SIR Analysis In Square-Shaped Indoor Premises

The increased wireless network densification has resulted in availability of wireless access points (AP) in almost each and every indoor location (room, office, etc.). To provide complete in-building coverage very often an AP is deployed per room. In this paper we analyze signal-to-interference (SIR) ratio for wireless systems operating in neighboring rooms separated by walls of different materials by explicitly taking into account the propagation and wall penetration losses. Both AP and direct device-to-device (D2D) configurations are addressed. Our numerical results indicate that the performance of such system is characterized by both the loss exponent describing the propagation environment of interest and wall materials. We provide the numerical results for typical wall widths/materials and analyze them in detail. INTRODUCTION The predicted increase in the user traffic demands places extreme requirements on the future evaluation of mobile systems, often referred to as fifth generation (5G) networks [1], [2]. In addition to physical layer improvements including advanced modulation and coding and MIMO techniques, over the last decade researchers investigated a number of network solutions providing decisive performance improvements including the use of small (micro/pico/femto) cells [3], clientrelays [4], direct in-band and out-of-band device-to-device communications [5]. All these concepts target aggressive spatial reuse of frequencies promising substantial area capacity gains. With the adoption of novel mechanism the user devices are expected to take a more active part in 5G systems and, in some cases, even take on the role of the network infrastructure in providing wireless connectivity such as offering D2D-based data relaying, proximity services, etc. This shift from the classic cellular model is dictated by the progress in communications technologies: the user devices are augmenting their capabilities, whereas the base stations (BSs) are becoming smaller as a result of the ongoing network densification [6]. The networks densification, novel networking and service mechanisms as well as the trend to use multiple access technologies to serve the users, known as heterogeneous cellular system concept, altogether lead to increased randomness of the network, where the positions of servicing stations such as BSs, relays and D2D partners are random rather than deterministic. The signal-to-interference ratio (SIR) is a universal metric specifying performance of wireless systems [7]. Once SIR is known one could describe the Shannon rate of the channel and spectral efficiency of the system. In contrast to noise-limited systems, where the bit error rate (BER) decreases exponentially with signal-to-noise ratio (SNR), the heterogeneous mobile networks are interference-limited showing linear improvement of BER with respect to SIR. Thus, the increase of the emitted power does not improve the performance of these systems. Thus, the problem of finding SIR for typical network configurations is of special importance characterizing applicability and typical scenarios of modern and future wireless technologies. The SIR performance of wireless systems is often studied using the tools of stochastic geometry [8]. The basic approach is to specify the point process on the plane modeling positions of the stations and then derive the interference at the point of interest. The last step is rather complex as we need closed-form distribution of distance to the point of interest from at least several neighboring points. For this reason typical considered models are often limited to Poisson point process on the plane for which we immediately have closed-form expressions for distributions of distances to the i-th neighbor [9]. The constantly increasing need for wireless connectivity on-the-go [10] are gradually changing the way service is provisioned in wireless networks. Nowadays, one of the trends is to deploy small wireless stations including both IEEE 802.11 or micro-LTE access points (AP) in crowded areas to benefit from increased network densification [6] and shorter propagation distances. Examples include large shopping mall, office environment, where one of few adjacent rooms is served by an AP having relatively small coverage area. In this dense environment interference between neighboring APs is inevitable and may easily lead to degraded system performance. In this paper, using the tools of stochastic geometry, we analyze performance of wireless systems operating in neighboring rooms of rectangular configuration. We consider both direct device-to-device and AP configurations assuming that Proceedings 30th European Conference on Modelling and Simulation ©ECMS Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose (Editors) ISBN: 978-0-9932440-2-5 / ISBN: 978-0-9932440-3-2 (CD) the systems in adjacent rooms operate at the same frequency. The analytical results are compared to simulations showing adequate agreement. Numerical results for the set of input metrics demonstrate that the system performance is dictated by the interplay between path loss exponent typical for a given environment and type of the walls used between rooms. The rest of the paper is organized as follows. First, in the next section we introduce a system model. Further, we analytically study SIR for downlink scenario. The simulation models for both downlink and D2D scenarios are introduced next. Numerical results for different sets in input variables are illustrated. Conclusions are drawn in the last section. SYSTEM MODEL In this study we focus on an indoor scenario with grid aligned rooms, see Fig. 1 that are typical for shopping malls or office buildings. In these environments rooms are often of rectangular or square shapes. Each room is assumed to be equipped with an AP deployed in the geometrical center. To take advantage of the wireless network densification trend as a solution to upgrade the degree of spatial reuse, the devices in adjacent rooms are assigned the same set of communication channels [6]. The mobile terminals (users) operating over the same channel are assumed to be uniformly distributed over the room, one per room. We concentrate on the so-called tagged user in the central room, see Fig. 1(a) and Fig. 1(b). We assume both AP and users to be equipped with omnidirectional antennas. We do not focus on a particular radio technology addressing the general case. In addition to AP scenario we also address D2D configuration, sketched in Fig. 1(c). The principal difference compared to AP case is that both transmitter and receiver are assumed to be uniformly distributed within a room. Under this assumption the configuration is symmetric, i.e., we do not have to distinguish between uplink and downlink cases. Similarly, we concentrate on D2D pair located in the central room. Focusing on SIR, as a metric of interest, for both AP and D2D configurations we calculate it for a randomly chosen receiving device, taking into account the interference from a set of neighboring rooms. Using the commonly used propagation model, we add a correction factor, accounting for the attenuation of a signal when passing through a wall