Received signal strength indicator

Last updated
Cellular signal strength of -74dBm (or 66 asu) displayed on a smartphone. Also shown: signal bars of two cellular networks, and signal bars of a Wi-Fi network. Signal Strength -74 dBm 66 asu LTE Golan Telecom Signal Bars EN.jpg
Cellular signal strength of -74dBm (or 66 asu) displayed on a smartphone. Also shown: signal bars of two cellular networks, and signal bars of a Wi-Fi network.

In telecommunications, received signal strength indicator or received signal strength indication [1] (RSSI) is a measurement of the power present in a received radio signal. [2]

Contents

RSSI is usually invisible to a user of a receiving device. However, because signal strength can vary greatly and affect functionality in wireless networking, IEEE 802.11 devices often make the measurement available to users.

RSSI is often derived in the intermediate frequency (IF) stage before the IF amplifier. In zero-IF systems, it is derived in the baseband signal chain, before the baseband amplifier. [3] RSSI output is often a DC analog level. It can also be sampled by an internal analog-to-digital converter (ADC) and the resulting values made available directly or via peripheral or internal processor bus.

In 802.11 implementations

In an IEEE 802.11 system, RSSI is the relative received signal strength in a wireless environment, in arbitrary units. RSSI is an indication of the power level being received by the receiving radio after the antenna and possible cable loss. Therefore, the greater the RSSI value, the stronger the signal. Thus, when an RSSI value is represented in a negative form (e.g. −100), the closer the value is to 0, the stronger the received signal has been.

RSSI can be used internally in a wireless networking card to determine when the amount of radio energy in the channel is below a certain threshold at which point the network card is clear to send (CTS). Once the card is clear to send, a packet of information can be sent. The end-user will likely observe an RSSI value when measuring the signal strength of a wireless network through the use of a wireless network monitoring tool like Wireshark, Kismet or Inssider. As an example, Cisco Systems cards have an RSSI maximum value of 100 and will report 101 different power levels, where the RSSI value is 0 to 100. Another popular Wi-Fi chipset is made by Atheros. An Atheros-based card will return an RSSI value of 0 to 127 (0x7f) with 128 (0x80) indicating an invalid value.

There is no standardized relationship of any particular physical parameter to the RSSI reading. The 802.11 standard does not define any relationship between RSSI value and power level in milliwatts or decibels referenced to one milliwatt (dBm). Vendors and chipset makers provide their own accuracy, granularity, and range for the actual power (measured as milliwatts, which can be expressed in terms of decibels relative to one milliwatt) and their range of RSSI values (from 0 to RSSI maximum, in arbitrary signal units "asu"). [4] One subtlety of the 802.11 RSSI metric comes from how it is sampledRSSI is acquired during only the preamble stage of receiving an 802.11 frame, not over the full frame. [5]

As early as 2000, researchers were able to use RSSI for coarse-grained location estimates. [6] More recent work was able to reproduce these results using more advanced techniques. [7] Nevertheless, RSSI does not always provide measurements that are sufficiently accurate to properly determine the location. [8] However, RSSI still represents the most feasible indicator for localization purposes as it is available in almost all wireless nodes and it does not have any additional hardware requirements. [9]

Received channel power indicator

For the most part, 802.11 RSSI has been replaced with received channel power indicator (RCPI). RCPI is an 802.11 [5] measure of the received radio frequency power in a selected channel over the preamble and the entire received frame, and has defined absolute levels of accuracy and resolution. RCPI is exclusively associated with 802.11 and as such has some accuracy and resolution enforced on it through IEEE 802.11k-2008. Received signal power level assessment is a necessary step in establishing a link for communication between wireless nodes. However, a power level metric like RCPI generally cannot comment on the quality of the link like other metrics such as travel time measurement (time of arrival).

Uses in indoor localization

RSSI-based distance estimation

RSSI is commonly used in wireless communication protocols, such as Bluetooth and ZigBee, to estimate the distance between nodes.[ citation needed ] This estimation is essential for indoor localization and is often preferred due to its simplicity and the lack of need for synchronization or timestamping, as required in other methods like Time of Arrival (TOA).

