IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 71, NO. 1, JANUARY 2024

89

92 Mb/s Fat-Intrabody Communication (Fat-IBC)
With Low-Cost WLAN Hardware
Pramod K. B. Rangaiah, Member, IEEE, Johan Engstrand , Ted Johansson , Senior Member, IEEE,
Mauricio D. Perez , Member, IEEE, and Robin Augustine , Member, IEEE

Abstract—The human subcutaneous fat layer, skin andmuscle together act as a waveguide for microwave transmissions and provide a low-loss communication medium
for implantable and wearable body area networks (BAN). In
this work, fat-intrabody communication (Fat-IBC) as a human body-centric wireless communication link is explored.
To reach a target 64 Mb/s inbody communication, wireless
LAN in the 2.4 GHz band was tested using low-cost Raspberry Pi single-board computers. The link was characterized using scattering parameters, bit error rate (BER) for
different modulation schemes, and IEEE 802.11n wirelesscommunication using inbody (implanted) and onbody (onthe skin) antenna combinations. The human body was emulated by phantoms of different lengths. All measurements
were done in a shielded chamber to isolate the phantoms
from external interference and to suppress unwanted transmission paths. The BER measurements show that, except
when using dual on-body antennas with longer phantoms,
the Fat-IBC link is very linear and can handle modulations
as complex as 512-QAM without any significant degradation of the BER. For all antenna combinations and phantoms lengths, link speeds of 92 Mb/s were achieved using
40 MHz bandwidth provided by the IEEE 802.11n standard
in the 2.4 GHz band. This speed is most likely limited by
the used radio circuits, not the Fat-IBC link. The results
show that Fat-IBC, using low-cost off-the-shelf hardwareand established IEEE 802.11 wireless communication, canachieve high-speed data communication within the body.
The obtained data rate is among the fastest measured withintrabody communication.
Index Terms—Body area networks (BAN), body sensor
networks (BSN), intrabody communication (IBC), bit error
rate (BER), signal-to-noise ratio (SNR), WLAN.

Manuscript received 18 March 2023; revised 1 June 2023; accepted
27 June 2023. Date of publication 11 July 2023; date of current version 25 December 2023. This work was supported by Wireless BrainConnect inteRfAce TO machineS: B-CRATOS, European Union’s Horizon 2020 Research and Innovation Program, under Grant 965044,
DOI.10.3030/965044, funded through EXCELLENT SCIENCE - Futureand Emerging Technologies (FET) Open. This work was coordinatedby UPPSALA UNIVERSITET, Sweden. Start date 1 March 2021 andEnd date 28 February 2025. (Pramod K. B. Rangaiah, Johan Engstrand,
and Ted Johansson are co-first authors.) (Corresponding author: Robin
Augustine.)
Pramod K. B. Rangaiah, Johan Engstrand, Ted Johansson, andMauricio D. Perez are with the Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, Sweden.
Robin Augustine is with the Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, SE-751 03 Uppsala, Sweden (e-mail: robin.augustine@angstrom.uu.se).
Digital Object Identifier 10.1109/TBME.2023.3292405

