System Performance Estimation
In Chapter 3, techniques for propagation modelling were discussed. A three-dimensional GO/UTD model implemented in MATLABr was compared with experimental mea-surements. The contribution of higher order reflections was analysed by comparing the total received power in various LOS and NLOS locations within a simple indoor environment.
This chapter describes how received signal strength (RSS) is associated with wire-less system performance. The RSS depends on a number of parameters such as transmitted power, antenna gains, noise, interference, channel behaviour, etc. The eﬀect of noise and interference on the overall system performance is described in Section § 4.2. Section § 4.3 illustrates the concept of link budget to account for the parameters aﬀecting the received signal strength and Section § 4.4 discusses the trade-oﬀ between coverage and capacity of wireless system deployment. Sec-tion § 4.5 describes describes the necessary requirements to ensure adequate system performance in indoor environments and Section § 4.6 describes the cost function developed to quantify coverage via several illustrative examples. Section § 4.7 sum-marises this chapter.
Characterisation of Noise and Interference
Generally, wireless system performance can be quantified by bit error rate (BER), which is defined as the ratio of the number of received data packets with an error to the total number of data packets sent. BER is a measure of end-to-end system performance and is aﬀected by interference, transmitter power, the order of modu-lation and bandwidth. Noise and interference are two important factors causing loss of information bits at the receiver and need to be carefully accounted for in system planning.
Thermal noise is generated by all operating electronic components and is caused by current variation. Thermal noise power (dBW) can be expresses as where k is Boltzmann’s constant (1.380 × 1023J/K), T (◦K) is the temperature and B is the bandwidth (Hz).
Based on (4.1) the thermal noise power for 1 Hz bandwidth at room temperature is −204 dBW (or −174 dBm).
Noise Figure is a useful parameter to quantify the noise levels at the input and output and is expressed in terms of Signal-to-Noise-Ratio (SNR) at the input to that at the output. The SNR is the ratio of signal power to the noise power. The Noise Figure NF is expressed in dB
The lower the noise figure (NF), the better is system performance. The Noise Floor is the noise power at a given bandwidth and given noise figure.
where G is the gain of the device.
The minimum detectable signal level can be obtained from the total noise floor calculation of the transmitter and the receiver sections in a wireless system. [7, pp. 611-615].
The thermal noise power is directly proportional to the temperature and bandwidth of the signal. In order to reconstruct the baseband signal from a modulated carrier, a minimum signal power is required at the receiver, which must be above the minimum detectable signal power Pmin(dBW). Signals below or equal to the noise floor.
Cellular wireless systems use the cellular concept, which divides a large area into small cells. The cellular concept reduces spectral congestion and increases user capacity. It also eliminates the need for a single high power transmitter by having base-station antennas in each cell. The number of base stations can be increased to meet demand. The entire frequency spectrum available is divided into channels, some of which are allocated to each base station. The neighbouring base stations are assigned diﬀerent channels. The same channels can be used in diﬀerent cells if they are suﬃciently far apart to maintain the interference levels within an acceptable limit. This is called frequency reuse [7, pp. 57-59]. Fig. 4.1 shows a cell concept and frequency reuse. A group of cells is called a cluster within which no frequency is reused. Same numbered cells use the same group of channels. The transmitting antenna can be placed either at the centre of the cell or at the intersection of three cells.
The total available channels are divided among the cells. If there are na number of duplex channels available in a cellular system consisting of N cells and each cell is allocated nc number of channels (nc<na) then the total number of channels and the channels
Here, N is the cluster size of the cellular system. For a cellular system consisting of clusters, the total channels nt .
The value of N is decided by the minimum acceptable level of interference in the system. In order to maximise the capacity in a given area, N needs to be as small as possible. The reciprocal of N is called the frequency reuse factor of a cellular system.
Increased frequency reuse causes interference. Interference aﬀects system perfor-mance and limits throughput. Cells operating at the same frequency are designated with same number in Fig. 4.1. They are termed co-channel cells and the interference caused by these cells is known as co-channel interference. Though the SNR can be improved by increasing the transmitted power, co-channel interference cannot be combated by this approach. It is a function of the cell radius and the distance between the centres of the nearest co-channel cells. Co-channel interference can be reduced by increasing the frequency reuse distance. The co-channel reuse ratio Q can be expressed as where rc is the radius (m) of the cells and dc is the distance (m) between the centers of the nearest co-channel cells. To increase the capacity, the value of Q needs to be as small as possible. But as Q decreases the co-channel interference levels increase.
