Optimising lower layers of the protocol stack to improve communication performance in a wireless temperature sensor network

The function of wireless sensor networks is to monitor events or gather information and report the information to a sink node, a central location or a base station. It is a requirement that the information is transmitted through the network efficiently. Wireless communication is the main activity that consumes energy in wireless sensor networks through idle listening, overhearing, interference and collision. It becomes essential to limit energy usage while maintaining communication between the sensor nodes and the sink node as the nodes die after the battery has been exhausted. Thus, conserving energy in a wireless sensor network is of utmost importance. Numerous methods to decrease energy expenditure and extend the lifetime of the network have been proposed. Researchers have devised methods to efficiently utilise the limited energy available for wireless sensor networks by optimising the design parameters and protocols. Cross-layer optimisation is an approach that has been employed to improve wireless communication. The essence of cross-layer scheme is to optimise the exchange and control of data between two or more layers to improve efficiency. The number of transmissions is therefore a vital element in evaluating overall energy usage. In this dissertation, a Markov Chain model was employed to analyse the tuning of two layers of the protocol stack, namely the Physical Layer (PHY) and Media Access Control layer (MAC), to find possible energy gains. The study was conducted utilising the IEEE 802.11 channel, SensorMAC (SMAC) and Slotted-Aloha (S-Aloha) medium access protocols in a star topology Wireless Temperature Sensor Network (WTSN). The research explored the prospective energy gains that could be realised through optimizing the Forward Error Correction (FEC) rate. Different Reed Solomon codes were analysed to explore the effect of protocol tuning on energy efficiency, namely transmission power, modulation method, and channel access. The case where no FEC code was used and analysed as the control condition. A MATLAB simulation model was used to identify the statistics of collisions, overall packets transmitted, as well as the total number of slots used during the transmission phase. The bit error probability results computed analytically were utilised in the simulation model to measure the probability of successful transmitting data in the physical layer. The analytical values and the simulation results were compared to corroborate the correctness of the models. The results indicate that energy gains can be accomplished by the suggested layer tuning approach.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

On Coding for Reliable Communication over Packet Networks

We present a capacity-achieving coding scheme for unicast or multicast over lossy packet networks. In the scheme, intermediate nodes perform additional coding yet do not decode nor even wait for a block of packets before sending out coded packets. Rather, whenever they have a transmission opportunity, they send out coded packets formed from random linear combinations of previously received packets. All coding and decoding operations have polynomial complexity. We show that the scheme is capacity-achieving as long as packets received on a link arrive according to a process that has an average rate. Thus, packet losses on a link may exhibit correlation in time or with losses on other links. In the special case of Poisson traffic with i.i.d. losses, we give error exponents that quantify the rate of decay of the probability of error with coding delay. Our analysis of the scheme shows that it is not only capacity-achieving, but that the propagation of packets carrying "innovative" information follows the propagation of jobs through a queueing network, and therefore fluid flow models yield good approximations. We consider networks with both lossy point-to-point and broadcast links, allowing us to model both wireline and wireless packet networks.Comment: 33 pages, 6 figures; revised appendi

Permutation Trellis Coded Multi-level FSK Signaling to Mitigate Primary User Interference in Cognitive Radio Networks

We employ Permutation Trellis Code (PTC) based multi-level Frequency Shift Keying signaling to mitigate the impact of Primary Users (PUs) on the performance of Secondary Users (SUs) in Cognitive Radio Networks (CRNs). The PUs are assumed to be dynamic in that they appear intermittently and stay active for an unknown duration. Our approach is based on the use of PTC combined with multi-level FSK modulation so that an SU can improve its data rate by increasing its transmission bandwidth while operating at low power and not creating destructive interference for PUs. We evaluate system performance by obtaining an approximation for the actual Bit Error Rate (BER) using properties of the Viterbi decoder and carry out a thorough performance analysis in terms of BER and throughput. The results show that the proposed coded system achieves i) robustness by ensuring that SUs have stable throughput in the presence of heavy PU interference and ii) improved resiliency of SU links to interference in the presence of multiple dynamic PUs.Comment: 30 pages, 12 figure

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

Network coding aware queue management in multi-rate wireless networks

In this thesis we focus on network coding for unicast flows, in particular we take into consideration the COPE architecture. We study what happens when two nodes transmit with different rates and we propose a Markov chain to model this scenario. Furthermore, we propose a queue management algorithm to increase the coding opportunity and the throughput of the network. In COPE, a node codes two or more packets together when packets are headed to different nexthops. When there are just packets for the same nexthop, a node loses a coding opportunity. The queue management algorithm increases the coding opportunity prioritizing the channel access of sender nodes based on the queue information and on PER of the links. We simulate this algorithm on top of COPE in a multi rate scenario with NS 2 and we show that our algorithm yields throughput gains of up to 57\% compared to COP

KALOHA: ike i ke ALOHA

A new family of channel-access schemes  called KALOHA  (for ``Knowledge in ALOHA") is introduced.  KALOHA consists of modifying the pure ALOHA  protocol  by  endowing nodes with knowledge regarding the local times when packets  and acknowledgments are received,  and sharing  estimates of channel utilization at the medium access control (MAC) layer. The only physical-layer feedback needed   in KALOHA is the reception of  correct data packets and their ACKs. A  simple Markov-chain model is used  to  compare the throughput of KALOHA with ALOHA and slotted ALOHA. The analysis takes into account the amount of knowledge that nodes have and  the  effect of  acknowledgments and turnaround latencies.  The results  demonstrate the  benefits  derived from using  and sharing knowledge of channel utilization at the MAC layer.  KALOHA is more stable  than ALOHA and attains  more than double  the throughput of  ALOHA,  without the need for carrier sensing, requiring time slotting at the physical layer, or using other physical-layer mechanisms