I. INTRODUCTION
N RECENT years, body area networks (BAN) and bodysensor networks (BSN) have due to their potential in healthcare, sports, and entertainment gained attention [1], [2]. BAN
allows data to be shared between personal portable devices andsensors on the body and plays an important role in a numberof biomedical applications that continuously measure humanphysiological data such as electrocardiogram (ECG), heart rate,
blood pressure, and body temperature [3]. A health tracker canmeasure important parameters continuously, which is essential
for patients with chronic diseases who are at risk and who need
early warning and long-term treatment [4]. For wireless BAN(WBAN) [5], the IEEE 802.15 standards [6] for Internet ofThings (IoT) protocols, which include low data rate wirelesspersonal area networks (WPAN) such as Bluetooth, ZigBee, andWireless HART, can be used with communication speeds in theorder of a few Mb/s.
Intrabody communication (IBC) is short-range communication inside the human body, and allows wireless connection of
sensors on/off the human body [7]. IBC can be deployed using
a number of different techniques, such as galvanic coupling,
capacitive coupling, ultrasound, and resonant coupling [8]. Mostof these IBC techniques suffer from low bandwidth and shorttransmission distances although ultrasound can reach tens ofMb/s over very short distances [9], and capacitive coupling up to
150 Mb/s [10] using custom CMOS transceiver circuit designs.
However, for capacitive coupling, a path through external groundis needed, thus the modification of the surroundings becomes
essential.
Brain-computer interfaces (BCI) provide a direct communication link between the brain and an external device. BCI canbe used to record, decode and stimulate neural activity, treat
neurological disorders and restore lost functions in patients,
such as allowing a person to control robotic arms or to generate
synthetic speech with just their thoughts [11]. B-CRATOS —“Wireless Brain-Connect inteRfAce TO machineS” [12] — isan EU H2020 FET Open project that defines a new paradigm
for future Brain-Machine interfaces by supporting wireless highdata rate, low-latency two-way communication to establish realtime communication for streaming motor cortex data (read data
rate >32 Mb/s) between brain and a peripheral prosthetic andfrom prosthetic proprioceptive sensors (write data rate >2 Mb/s)
to somatosensory cortex using the Utah array from Blackrock
Neurotech.

I© 2023 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see
https://creativecommons.org/licenses/by/4.0/

90IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 71, NO. 1, JANUARY 2024

TABLE IHT MCS DATA RATES IN IEEE 802.11N FOR A SINGLE SPATIAL STREAM
WITH A GUARD INTERVAL OF 800 NS

design of a shielded chamber for the phantom measurements
is discussed in Section II-C, and in Section II-D and II-E, thetools and procedures for the RF characterization and WLAN
measurements are described.
A. Antennas

Fat-IBC [13] is a novel technique that can be used to connect
devices wirelessly using microwave transmission through thehuman body fat layer, sandwiched between skin and muscle. Dueto the lower relative permittivity and losses of fat with respect
to skin and muscle [14], the fat layer can act as a waveguide formicrowave transmissions and support low-loss communication
for implantable and wearable body networks. The RF smallsignal characteristics show that the fat channel can be used atleast up to 8 GHz without any significant increase in insertion
loss [15], [16].
To reach a data speed >32 Mb/s with Fat-IBC, wireless LAN(WLAN, i.e. the IEEE 802.11 group of standards [17]) together
with 4 G and low/midband 5 G are viable alternatives among
the established communication standards. To reach 64 Mb/s, weneed to target IEEE 802.11n or higher [18].
The modulation coding scheme (MCS) systems in theIEEE 802.11 protocols define various combinations of parameters that together result in data rates of varying speed. The
IEEE 802.11n standard defines eight MCS indices for the“high throughput” (HT) data rates with channel bandwidthsof 20 MHz (HT20) and 40 MHz (HT40) in the 2.4 GHz
band [19].
Table I lists the HT data rates (for the case of a single spatial
stream with the default guard interval of 800 ns). For 64 Mb/s
with HT20, we need to reach the highest modulation rate (64QAM) and coding to achieve speeds faster than 64 Mb/s. If a
40 MHz bandwidth (HT40) can be used, such speeds can bereached already with 16-QAM.
Although the potential of Fat-IBC for intrabody communication has been demonstrated using small-signal characterizationand low-speed data packet transmission [20], high-speed digital
data communication through this link has yet to be demonstrated.
This article aims to explore Fat-IBC as a communication linkwith both inbody (implanted) and onbody (on the skin) antennas
in the 2.4 GHz band inside the body, with the goal to reach
64 Mb/s end-to-end data communication.
II. MATERIALS AND METHODS
To evaluate the potential of using Fat-IBC for high-speed
data transmission, we used two types of antennas, as described in Section II-A, and three-layer phantoms that model
the skin/fat/muscle layers, as described in Section II-B. The