Signal to Interference plus Noise Ratio (SINR)
In actual practice, instead of representing the noise and interference separately, the Signal-to-Interference-plus-Noise Ratio (SINR) is often considered to represent the signal quality of wireless systems [108, pp. 225-283]. It is the ratio of signal power PS (W) to the sum of noise power PN (W) and interference signal power PI (W) and is expressed as The overall system performance is aﬀected by the SINR. Although noise and in-terference are two major factors aﬀecting the overall system performance, there are many other parameters such as propagation loss, cable losses, antenna gains, etc. that need to be carefully considered in wireless system planning. A proper link bud-get need to be prepared to account for the parameters aﬀecting the total received signal strength (RSS).
The link budget is used to calculate the maximum allowable pathloss from the bases-tation to the user device in a cellular system. To understand the overall system per-formance, both downlink (basestation to user device) and uplink (user device to the basestation) must be budgeted in order to obtain the maximum allowable pathlosses in both cases. The RSS depends on a number of factors such as transmitted power, antenna gains, pathloss, feeder loss, etc. [109, pp. 329-344][110, pp.76-82]. The received power is directly related to the gains and losses of various components such as amplifiers, connecting cables, feeders, antennas, etc. in the system and the prop-agation loss in the channel. Therefore, all parameters that aﬀect the signal levels and determine the required minimum signal level at the receiving antenna need to be clearly specified and accounted for in link budget. The main parameters are
Transmitter power or power from the basestation Pt (dBm)
Cable loss or feeder loss Ac (dB) is the attenuation of the feeding mechanism such as coaxial cable used to feed the antenna
Transmitting and receiving antenna gains Gt and Gr respectively (dBi)
Path loss P L (dB)
Noise Figure of the transmitter and receiver NF (dB)
Thermal Noise Floor (dB), which is a constant at a particular temperature for a specified bandwidth
Interference from the other basestations operating at the same frequency. The received power (dBm) can be related to the gains and losses in the system as
Parameters associated with noise and interference determine the required min-imum signal level to be maintained at the receiver, whereas gains and losses of various components in the system determine the signal strength at the receiving antenna. By increasing the transmitter power, signal levels at the receiving antenna can be increased. However, this increases the interference and thus degrades system performance. A proper link budget is essential to system performance.
Coverage and Capacity
Conventionally, in cellular systems, coverage is the geographic area where the trans-mitted signal power is above a particular threshold power level Pth. There is always a trade-oﬀ between coverage and capacity. Coverage can be increased by simply increasing the transmitted power, but at the same time capacity is reduced owing to increased co-channel interference. The maximum possible data rate through a wire-less channel is referred to as Shannon’s channel capacity and is given by [112, pp. 128-134]
where B (Hz) is the bandwidth, PS (W) is the signal power and PN (W) is the noise power. In order to increase the user capacity while maintaining the available signal quality or to provide improved signal quality [7, pp. 86-96], approaches such as cell splitting, sectoring, range extension using repeaters and the use of microcell zones are developed.
Cell Splitting is the process of sub-dividing cells into smaller ones in order to increase the capacity and to avoid congestion. Introducing new cells with smaller radii, called microcells, inside the existing cell increases the number of channels per unit area, which increases the capacity. The signal to interference ratio remains the same if the cluster size is maintained. As shown in Fig. 4.3, basestations are at the corners of each cell and additional base-stations are introduced to split cells. Channels 2 to 6 are reused around the base station 1. The radii of new microcells are half of the original cells in this example. To avoid co-channel interference, the transmitting power should be reduced.
Sectoring is adopted to increase the capacity as well as the signal to interference ratio. Several directional antennas are utilised at the basestation instead of a single omni-directional antenna at the cell centre. For example, three antennas of 120◦ beam width or six antennas of 60◦ beam width can be introduced to sweep 360◦. As sectoring uses multiple antennas at each base station, the available channels need to be further divided among these antennas. Fig. 4.4 illustrates the subdividing of cells into six sectors using antennas of 60◦ beamwidth. Sectoring approach does not increase cluster size. The main disadvantage of this approach is the increased number of handovers1.
Repeaters are used to improve coverage in weak signal regions or in targeted loca-tions. Repeaters do not increase the capacity of the system. They receive a signal from the basestation and re-radiate the amplified signal. As the interference and noise also are amplified with the signal, careful planning of the location of repeaters is very important.
The use of Microcell zones is introduced to avoid the increased handover problem in the sectoring approach . In this approach, a cell is further divided into microcells having separate transmitting/receiving antennas located at the vertices of the microcells, which are connected to the same basestation having the same hardware resources shared through zone selector equipment as shown in Fig. 4.5. All microcells operate at the same frequency and thereby avoid handover. This concept is commonly adopted for indoor environments .
