Link Scheduling Algorithms For In-Band Full-Duplex Wireless Networks

In the last two decades, wireless networks and their corresponding data traffic have grown significantly. This is because wireless networks have become an indispens- able and critical communication infrastructure in a modern society. An on-going challenge in communication systems is meeting the continuous increase in traffic de- mands. This is driven by the proliferation of electronic devices such as smartphones with a WiFi interface along with their bandwidth intensive applications. Moreover, in the near future, sensor devices that form the Internet of Things (IoTs) ecosystem will also add to future traffic growth. One promising approach to meet growing traffic demands is to equip nodes with an In-band-Full-Duplex (IBFD) radio. This radio thus allows nodes to transmit and receive data concurrently over the same frequency band. Another approach to in- crease network or link capacity is to exploit the benefits of Multiple-Input-Multiple- Output (MIMO) technologies; namely, (i) spatial diversity gain, which improves Signal-to-Noise Ratio (SNR) and thus has a direct impact on the data rate used by nodes, and (ii) spatial multiplexing gain, whereby nodes are able to form concurrent links to neighbors

Low Complexity Scheduling and Coding for Wireless Networks

The advent of wireless communication technologies has created a paradigm shift in the accessibility of communication. With it has come an increased demand for throughput, a trend that is likely to increase further in the future. A key aspect of these challenges is to develop low complexity algorithms and architectures that can take advantage of the nature of the wireless medium like broadcasting and physical layer cooperation. In this thesis, we consider several problems in the domain of low complexity coding, relaying and scheduling for wireless networks. We formulate the Pliable Index Coding problem that models a server trying to send one or more new messages over a noiseless broadcast channel to a set of clients that already have a subset of messages as side information. We show through theoretical bounds and algorithms, that it is possible to design short length codes, poly-logarithmic in the number of clients, to solve this problem. The length of the codes are exponentially better than those possible in a traditional index coding setup. Next, we consider several aspects of low complexity relaying in half-duplex diamond networks. In such networks, the source transmits information to the destination through $n$ half-duplex intermediate relays arranged in a single layer. The half-duplex nature of the relays implies that they can either be in a listening or transmitting state at any point of time. To achieve high rates, there is an additional complexity of optimizing the schedule (i.e. the relative time fractions) of the relaying states, which can be $2^n$ in number. Using approximate capacity expressions derived from the quantize-map-forward scheme for physical layer cooperation, we show that for networks with $n\leq 6$ relays, the optimal schedule has atmost $n+1$ active states. This is an exponential improvement over the possible $2^n$ active states in a schedule. We also show that it is possible to achieve at least half the capacity of such networks (approximately) by employing simple routing strategies that use only two relays and two scheduling states. These results imply that the complexity of relaying in half-duplex diamond networks can be significantly reduced by using fewer scheduling states or fewer relays without adversely affecting throughput. Both these results assume centralized processing of the channel state information of all the relays. We take the first steps in analyzing the performance of relaying schemes where each relay switches between listening and transmitting states randomly and optimizes their relative fractions using only local channel state information. We show that even with such simple scheduling, we can achieve a significant fraction of the capacity of the network. Next, we look at the dual problem of selecting the subset of relays of a given size that has the highest capacity for a general layered full-duplex relay network. We formulate this as an optimization problem and derive efficient approximation algorithms to solve them. We end the thesis with the design and implementation of a practical relaying scheme called QUILT. In it the relay opportunistically decodes or quantizes its received signal and transmits the resulting sequence in cooperation with the source. To keep the complexity of the system low, we use LDPC codes at the source, interleaving at the relays and belief propagation decoding at the destination. We evaluate our system through testbed experiments over WiFi

Self managed Access Scheme for Demand Request in TDM TDMA Star Topology Network

In demand assignment protocol, resources are granted on the basis of demand, governing some rules, policies in resource assignment and after the completion of need, resources are released back to the central pool for further requests. In star topology TDM/TDMA network of VSATs, large number of participating terminals generate signaling packet on common demand request channel. It is desired that these signaling terminals to have higher chances of successful access to the media and at the same time with minimal number of collision over the shared channel. Under these circumstances, performance of media access protocol is really crucial. Aloha is the simplistic technique to access the shared channel but suffers from extremely low throughput. Its immediate successor slotted Aloha improves the throughput by cutting down the vulnerable period to half by agreeing on transmission at slot boundaries. This improvement is also not adequate to provide the better chances of packets getting through when multiple nodes are participating. The large latency network where one hop delay is of the order of 270ms, feedback time and timeouts are also of high order this further worsen the problem. In this paper, we propose self-managed access scheme for demand request that tries to reduce the collision by managing the multiple requests and distributing them over different slots