Localization algorithms

Various localization algorithms, such as anchor-based algorithms, employ RSSI. Anchor-based algorithms use nodes with known positions (anchors) to determine the location of an unknown node. The accuracy of these algorithms is enhanced by using a higher number of known nodes, as they rely on the Time of Arrival (TOA) and Angle of Arrival (AOA) of the signal for estimating the distance between the known nodes and the unknown node. However, the accuracy of these algorithms can be affected by environmental factors, such as signal interference, obstacles, and the density of nodes in the area.[ citation needed ]

Effect of environmental factors and antenna type

Factors like diffraction, reflection, scattering, and antenna type can significantly influence RSSI values. These variables need consideration for accurate indoor localization using RSSI. [10]

RSSI-with-Angle-based Localization Estimation (RALE)

The RALE approach offers several advantages for indoor localization:

See also

Related Research Articles

<span class="mw-page-title-main">IEEE 802.11</span> Wireless network standard

IEEE 802.11 is part of the IEEE 802 set of local area network (LAN) technical standards, and specifies the set of medium access control (MAC) and physical layer (PHY) protocols for implementing wireless local area network (WLAN) computer communication. The standard and amendments provide the basis for wireless network products using the Wi-Fi brand and are the world's most widely used wireless computer networking standards. IEEE 802.11 is used in most home and office networks to allow laptops, printers, smartphones, and other devices to communicate with each other and access the Internet without connecting wires. IEEE 802.11 is also a basis for vehicle-based communication networks with IEEE 802.11p.

<span class="mw-page-title-main">Wireless network</span> Computer network not fully connected by cables

A wireless network is a computer network that uses wireless data connections between network nodes. Wireless networking allows homes, telecommunications networks and business installations to avoid the costly process of introducing cables into a building, or as a connection between various equipment locations. Admin telecommunications networks are generally implemented and administered using radio communication. This implementation takes place at the physical level (layer) of the OSI model network structure.

<span class="mw-page-title-main">Carrier-sense multiple access with collision avoidance</span> Computer network multiple access method

Carrier-sense multiple access with collision avoidance (CSMA/CA) in computer networking, is a network multiple access method in which carrier sensing is used, but nodes attempt to avoid collisions by beginning transmission only after the channel is sensed to be "idle". When they do transmit, nodes transmit their packet data in its entirety.

<span class="mw-page-title-main">Wi-Fi</span> Wireless local area network

Wi-Fi is a family of wireless network protocols based on the IEEE 802.11 family of standards, which are commonly used for local area networking of devices and Internet access, allowing nearby digital devices to exchange data by radio waves. These are the most widely used computer networks, used globally in home and small office networks to link devices and to provide Internet access with wireless routers and wireless access points in public places such as coffee shops, hotels, libraries, and airports to provide visitors.

Ultra-wideband is a radio technology that can use a very low energy level for short-range, high-bandwidth communications over a large portion of the radio spectrum. UWB has traditional applications in non-cooperative radar imaging. Most recent applications target sensor data collection, precise locating, and tracking. UWB support started to appear in high-end smartphones in 2019.

A cognitive radio (CR) is a radio that can be programmed and configured dynamically to use the best channels in its vicinity to avoid user interference and congestion. Such a radio automatically detects available channels, then accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given band at one location. This process is a form of dynamic spectrum management.

Wireless sensor networks (WSNs) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind.

Qualcomm Atheros is a developer of semiconductor chips for network communications, particularly wireless chipsets. The company was founded under the name T-Span Systems in 1998 by experts in signal processing and VLSI design from Stanford University, the University of California, Berkeley, and private industry. The company was renamed Atheros Communications in 2000 and it completed an initial public offering in February 2004, trading on the NASDAQ under the symbol ATHR.

A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers or wireless access points. Instead, each node participates in routing by forwarding data for other nodes. The determination of which nodes forward data is made dynamically on the basis of network connectivity and the routing algorithm in use.

Long-range Wi-Fi is used for low-cost, unregulated point-to-point computer network connections, as an alternative to other fixed wireless, cellular networks or satellite Internet access.

<span class="mw-page-title-main">Indoor positioning system</span> Network of devices used to wirelessly locate objects inside a building

An indoor positioning system (IPS) is a network of devices used to locate people or objects where GPS and other satellite technologies lack precision or fail entirely, such as inside multistory buildings, airports, alleys, parking garages, and underground locations.

Wi-Fi positioning system is a geolocation system that uses the characteristics of nearby Wi‑Fi access point to discover where a device is located.

There are several uses of the 2.4 GHz ISM radio band. Interference may occur between devices operating at 2.4 GHz. This article details the different users of the 2.4 GHz band, how they cause interference to other users and how they are prone to interference from other users.

<span class="mw-page-title-main">OCARI</span>

OCARI is a low-rate wireless personal area networks (LR-WPAN) communication protocol that derives from the IEEE 802.15.4 standard. It was developed by the following consortium during the OCARI project that is funded by the French National Research Agency (ANR):

WiFi-Where was a tool that facilitated Wardriving and detection of wireless LANs using the 802.11b, 802.11a and 802.11g WLAN standards. Versions existed for the operating systems iOS and Palm OS. Originally created in June 2004 for the Palm OS by Jonathan Hays of Hazelware Software, the IP for WiFi-Where was licensed to 3Jacks Software in 2009. An iPhone version of the application was released in January 2010, but was pulled from the App Store by Apple in March 2010. The app was frequently listed as a common tool to facilitate Wardriving As of 2010, it is still available in the Jailbroken Cydia store.