Two types of antennas were used in this study. To emulate
inbody (implanted) antennas, topology-optimized planar antennas (TOPA) similar to Asan, et al. [21] were used, with the
impedance of the TOPA matched to that of the fat tissue for
the R-band frequencies (1.7–2.6 GHz) [22]. For the onbody (onthe skin) antennas, we used a ring-shaped antenna design basedon the gap-coupled concentric annular ring microstrip antenna(ARMSA) concept, as described by Kanaujia et al. [23]. The FR4material, with a dielectric constant of 4.4, a loss tangent of 0.02,
and a height of 1.6 mm, was chosen for its cost-effectivenessand favorable electrical properties. The antenna was encapsulated within a layer of polydimethylsiloxane (PDMS) to ensure
biocompatibility. Electromagnetic simulations were performed
using a three-layered human tissue model to optimize the antenna’s performance at the desired frequency of 2.45 GHz.
B. Fat-IBC Phantoms
This study uses phantoms with three layers, emulating skin,fat, and muscle, respectively. The phantoms are designed for
500 MHz–20 GHz frequency range and manufactured fromsemi-solid, low water content structures designed to emulate
the properties of real human tissues according to the recipesin [24], [25]. The muscle and skin layers of the phantoms were
fabricated in a clean room environment. The materials usedwere DI-water, n-propanol, canola oil, kerosene, gelatin, TX151, surfactant, glycerine, dextrin, corn starch, salt, and sodium
benzoate. The material compositions of the layers were varied toobtain diverse dielectric properties, which were measured using
a Keysight 85070E slim probe [26]. The measurements were ingood agreement with the reference data from the Istituto di Fisica
Applicata “Nello Carrara” (IFAC) database for the 2.45 GHz
frequency, which provides a benchmark for dielectric propertiesof biological tissues [14].
The tissues have low water contents, therefore the phantoms
can be stored for long periods of time without drying out. For the
fat layer, we employed vulcanized rubber with similar dielectric
properties to human fat tissue, i.e. relative permittivity of 5.28
and conductivity of 0.1 S/m. Three-layer phantoms of 10, 20,
and 30 cm were fabricated. The widths of all phantoms were
58 mm, the fat and muscle layer heights were 30 mm each, andthe skin layer was approximately 2 mm thick. The dimensions
are similar to our previous work [15], except that we earlier onlyused phantoms up to a length of 10 cm.
To assess the data transmission within the fat, three cases withdifferent antenna configurations, as shown in Fig. 1, were used.
1) Case 1, Inbody-to-Inbody Antennas: The TOPA antennas were used to emulate inbody (implanted) antennas, placedon both sides of the phantom, providing a good coupling of
the signal from the antennas to the fat layer. The experimental
setup is shown in Fig. 1(a) with fat channel lengths of 10, 20,

RANGAIAH et al.: 92MB/S FAT-INTRABODY COMMUNICATION (FAT-IBC) WITH LOW-COST WLAN HARDWARE

91

Fig. 1. Antenna connections to the phantoms: (a) Case 1: inbody-toinbody antennas, (b) Case 2: inbody-to-onbody antennas, (c) Case 3:
onbody-to-onbody antennas.

Fig. 3. Longitudinal-cutplane view of the simulated 3D electric field
distribution at 2.45 GHz for Case 1 with a 30 cm phantom: (a) without
the shielded chamber and wall and (b) with the shielded chamber andwall. The scale is clamped at 0 dB (V/m) and 50 dB (V/m).

Fig. 2. A conceptual model of the shielded chamber, with two TOPAs
and a phantom.

and 30 cm. The TOPAs have to be carefully aligned with thephantom to avoid signal loss.
2) Case 2, Inbody-to-Onbody Antennas: For this case, a
TOPA to an onbody antenna configuration was used. However,signal coupling to the Fat-IBC channel with the onbody antennais less efficient than with an inbody antenna. The experimental
setup is illustrated in Fig. 1(b), with phantom lengths of 10, 20,
and 30 cm.
3) Case 3, Onbody-to-Onbody Antennas: For the thirdcase, both antennas were onbody antennas. The experimental
setup is illustrated in Fig. 1(c), with phantom lengths of 10, 20,
and 30 cm.
C. Design of a Shielded Chamber for Phantom
Measurements
To reduce external interference, we used a shielded chamber,as sketched in Fig. 2. The chamber includes a wall to suppress
surface waves, mainly at the air-skin interface. Interference fromsurface waves, as secondary (undesired) propagation paths, is
expected to be more prominent for Case 2 and Case 3 due to theonbody antennas. With the separation wall, such surface waves
are reduced for all cases equally [27].

