Building a low cost low power wireless network to enable voice communication in developing regions

Abstract

In this work, we describe our experiences in building a low cost and low power wireless mesh network using IEEE 802.15.4 technology to provide telephony services in rural regions of the developing world. 802.15.4 was originally designed for a completely different application space of non-real-time, low data rate embedded wireless sensing. We use it to design and prototype a telephony system, which we term as Lo 3 (Low cost, Low power, Local voice). Lo 3 primarily provides two use cases; (1) local and broadcast voice within the wireless mesh network, and (2) remote voice to a phone in the outside world. A Lo 3 network can cost as less as $2K, and can last for several days without power "off the grid", thus making it an ideal choice to meet cost and power constraints of rural regions. We test deployed a full-fledged Lo 3 system in a village near Mumbai, India for 18 hours over 3 days. We established voice calls with an end-to-end latency of less than 120ms, with an average packet loss of less than 2%, and a MOS of 3.6 which is considered as good in practice. The users too gave a positive response to our system. We also tested Lo 3 within our department where it can be used as a wireless intercom service. To our knowledge, Lo 3 is the first system to enable such a voice communication system using 802.15.4 technology, and show its effectiveness in operational settings.

Sharing low-cost wireless infrastructures with telecommunications operators to bring 3G services to rural communities

“…In [16] authors describe a system known as Lo (low infrastructure cost, low power, local voice telephony system) based on 802.15.4 to provide telephony services in rural India. The network requires having a cellular base station close to the village to use it as gateway.…”

A-LNT: A Wireless Sensor Network Platform for Low-Power Real-Time Voice Communications

“…There are a few suitable protocols and platforms for WASNs (wireless audio sensor networks) [9] at present [10][11][12][13][14]. Gabale et al present a TDMA-(time division multiple access-) based MAC protocol LiT [10] and implement the MAC on an 802.15.4 platform Tmote; the evaluation of LiT shows quick flow setup, low packet delay, and essentiality for real-time applications; however, the speech coder chosen is G.723.1, and the coding bit is 6.3 kbps, but the speech codec power consumption is not considered; in 2012, a Lo 3 system based on LiT was reported [15], and it showed that such system bodes well with cost and power constraints in rural regions; the audio codec is SPEEX [16] with data rate of 5.9 Kbps, and the expected lifetime is 5 days. For most WSN applications, we need longer lifetime.…”

“…Check RF channel (4) if RF channel is not available (5) If RF channel == MAX RF CHANNEL (6) Halt application. 7else (8) RF channel +1; (9) continue; (10) else (11) break; (12) while (1) (13) Sleep; (14) Wake up for RF packet receiving or system event (15) if time == T SENDING SYNC // time for sending synchronization (16) Send POLL(ALL NODES); (17) else if received RF packet (18) Unpack the packet, extract source address NODEA; (19) If packet type == ACK POLL (20) if the node is synchronized (21) TOUT NODE = 0; // clear timeout counter of the node (22) else if packet type == ACK POLL DATA (23) if the node is synchronized (24) TOUT NODE = 0; Listen to radio channel for 100 ms (5) if RF packet received (6) Calculate system time 7Set system parameter; (8) while (counter < CMAX) (9) Send APPLY(CNODE) (10) while ( < TTIMEOUT) (11) Listen to radio channel (12) if ACK APL received (13) break; (14) else if DENY received (15) break; (16) if ( ≥ TTIMEOUT) (17) counter++; (18) else if DENY received (19) RF channel = unavailable; (20) break; (21) else if ACK APL received (22) counter = 0; In our design, the work is mainly done by CNODE. It chooses an available radio channel and waits for radio packet receiving events.…”

An Evaluation of the Goertzel Algorithm for Low-Power, Embedded Systems

“…Multiple tones can be detected by running the algorithm multiple times, unlike the FFT which calculates for all bins simultaneously. Examples include structural health monitoring [2], instrument tuning [3], power metering [4] and active damping [5], voice [6] and underwater communications [7], security applications such as fingerprint identification [10], and mobile applications such as crowd counting [8] and gesture sensing [9].…”