IEEE 802.11ac-2013 or 802.11ac is a wireless networking standard in the IEEE 802.11 set of protocols, providing high-throughput wireless local area networks (WLANs) on the 5 GHz band. The standard has been retroactively labelled as Wi-Fi 5 by Wi-Fi Alliance.

Teresa Huai-Ying Meng is a Taiwanese-American academician and entrepreneur. She is the Reid Weaver Dennis Professor of Electrical Engineering, Emerita, at Stanford University, and founder of Atheros Communications, a wireless semiconductor company acquired by Qualcomm, Inc.

Task Group mc (TGmc) of the IEEE 802.11 Working Group, sometimes referred to as IEEE 802.11mc, was the third maintenance/revision group for the IEEE 802.11 WLAN standards. Purpose was to incorporate accumulated maintenance changes into IEEE Std 802.11-2012, and roll up approved amendments into the standard.

WiFi sensing uses existing Wi-Fi signals to detect events or changes such as motion, gesture recognition, and biometric measurement. WiFi sensing is a combination of Wi-Fi and radar sensing technology working in tandem to enable usage of the same Wi-Fi transceiver hardware and RF spectrum for both communication and sensing.

Ultra-wideband impulse radio ranging is a wireless positioning technology based on IEEE 802.15.4z standard, which is a wireless communication protocol introduced by IEEE, for systems operating in unlicensed spectrum, equipped with extremely large bandwidth transceivers. UWB enables very accurate ranging without introducing significant interference with narrowband systems. To achieve these stringent requirements, UWB-IR systems exploit the available bandwidth that they support, which guarantees very accurate timing and robustness against multipath, especially in indoor environments. The available bandwidth also enables UWB systems to spread the signal power over a large spectrum, avoiding narrowband interference.

References

  1. "Usage of received signal strength indicator v. received signal strength indication in literature". Google Ngram Viewer.
  2. Martin Sauter (2010). "3.7.1 Mobility Management in the Cell-DCH State". From GSM to LTE: An Introduction to Mobile Networks and Mobile Broadband (eBook). John Wiley & Sons. p. 160. ISBN   9780470978221 . Retrieved 2013-03-24.
  3. Foerster, Anna; Foerster, Alexander (2011-02-07). Emerging Communications for Wireless Sensor Networks. BoD – Books on Demand. p. 241. ISBN   978-953-307-082-7.
  4. Lui, Gough; Gallagher, Thomas; Binghao, Li (2011). Differences in RSSI readings made by different Wi-Fi chipsets: A limitation of WLAN localization. 2011 International Conference on Localization and GNSS (ICL-GNSS). pp. 53–57. doi:10.1109/ICL-GNSS.2011.5955283. hdl: 1959.4/unsworks_47285 . ISBN   978-1-4577-0186-3. S2CID   16846238.
  5. 1 2 "IEEE 802.11-2012". IEEE. 2012-03-29. Retrieved 2013-02-11.
  6. Paramvir, Bahl; Padmanabhan, Venkata. "RADAR: An In-Building RF-based User Location and Tracking System". Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. doi:10.1109/INFCOM.2000.832252 . Retrieved 19 December 2014.
  7. Sen, Souvik; Lee, Jeongkeun; Kim, Kyu-Han; Congdon, Paul (2013). "Avoiding Multipath to Revive Inbuilding WiFi Localization". MobiSys '13: Proceeding of the 11th annual international conference on Mobile systems, applications, and services. pp. 249–262. doi:10.1145/2462456.2464463. ISBN   9781450316729. S2CID   16251944 . Retrieved 19 December 2014.
  8. Parameswaran, Ambili Thottam; Husain, M, I.; Upadhyaya, S. Is RSSI a Reliable Parameter in Sensor Localization Algorithms – An Experimental Study (PDF). 28th International Symposium On Reliable Distributed Systems, New York. September 2009. Retrieved 17 March 2013.{{cite conference}}: CS1 maint: multiple names: authors list (link)
  9. Alhasanat, Abdullah; Sharif, Bayan; Tsemendis, C. (January 2016). "Efficient RSS-based collaborative localisation in wireless sensor networks". International Journal of Sensor Networks. 22 (1): 27–36. doi:10.1504/IJSNET.2016.079335.
  10. "RSSI-based method in Indoor Asset Tracking: Benefits, Drawbacks and Comparison with AoA, Navigine".