The chamber consists of two rectangular cuboid-like 3Dprinted plastic structures, parted by the removable separation
wall. All internal faces of the cuboids and lateral faces of theseparation wall are covered with high-loss 15-mm thick foam
microwave absorbers (EA-LF500-24). The separation wall has
overall dimensions of 18 × 15 × 2.5 cm, and protrudes slightly
from the cuboids. A section at the bottom part of the separationwall is cut to fit the three-layer phantom. The external facesof the chamber are clad with a 30-µm thick aluminium foil toenhance shielding efficiency.
To illustrate the shielding ability of the chamber, we used
CST Microwave Studio 2021 to simulate the 3D electric field
distribution for two instances of Case 1: one with the shieldedchamber and wall and the other without them. The simulations
included the TOPAs and a 30-cm phantom and were done withan “open” boundary. The phantoms were modelled based ondispersion data in the IFAC database [14].
To demonstrate the suppression ability of the wall, the suppression of a space wave and reduction of a surface wave whencomparing the shielded and unshielded cases can clearly be seenin Fig. 3.
D. Radio Equipment and Parameter Settings
Using the shielded chamber with the different phantoms andantenna combinations, the coupling of the signal from the antennas to the fat channel and the losses through the channel were
evaluated by small-signal scattering parameters (s-parameters)

92IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 71, NO. 1, JANUARY 2024

Fig. 4. Shielded chamber with one chamber segment at the side,
exposing the three-layer phantom and one of the TOPAs inside. In front
are the two Raspberry Pis inside aluminum-clad cases.

between 2 and 3 GHz using a Keysight N9918 A Fieldfox microwave analyzer. Scattering parameters can be effectively used
for the Fat-IBC channel characterisation since the anatomical
lengths are in the accessible range of any multiport network
analyzer. This provides better accuracy in measurements unlike
traditional antenna communication link measurements where
two independent transmitter and receiver systems are used.
To evaluate the antennas/fat channel performance with modulated signals, we used Rohde & Schwarz (R&S) SMCV100B
vector signal generator (VSG) and FSVA3000 vector signal
and spectrum analyzer (VSA). Measurements of bit error rate
(BER) vs. normalized SNR (Eb /N0 ) were used to compare
performance of different digital modulation schemes.
A 1 MSamples/s PRBS 9-encoded data stream with an RRC
filter setting of 0.22 was used with all digital modulation formats(BPSK to 512-QAM, IEEE 802.11n uses up to 64-QAM). The
output power of the VSG was set to 10 dBm at the 2.45 GHz
target frequency. The Eb /N0 using added additive white Gaussian noise (AWGN) was swept and the BER down to 10−6 wasrecorded for the different modulations.
E. IEEE 802.11n Link
For the 802.11n link, we utilized two Raspberry Pi Compute
Module 4 units (CM4102008) [28]. This particular Raspberry
Pi model is equipped with a wireless module based on the
Cypress Semiconductor CYW43455 [29], which — unlike thewireless module on the ordinary Raspberry Pi 4 — has a U.FL
connector for an external antenna. A “DFRobot IoT Carrier
Board Mini” expansion board provided power and a gigabit
Ethernet connection, which was used to communicate with ahost computer.
RF leakage from the U.FL connector and adapter cable was
identified as a possible concern. To address this, the units
were mounted in 3D-printed cases wrapped in a 30-µm thickaluminum sheet. Each case was then placed on an absorbersheet, with another absorber sheet on top. The U.FL-to-SMA
connections were also wrapped with the aluminum sheet.

