in the license-free 2.4 GHz ISM band of the IEEE 802.15.6 standard, we firstly propose a distributed time- based channel hopping mechanism, namely, DAIL, for sensor-level interference avoidance among WBANs based on Latin rectangles. DAIL allocates channel-and- time-slot combination to sensors to lower the probability of inter-WBAN interfer- ence while enabling autonomous scheduling of the medium access within each WBAN. However, DAIL incurs additional energy consumption and delay due to
frequent channel hopping. To resolve the problem, we propose another scheme, namely, CHIM, that allocates a random channel to each WBAN and provisions backup time-slots for failed transmission. Like DAIL, CHIM generates a pre- dictable interference-free transmission schedule for all sensors within a WBAN based on Latin rectangles. Basically, CHIM enables only a sensor that experiences interference to hop to an alternative backup channel in its allocated backup time- slot. Furthermore, we develop an analytical model that derives bounds on the collision probability and throughput for sensors transmissions. Extensive and in- tensive simulation results demonstrate the effectiveness and efficiency of DAIL and CHIM in terms of collision probability, network energy lifetime, network through- put, transmission delay, and reliability [4,5,10].
• Chapter 6 – Interference Mitigation in WBANs with IoT: Motivated by the emer- gence of Bluetooth Low Energy (BLE) technology, we propose a distributed pro- tocol, namely, CSIM, to facilitate the interference detection and mitigation and enable WBAN operation and interaction within an existing IoT. We integrate a BLE transceiver and a Cognitive Radio (CR) module within each WBAN’s Crd for se- lecting an Interference Mitigation Channel (IMC) for its WBAN. To mitigate the interference, CSIM opts to extend the active period of the superframe to involve not only a TDMA frame, but also a Flexible Channel Selection (FCS) and a Flexible Backup TDMA (FBTDMA) frames. Basically, CSIM enables each WBAN’s sensor that experiences interference on default channel within the TDMA frame to even- tually switch to an IMC for successful data transmission. In essence, all interfering sensor nodes within the same WBAN will use the same IMC, each in its allo- cated backup time-slot within FBTDMA frame. The simulation results show that CSIM mitigates the interference, saves the power resource at both the sensor- and coordinator-levels [3].
• Chapter 7 – Conclusions: finally, we complete our thesis with conclusions that summarize the main contributions of our thesis and provide different directions for future research.
Related Works
Contents2.1 Resource Allocation . . . . 18
2.1.1 Channel Assignment . . . 19
2.1.2 Transmission Scheduling . . . 20
2.1.3 Combined Channel and Time Allocation . . . 20
2.1.4 Summary . . . 21