Optimal location of the base station based on measured interference power
27 Jul 2015-pp 1-3
TL;DR: Based on the measured interference power, the optimal location of the base station is obtained by minimizing the sum of the ratio of the interference power to the signal power for all interesting points in the downlink.
Abstract: Based on the measured interference power, the optimal location of the base station is obtained by minimizing the sum of the ratio of the interference power to the signal power for all interesting points in the downlink. Especially, a closed-form solution is derived when the path loss exponent is 2. The results show that the optimal base station location is closer to the major interference area.
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TL;DR: Simulation results show that the gateway placements by the proposed algorithms achieve lower average contention, which means higher packet delivery ratio in the same conditions, than when gateways are naively placed, for several area distributions of sensors.
Abstract: We study the placement of gateways in a low-power wide-area sensor network, when the gateways perform interference cancellation and when the model of the residual error of interference cancellation is proportional to the power of the packet being canceled. For the case of two sensor nodes sending packets that collide, by which we mean overlap in time, we deduce a symmetric two-crescent region wherein a gateway can decode both collided packets. For a large network of many sensors and multiple gateways, we propose two greedy algorithms to optimize the locations of the gateways. Simulation results show that the gateway placements by our algorithms achieve lower average contention, which means higher packet delivery ratio in the same conditions, than when gateways are naively placed, for several area distributions of sensors.
20 citations
TL;DR: The simulation results show that the method proposed in this paper can optimize the performance of the secondary system while guaranteeing the priority of the primary user, and it is superior to several advanced algorithms.
Abstract: Aiming at the problem that the location of the secondary base station affects the interference between the primary and secondary systems directly and the reasonable allocation of channel resources, an Internet of Things (IoT) sensor network resource allocation scheme using an improved chaotic firefly algorithm is proposed. This solution builds a multi-objective optimization model based on interference analysis of the working scenario of the cognitive radio. The goal is to protect the primary user’s normal activity to maximize the throughput of the secondary system and maximize the number of users that can be covered by the secondary base station. Because the multi-objective model is a non-linear convex optimization problem, the paper uses an improved chaotic firefly algorithm to solve it. Chaos algorithm is introduced into the firefly algorithm. By perturbing individuals, the convergence speed is accelerated and the probability of local optimization is reduced. The algorithm can efficiently obtain the optimal solution while reducing the complexity of the problem. The simulation results show that the method proposed in this paper can optimize the performance of the secondary system while guaranteeing the priority of the primary user. And it is superior to several advanced algorithms.
18 citations
TL;DR: A novel method for IoT sensor networks is proposed to obtain the optimal positions of secondary information gathering stations (SIGSs) and to select the optimal operating channel and an appearance probability matrix for secondary IoT devices (SIDs) to maximize the supportable number of SIDs that can be installed in a car, in wearable devices, or for other monitoring devices, based on optimal deployment and probability.
Abstract: The Internet of Things (IoT) is the interconnection of different objects through the internet using different communication technologies. The objects are equipped with sensors and communications modules. The cognitive radio network is a key technique for the IoT and can effectively address spectrum-related issues for IoT applications. In our paper, a novel method for IoT sensor networks is proposed to obtain the optimal positions of secondary information gathering stations (SIGSs) and to select the optimal operating channel. Our objective is to maximize secondary system capacity while protecting the primary system. In addition, we propose an appearance probability matrix for secondary IoT devices (SIDs) to maximize the supportable number of SIDs that can be installed in a car, in wearable devices, or for other monitoring devices, based on optimal deployment and probability. We derive fitness functions based on the above objectives and also consider signal to interference-plus-noise ratio (SINR) and position constraints. The particle swarm optimization (PSO) technique is used to find the best position and operating channel for the SIGSs. In a simulation study, the performance of the proposed method is evaluated and compared with a random resources allocation algorithm (parts of this paper were presented at the ICTC2017 conference (Wen et al., 2017)).
10 citations
Cites background from "Optimal location of the base statio..."
...Some papers have discussed minimizing power consumption by obtaining optimal base station positions [17, 18]....
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07 Jan 2016
TL;DR: Using ACIS and Google Earth techniques to establish a new Telecommunication base station site selection of the CAD system using the particle swarm optimization algorithm to solve multi-objective mathematical model about base station planning problem.
Abstract: At present, People quickly go into the era of 4 G, which requires vast amounts of 4 G base stations to be established. So How to use the algorithm to layout the base station reasonably in order to save costs for operators has become an important research content. In this context, this paper proposes a new solution--using ACIS and Google Earth techniques to establish a new Telecommunication base station site selection of the CAD system. This system on the basis of predecessors innovatively introduced the reconstructing 3 d terrain simulation system into the base station location optimization problem and used the particle swarm optimization algorithm to solve multi-objective mathematical model of the problem about base station planning problem under the condition of considering the geographic information. It can automatically produce base station primary scheme and showed the primary scheme on the reconstruction of the terrain by ACIS/HOOPS modeling techniques.