Raspberry Pi OS Lite version 10 (32-bit, Linux kernel version
5.10.103) was installed on the on-board storage. The host accesspoint daemon (Hostapd) software was used on one Raspberry
Pi to broadcast a service set identifier (SSID), with which thesecond Raspberry Pi joined the network. The Hostapd (version
2.9) source code was modified to allow 40 MHz bandwidths in
the 2.4 GHz band regardless of any surrounding interference
from overlapping stations (which technically violates IEEE
802.11-2012, 10.14.3.2). We specified the desired wireless channel and activated the HT20 and HT40 capabilities in the Hostapd
configuration file. The data rate was measured with the “Iperf3”
tool in User Datagram Protocol (UDP) mode as an average of anumber of measurements performed within a time duration of
60 seconds (block size 1448 bytes).
The radio transmission power and guard interval length were
set in firmware with the help of the “WL” command-line toolfrom Cypress Semiconductor [30], after which we recorded theauto-negotiated data rate and its associated HT MCS settingwith Iperf3. Similarly, the achieved data rate at HT MCS 0–7
was recorded in the same way, with the “WL” tool “forcing” theradio to operate in a specific HT MCS mode.
III. RESULTS
In this section, the performance of the Fat-IBC link for highspeed data transmission using different antenna combinations
is evaluated using s-parameter measurements, modulated highspeed data measurements, and creating a WLAN link throughthe Fat-IBC material using two Raspberry Pis connected tothe inbody and onbody antennas. All radio measurements used
the same experimental setup (phantoms and shielded chamber)
except for the length of the phantoms (10, 20, 30 cm) and theantennas (onbody and inbody) combinations.
Fig. 4 shows the actual measurement setup with the shieldedchamber (here opened for inspection), a phantom, and a TOPA.
A. Case 1: Inbody-to-Inbody Antennas
Fig. 5(a) and (b), show the measured input (s11 ) and output(s22 ) reflection coefficients for the implant-to-implant antennaconfiguration. These parameters are used to estimate the matching or the effectiveness of the energy coupling of the signal fromthe antenna to the fat layer. The values below –25 dB indicate
excellent coupling for the 10 cm and 20 cm phantoms. For the
30 cm phantom, while still below –15 dB, the measured s11
and s22 indicate a slightly higher level of impedance mismatch.
Fig. 5(c) shows the transmission coefficient (s21 ), which isinterpreted as the signal loss in the fat channel. It scales almost
linearly (in dB) as 1 dB/cm loss at the target frequency 2.45 GHz,
consistent with our previous observations [15].
The radio link performance, measured as described in Section II-D, for different modulation schemes are shown in Fig. 6
for the 30 cm phantom (the shorter phantoms showed almost
identical performance). We could reach BER < 10−6 for all
tested modulations.
To test the performance using an established wireless communication standard and tools, we measured the fat-channel link
performance with an IEEE 802.11n network as described inRANGAIAH et al.: 92MB/S FAT-INTRABODY COMMUNICATION (FAT-IBC) WITH LOW-COST WLAN HARDWARE

Fig. 6.

93Case 1: BER vs. Eb /N0 for different modulation schemes.

Fig. 7. Case 1: Date rate vs. MCS index for bandwidths of 20 MHz and
40 MHz, 30 cm phantom length.

Fig. 5. Case 1: (a) input reflection coefficient (s11 ), (b) output reflection
coefficient (s22 ), (c) transmission coefficient (s21 ) for the three different
phantom lengths.