Though the capacity can be increased by the above techniques, the number of com-ponents in the system also increases and thus the expense. It is desirable to achieve the maximum performance at the minimum expense.
Performance of Indoor Systems
As discussed in Chapter 2, basestation planning needs more care in indoor environ-ments than outdoor environments owing to the site-specific nature of the propaga-tion . Moreover, the service requirements need to be considered. For example, wireless systems in hospital environments used for real-time medical imaging ap-plications need to have high data rate and low latency , whereas the latency required for multimedia video streaming applications is not necessarily as low as for medical applications .
The system performance for a given scenario depends on the network and service requirements. Generally, the performance of an indoor wireless system can be quan-tified in terms of coverage, throughput, capacity, power consumption, etc. Industries use Key Performance Indicators (KPI) to quantify system performance  based on the network and service requirements.
Providing adequate coverage is an elementary requirement of an indoor wireless system. At the least, it is essential to provide adequate coverage in all significant volumes within the indoor environment. The term ‘significant volume’ refers to the volume in which the probability of finding a user device is greater than zero. For example, it would be unlikely to find an operating user device locked inside a filing cabinet, so good coverage in this volume is not expected, and there is no impact on the overall system performance if such a volume is not covered.
Factors aﬀecting the wireless system performance vary with respect to frequencies also. Interference from outdoor and indoor basestations is significant in the sub-6 GHz bands owing to the penetration of signals through walls and building struc-tures, whereas due to higher propagation and penetration losses at millimetre wave frequencies, interference is likely to be less compared to sub-6 GHz frequencies . This makes millimetre wave frequencies suitable for single room per cell scenarios . In addition to the increased losses, diﬀraction is less dominant , which may results in no signal regions in NLOS regions inside the indoor environment. So a quantitative measure of coverage (or shadowing) at these frequencies is needed to be analysed to understand the behaviour of millimetre wave indoor systems.
Cost Function to Quantify System Performance
To quantify system performance, a cost function has been developed that takes into account the relative importance of diﬀerent regions within the indoor environment. For example, the volume inside a filing cabinet is less significant because it is an unlikely location for an operating user device. Therefore, this volume need not to be considered when system performance is quantified. The cost is defined as a weighted sum of user locations that fail to exceed a specified coverage threshold power Pth namely, where u, v, w ∈ I, W (u, v, w) is a cost weight corresponding to the user location (u, v, w) in a matrix grid topology based on the Cartesian coordinate system and
W (u, v, w) is used to weight diﬀerent regions depending on their importance (0 ≤≤ 1), Nx, Ny and Nz are the numbers of user locations in the x, y and z directions respectively, and
NT = umvmwm where (um, vm, wm) are the total number of user locations along (u, v, w) in volume having weight W > 0.
The cost function C gives a weighted coverage representation inside an indoor sce-nario. It can be used to signify diﬀerent volumes inside the indoor space and enables the coverage of particular volumes to be analysed by assigning a suitable weightings to the various regions depending on their significance. If the coverage of table tops is more important than the rest of the volume inside the geometry, a suitable category weight can be assigned (which gives significance to the volume above the table) to obtain the most suitable deployment for that particular scenario.
2 Indoor Propagation at Millimetre Wave Frequencies
2.2 Radio Wave Propagation
2.3 Indoor Wireless Systems
2.4 Contribution of the Thesis
3 Propagation Modelling using Ray Methods
3.2 Ray-Optic Fields
3.3 Received Signal Strength
4 System Performance Estimation
4.2 Characterisation of Noise and Interference
4.3 Link Budget
4.4 Coverage and Capacity
4.5 Performance of Indoor Systems
4.6 Cost Function to Quantify System Performance
5 Research Overview
5.2 Environmental Modelling
5.3 Antenna Configurations and Characteristics
5.4 Research Overview
6 Performance Study using Single Antenna Deployment
6.2 Overview of the Investigation
6.3 Cost Analysis
7 Performance Enhancement using Multiple Antennas
7.2 Overview of the Investigation
7.3 Cost Analysis using Multiple Antennas
7.4 System Performance Enhancement
8 Performance Enhancement using Environmental Modifications
8.2 Impact of Reflective Building Components
8.3 Deployment of a Spherical Reflector
8.4 Deployment of a Hemispherical Array Reflector
8.5 Reflectarray to Enhance System Performance
9 Implications for System Performance
9.2 Prediction using the GO/UTD Model
9.3 Suitability of the Cost Function
9.4 Implications for System Performance
9.5 Recommendations for Future Investigations
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Deploying Millimetre Wave Indoor Wireless Systems