Wireless Energy Efficiency Evaluation for Buildings Under Design Based on Analysis of Interference Gain
Artikel i vetenskaplig tidskrift, 2020

In this paper, we present part of our ground-breaking work that bridges building design and wireless network deployment. The original contributions lie in: i) defining interference gain (IG) as an intrinsic figure of merit (FoM) of a building & x2019;s wireless performance in terms of interference signal blockage; ii) developing analytic models to calculate IG; and iii) developing a novel method to calculate the optimum transmitting power to achieve the maximum IG of a building. The IG is derived as an integral transform of the probability density function (PDF) of the distance from a probe user equipment (UE) with a random position relative to a wall, and with a uniformly distributed direction. Furthermore, the PDF of the random distance is derived in closed-form for rectangular rooms to facilitate fast computation of the IG of a building under design (BUD) tiled by rectangular rooms and corridors. For BUD with irregular rooms, a random shooting algorithm (RSA) is proposed to numerically compute the PDF. The closed-form expression and the RSA are compared and validated. Numerical results show the validity of both the model to calculate IG and the methodology to derive the optimum transmitting power to achieve the maximum IG of a given building. The results shed light to architects on how to design buildings with desirable wireless performance and for radio engineers on how densely wireless access points can be deployed to approach the intrinsic wireless performance of a building.

wireless performance evaluation



Wireless networks


Probability density function

building design

5G networks

Smart buildings



Jiliang Zhang

University of Sheffield

Andres Alayon Glazunov

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Antennsystem

Universiteit Twente

Jie Zhang

Ranplan Wireless Network Design Ltd

University of Sheffield

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 69 6 6310-6324







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