Section II-E. By connecting the two Raspberry Pis to the different antenna combinations, a local auto-negotiating peer-to-peer
network was created. For the 30 cm phantom with the implanted
antennas inside the shielded chamber, we obtained a 91.6 Mb/slink (MCS 7, HT40).
We also swept MCS, forcing the modulation settings for 20
and 40 MHz bandwidths. The resulting data rates are shown in
Fig. 7. For 20 MHz bandwidth, we obtained up to 58.0 Mb/s,
while increasing the bandwidth to 40 MHz saw the data rate
saturate at 92 Mb/s for MCS 5–7 (64-QAM).
B. Case 2: Inbody-to-Onbody Antennas
Fig. 8 shows the measured s11 and s22 parameters for theinbody-to-onbody antenna configuration. The input (s11 ) andoutput (s22 ) reflection coefficients are now asymmetrical, withhigh reflection coefficients for port 2, which is the onbody
antenna. s11 shows a good coupling using the implanted antenna(less than –15 dB), while the s22 , the onbody antenna shows

reduced coupling (–4 dB) to the fat layer. The s21 , Fig. 8(c)shows losses at 2.45 GHz proportional to the phantom lengths,
similar to the inbody-to-inbody antennas but with higher fixed
losses because of the less good coupling (s22 ) from the onbody
antenna to the phantom.
The radio link performance, Fig. 9, is almost identical tothe implant-to-implant case, although at 512-QAM, the performance deteriorates at low BER.
When connecting the two Raspberry Pis to the inbody/onbody
antennas, an almost identical link speed of 91.8 Mb/s (MCS 7,
HT40) as the inbody-to-inbody case (91.6 Mb/s) was obtained.
Sweeping the MCS for 20 and 40 MHz bandwidth, as shownin Fig. 10, shows similar performance to the previous case,with almost 60 Mb/s performance for 20 MHz bandwidth,and around 92 Mb/s using MCS 5–7 (64-QAM) at 40 MHz
bandwidth.
C. Case 3: Onbody-to-Onbody Antennas
The s-parameters for the case with dual onbody antennas
show not so good coupling to the skin/fat/muscle phantom, as
evident from Fig. 11, which also cancels out possible variationsof matching to the different phantoms of different lengths. The
s21 , Fig. 11(b), again scales reasonably well with the phantom
length.
The radio link performance, Fig. 12(c), shows clear degradation of BER with the 30 cm phantom for 32-QAM andhigher-order modulations. In comparison, the 20 cm phantom,
Fig. 12(b), shows some degradation for 128-QAM and higher

94IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 71, NO. 1, JANUARY 2024

Fig. 10. Case 2: Date rate vs. MCS index for bandwidths of 20 MHz
and 40 MHz, 30 cm phantom length.

Fig. 8. Case 2: inbody-to-onbody antennas: (a) input reflection coefficient (s11 ), (b) output reflection coefficient (s22 ), (c) transmission
coefficient (s21 ) for the three different phantom lengths.
Fig. 11. Case 3: onbody-to-onbody antennas: (a) input reflection coefficient (s11 ) and output reflection coefficient (s22 ), (b) transmission
coefficient (s21 ) for the three different phantom lengths.

For the Raspberry Pi link speed, also for this case it waspossible to achieve a link speed of 91.6 Mb/s (MCS 7, HT40).
Sweeping the MCS for 20 and 40 MHz bandwidth, as shownin Fig. 13, shows similar performance as the previous cases,
with 58 Mb/s performance for 20 MHz bandwidth, and 92 Mb/s
using MCS 5–7 (64-QAM) at 40 MHz bandwidth.
IV. DISCUSSION
Fig. 9.

Case 2: BER vs. Eb /N0 for different modulation schemes.

modulation, while the 10 cm phantom, Fig. 12(a), shows good
performance for all modulations. Considering the losses in thelink through the different phantoms and the settings of the signal
analyzer during the measurements, this degradation is likely due
to too weak input signal for the analyzer to correctly demodulate
the received signals.

The small-signal characterization of the phantoms with thedifferent antenna combinations shows a loss for microwave
signal of around 1 dB/cm in the fat channel. The inbody antennas
give excellent coupling to the fat channel, while the onbody (onthe skin) antennas need to be improved to better couple the signal
to/from the fat channel without high insertion losses.
The BER measurements show that, except when using dual
on-body antennas with the longer phantoms, the Fat-IBC link isvery linear and can handle modulations as complex as 512-QAM
without any significant degradation of the BER.