7 citations
01 Oct 2017
TL;DR: A novel method is proposed to obtain the optimal positions of secondary base stations (SBSs) for cognitive radio Internet of Things (IoT) sensor networks and to select the optimal operating channel in order to maximize the secondary capacity, while also protecting the primary systems.
Abstract: In our paper, a novel method is proposed to obtain the optimal positions of secondary base stations (SBSs) for cognitive radio Internet of Things (IoT) sensor networks and to select the optimal operating channel in order to maximize the secondary capacity, while also protecting the primary systems. We proposed an appearance probability matrix for secondary IoT sensor devices in order to maximize the supportable number of sensor devices based on the optimal deployment case and probability. We derived fitness functions based on the above objectives and also considered the constraint. The particle swarm optimization (PSO) technique is used to find the best position and operating channel of SBSs.
5 citations
Cites background from "Optimal location of the base statio..."
...[3] also gives the optimal base station locations based on the interference power....
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References
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TL;DR: Simulation results show that the proposed algorithms based on both the SNR and the SLR criteria offer a capacity gain over the conventional centralized antenna systems.
Abstract: In this paper, we propose new algorithms to determine the antenna location for downlink distributed antenna systems (DASs) in single-cell and two-cell environments. We consider the composite fading channel which includes small and large scale fadings. First, for the single-cell DAS, we formulate the optimization problem of distributed antenna (DA) port locations by maximizing the lower bound of the expected signal to noise ratio (SNR). In comparison to the conventional algorithm based on the squared distance criterion which requires an iterative method, our problem generates a closed form solution. Next, for the two-cell DAS, we propose a gradient ascent algorithm which determines the optimum DA locations by maximizing the lower bound of the expected signal to leakage ratio (SLR). In our work, we consider selection transmission, maximal ratio transmission and zero-forcing beamforming (ZFBF) under sum power constraint and study equal gain transmission and scaled ZFBF under per-antenna power constraint. Simulation results show that our proposed algorithms based on both the SNR and the SLR criteria offer a capacity gain over the conventional centralized antenna systems.
92 citations
TL;DR: This paper presents a model that determines the energy consumed per payload bit transferred without error over fading channels of various statistics and finds that each modulation scheme has a single optimal signal-to-noise ratio (SNR) at which the energy consumption is minimized.
Abstract: It is commonly assumed that the energy consumption of wireless communications is minimized when low-order modulations such as BPSK are used. Nevertheless, the literature provides some evidence that low-order modulations are suboptimal for short transmission distances. No complete analysis on how the modulation size and transmission power must be chosen in order to achieve energy-efficient communications over fading channels has been reported so far. In this paper we provide this analysis by presenting a model that determines the energy consumed per payload bit transferred without error over fading channels of various statistics. We find that each modulation scheme has a single optimal signal-to-noise ratio (SNR) at which the energy consumption is minimized. The optimal SNR and the minimal energy consumption are larger for channels with less favorable error statistics. We also find that, if each modulations is operated at its optimal SNR, BPSK and QPSK are the optimal choices for long transmission distances, but as the transmission distance shortens the optimal modulation size grows to 16-QAM and even to 64-QAM. This result leads to showing that for short-range communications the lifetime of a typical low-power transceiver can be up to 500% longer by selecting the optimal constellation instead of BPSK.
50 citations
23 Oct 2006
TL;DR: In this paper, the authors proposed a novel binary integer programming formulation of the base station placement problem that allows the user to find an optimal base station configuration in an interference-limited CDMA system using the branch-and-bound (B&B) method.
Abstract: The placement of base stations is an important issue in planning wireless systems because it can have a significant influence on the overall system performance. In this paper, we propose a novel binary integer programming formulation of the base station placement problem that allows the user to find an optimal base station configuration in an interference-limited CDMA system using the branch-and-bound (B&B) method. The results are compared to those obtained from a customised version of genetic algorithm (GA). It is shown that although the B&B method guarantees an optimal solution, its computational time increases dramatically with the size of the problem and hence its application may be restricted to small problems. In contrast, although the customised GA method does not guarantee an optimal solution, it is shown to be effective in solving the base station placement problem in most cases and its computational time does not increase as dramatically as the B&B method. This observation suggests that the GA may be useful for solving larger problems where the B&B method fails to find a solution within a reasonable time.
35 citations