# Optimized Gateway Placement for Interference Cancellation in Transmit-Only LPWA Networks
## 1 Introduction
Furthermore, we assume there are many more SNs than GWs, which makes packet collisions likely. For example, the topology of Figure 1 can represent quasi-stationary sensors used for monitoring and detection. The sensors may turn on receivers only to use GPS to determine their location, but turn off their receivers to save energy while they are stationary. If the device does not need to know its own location, the power consuming GPS chip can even be replaced by LPWAN localization algorithms based on signal strengths to base stations, such as fingerprinting and ranging. While stationary, the sensors can still make periodic reports of the monitored quantities or detected events. For example, the sensors could be on cars in a large dealership lot and report disturbances to the car. The locations of GWs are required to be strategically designed to maximize the chance of successful packet decoding, even if the packet suffers from a two-way collision. The direct motivation  
Figure 1: The network topology of the TO LPWAN. of this paper is coming from the Ph.D dissertation [8] of [PERSON], who aimed to maximize packet deliver ratio (PDR) of TO transmitters by optimizing the GW locations based on the capture effect in two-way collisions only. However, [PERSON] [8] disregarded the IC function, i.e., only one packet can be captured and decoded when two packets are in collision following the algorithm of F-Embed in [8]. In contrast, with capture and IC, both collision packets can be decoded. This paper provides two algorithms to optimize GW locations for the TO LPWA network to minimize the average contention number, which is inversely proportional to PDR, when other factors are the same [8]. Network planning and optimization is a very active research area with a considerable amount of published work in many types of wireless communication systems. In [15], the optimal base station placement is obtained based on minimizing the sum of the ratio of the interference power to the signal power for all interesting points in the downlink for planning of a cellular network. To optimize average capacities of collaborated MIMO and distributed MIMO, the authors of [16] employed the waveguide-multimode model and particle-swarm-optimization method. It obtained that distributed MIMO systems show desirable performance while significantly outperforming collaborated MIMO configurations. The authors of [17] proposed an algorithm specifically for LTE mixed-cell MIMO wireless systems, following a combinatorial approach and the optimization analysis based on the triplet of coverage, capacity and cost. In the research on the construction of WiMAX network, the authors of [18] transformed the relay station (RS) placement problem into a 0-1 binary programming problem in a two-hop IEEE802.16j network to maximize throughput. In the problem with huge input size, to find the sub-optimal solution, this paper proposes an efficient near-optimal placement solution for IEEE 802.16j WiMAX networks. Extending the work in [18; 19] combining the condition of whether a subscriber station needs the relays, a model of three-hop IEEE802.16j network about station placement is proposed by limiting the placement location of RS. In common wireless sensor networks (WSN), the designing and optimizing network structure is mainly focused on the cluster topology control and cluster head selection (e.g., [20; 21; 22]). Besides that, the authors of [23] focused on the topology control process for application nodes (ANs) and base stations (BSs), which constitutes the upper tier of two-tiered WSN. By proposing algorithmic approaches to place BSs optimally, the topological network lifetime of WSNs can be maximized deterministically, even when the initial energy provisioning for ANs is no longer always proportional to their average bit-stream rate. The obtained optimal BS locations are under different lifetime definitions according to the mission criticality of WSN.