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95

TABLE IICOMPARISON WITH OTHER SIMILAR INBODY COMMUNICATION

Fig. 13. Case 3: Date rate vs. MCS index for bandwidths of 20 MHz
and 40 MHz, 30 cm phantom length.

Fig. 12. Case 3: BER vs. Eb /N0 for different modulation schemes:(a) 10 cm phantom length, (b) 20 cm phantom length, (c) 30 cm phantom
length.

For the high-speed data communication, the throughput saturates at 92 Mb/s for all different phantoms and antenna combinations (Figs. 7, 10, and 13). This is not the upper limit according to
the IEEE 802.11n standard, see Table I, but the SDIO interface
on the CYW43455 wireless module likely limits the throughput [29]. The results show that a Fat-IBC link, using low-cost
off-the-shelf hardware and established IEEE 802.11 wirelesscommunication, can achieve high-speed data communication

within the body, and the data rate is among the fastest measured
with intrabody communication. Table II shows a comparison
with other similar inbody communication.
For the case with onbody antennas using the longest phantomof 30 cm, from the BER measurements plot, Fig. 12(a), one
would think that there would be a degradation in the full linkspeed, but a WLAN link speed of 92 Mb/s data using 64-QAM
modulation at 40 MHz bandwidth was still achieved for thiscase. In fact, the BER measurements (see Section II-D) were
performed with a generic 1 MSamples/s data stream without
any advanced coding or error correction that otherwise would
be present in an actual IEEE 802.11n system [33], so the BER
results may not in this case be a clear indication on the achievabledata rate when used with a full IEEE 802.11n system.
For the used phantoms and antennas, we did not observea limitation in the obtained link speed for IEEE 802.11n that
could be correlated to the antennas or length of the phantoms.
By using only the inbody antennas (Case 1), 30 dB is gainedin the link budget compared to the onbody antennas (Case 3),
which would extend the possible link distance by 30 cm. As thelosses are proportional to the phantom length, by increasing thetransmitted power, the fat channel length may also be extended
proportionally without degrading the throughput, while considering applicable specific absorption rate (SAR) limitations.

V. SUMMARY, FUTURE WORKIn this article, we have explored Fat-IBC as a wireless communication link for high-speed intrabody communication (IBC)
using inbody (implanted) topology-optimized planar antennas(TOPAs) and ring-shaped onbody (on the skin) antennas.

96IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 71, NO. 1, JANUARY 2024

The signal properties of the antennas and the link at microwave frequencies were characterized by s-parameter measurements. BER measurements were used to show that, except
when using dual on-body antennas with the longer phantoms,
the Fat-IBC link is very linear and can handle modulations ascomplex as 512-QAM without any sigificant degradation of the
BER.
To reach 64 Mb/s data communication speed, IEEE 802.11n
wireless communication in the 2.4 GHz band was used toestablish a link inside the body, emulated by phantoms ofdifferent lengths, and measured in a shielded chamber to suppress unwanted propagation paths and interference from externalsources.
For all antenna combinations and phantoms lengths, linkspeeds of 92 Mb/s were achieved using the 40 MHz bandwidth
provided by the IEEE 802.11n standard, which is among thehighest speed measured with intrabody communication, andmost likely limited by the used radio circuits. This shows that
Fat-IBC, using low-cost off-the-shelf hardware and establishedIEEE 802.11 wireless communication, can achieve high-speed
data communication with intrabody communication for wearable and implantable sensor networks.
Future work includes similar experiments at 5.8 GHz (i.e.
IEEE 802.11ac) and larger bandwidths, increased transmit
power, optimized onbody antennas, and other phantoms withdifferent geometries to explore the limits of Fat-IBC communication.
ACKNOWLEDGMENT
The authors would like to thank Rohde & Schwarz Sverige AB
for access to the vector signal instruments, and Bappaditya Mandal and Arvind Selvan Chezhian for their significant involvementin the experimental setup. The authors are also thankful to Roger
L. Karlsson for his valuable comments on the manuscript.
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