Browsing by Author "Lassila, Pasi, Docent, Aalto University, Finland"

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Forwarding Capacity in Large Wireless Multihop Networks - A Computational Approach
(2013) Nousiainen, Jarno
School of Electrical Engineering | Doctoral dissertation (article-based)
Wireless multihop networks are networks without any fixed infrastructure. This thesis concentrates on a network consisting of a plethora of immobile nodes communicating with each other over a shared wireless channel. The intrinsic nature of the shared wireless channel makes it difficult to efficiently avoid interference between the transmissions, and the exact capacity of such a network is in many respects an open question. At first, we characterize the capacity problem in a massively dense wireless network where a separation of scales emerges, and the problem can be separated into two different subproblems. The two subproblems loosely correspond to routing at the global scale and forwarding at the local scale. We focus on the latter one and study the microscopic level multidirectional forwarding capacity problem that considers an infinitely large network's capability to relay information. Because of the complexity of analyzing a large random network and wireless interference, the main approach is to construct algorithms that produce numerical bounds or estimates for the forwarding capacity, and simulate them for large network realizations. The methods used for studying the forwarding capacity are presented in two parts. The first part considers the instantaneous forwarding capacity. The instantaneous forwarding capacity can be achieved temporarily but cannot be maintained for a longer time period. It is a natural upper bound for the actual forwarding capacity and can be analyzed with more complex ways of modeling interference, such as the SINR-based models, in addition to the simple Boolean interference model. The actual forwarding capacity with multihop traffic under the Boolean interference model is considered in the second part. In this part, the upper bound provided by the instantaneous capacity is tightened for a small number of neighbor nodes, where it is less accurate. We also provide a lower bound that shows a notable improvement compared with previous results for uncoordinated opportunistic forwarding. Finally, an estimate is found for the forwarding capacity. The dependence of the estimate on the directional distribution of the traffic is studied to determine the possible gain from interleaving traffic in different directions compared with time sharing between the directions. Eventually, it is illustrated how the results for the forwarding capacity can be used with the macroscopic level results to obtain the total capacity of a large wireless network. The thesis hence makes it possible to calculate a numerical estimate for the total capacity.
Resource allocation in wireless access network : A queueing theoretic approach
(2016) Osti, Prajwal
School of Electrical Engineering | Doctoral dissertation (article-based)
To meet its performance targets, the future 5G networks need to greatly optimize the Radio Access Networks (RANs), which connect the end users to the core network. In this thesis, we develop mathematical models to study three aspects of the operation of the RAN in modern wireless systems. The models are analyzed using the techniques borrowed mainly from queueing theory and stochastic control. Also, simulations are extensively used to gain further insights. First, we provide a detailed Markov model of the random access process in LTE. From this, we observe that the bottleneck in the signaling channel causes congestion in the access when a large number of M2M devices attempt to enter the network. Then, in the context of the so-called Heterogeneous networks (HetNets), we suggest dynamic load balancing schemes that alleviate this congestion and reduce the overall access delay. We then use flow-level models for elastic data traffic to study the problem of coordinating the activities of the neighboring base stations. We seek to minimize the flow-level delay when there are various classes of users. We classify the users based on their locations, or, in dynamic TDD systems, on the direction of service the network is providing to them. Using interacting queues and different operating policies of running such queues, we study the amount of gain the dynamic policies can provide over the static probabilistic policies. Our results show that simple dynamic policies can provide very good performance in the cases considered. Finally, we consider the problem of opportunistically scheduling the flows of users with time-varying channels taking into account the size of data they need to transfer. Using flow-level models in a system with homogeneous channels, we provide the optimal scheduling policy when there are no new job arrivals. We also suggest the method to implement such a policy in a time-slotted system. With heterogeneous channels, the problem is intractable for the flow-level techniques. Therefore, we utilize the framework of the restless-multi-armed-bandit (RMAB) problems employing the so-called Whittle index approach. The Whittle index approach, by relaxing the scheduling constraints, makes the problem separable, and thereby provides an exact solution to the modified problem. Our simulations suggest that when this solution is applied as a heuristic to the original problem, it gives good performance, even with dynamic job arrivals.