29-01-2013, 02:52 PM
MIMO-OFDM for High Rate Underwater Acoustic Communications
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Abstract
Multiple-input multiple-output (MIMO) techniques
have been actively pursued in underwater acoustic communications
recently to increase the data rate over the bandwidth-limited
channels. In this paper, we present a MIMO system design, where
spatial multiplexing is applied with OFDM signals. The proposed
receiver works on a block-by-block basis, where null subcarriers
are used for Doppler compensation, pilot subcarriers are used
for channel estimation, and a MIMO detector consisting of a
hybrid use of successive interference cancellation and soft MMSE
equalization is coupled with LDPC channel decoding for iterative
detection on each subcarrier. The proposed design has been tested
using data recorded from three different experiments. A spectral
efficiency of 3.5 bits/sec/Hz was approached in one experiment,
while a data rate of 125.7 kb/s over a bandwidth of 62.5 kHz was
achieved in another. These results suggest that MIMO-OFDM
is an appealing solution for high data rate transmissions over
underwater acoustic channels.
INTRODUCTION
To enhance the transmission rate over communication links,
either the bandwidth, or the spectral efficiency in the unit
of bits/sec/Hz, or both, need to be increased. Multi-input
multi-output (MIMO) techniques can drastically increase the
spectral efficiency via parallel transmissions over multiple
transmitters [3], [4], hence are attractive to underwater acoustic
communications which are inherently bandwidth-limited.
Recently, several different approaches have been investigated
for MIMO underwater acoustic communications, including
those for single carrier transmissions [5]–[11] and
those for multicarrier transmissions in the form of orthogonalfrequency-
division-multiplexing (OFDM) [1], [2], [12], [13].
Specifically, adaptive multichannel decision-feedback equalization
(DFE) has been used in [5], [6]
RECEIVER ALGORITHMS
The receiver algorithms should be well designed for the
underwater acoustic communications. For stationary MIMOOFDM
tests, no resampling operation as described in [14] was
needed. The key processing steps at the receiver are depicted
in Fig. 1, and will be described next.
Doppler estimation
The channel Doppler effect can be viewed as caused by
carrier frequency offsets (CFO) among the transmitters and the
receivers [14]. On each receiver, we assume a common CFO
relative to all transmitters, as in [20, Chapter 11.5]. Hence,
the CFO estimation algorithm presented in [14, Eqns. (14)
and (15)] is directly applicable, where the energy on the null
subcarriers is used as the objective function to search for the
best CFO estimate.
After Doppler shift estimation and compensation, the average
energy on the null subcarriers is used to compute
the variance of the additive noise and residual inter-carrierinterference
(ICI). This quantity is needed for the soft MMSE
equalization in Section III-C.
PERFORMANCE RESULTS: AUV07
The experimental data for this test was collected during the
AUV Fest held in Panama City, FL, June 2007. The water
depth was 20 meters. Two transmitters were deployed about 9
meters below a surface buoy. The receiving array was about
9 meters below a boat. The vertical array was 2 meters in
aperture with 16 hydrophones, out of which we used four.
Here we report performance results for transmission distances
of 500 and 1500 meters. The key system parameters are listed
in Table I.
CFO and channel estimation
The CFO estimates are shown in Fig. 4 for one data packet
on one receiver. The CFO is within [-2, 2] Hz range, which
is caused by transmitter and receiver drifting with waves.
The estimated channel for one OFDM block is shown in
Fig. 5, which is in good agreement with the channel profiles
shown in Figs. 2 and 3. It can be seen that the channel for the
500 m case has larger energy.
With Kp/2 = 128 subcarriers for each channel estimation,
we can estimate 128 channel taps in discrete time, which
amounts to a delay spread of 10.7 ms. Any arrivals after 10.7
ms will thus be treated as additive noise. Since the channel
at 500 m has significant arrivals after 10.7 ms, the noise floor
is much higher (around 8 dB) than that at 1500 m, as shown
in Fig. 6. As a result, although the signal energy at 500 m
is greater than that at 1500 m, the pre-demodulation signal to
noise ratios (SNRs) become similar for both cases. The predemodulation
SNR is computed as the ratio of the average
signal energy on the pilot subcarriers to the average energy
on the null subcarriers.
PERFORMANCE RESULTS: RACE08
The Rescheduled Acoustic Communications Experiment
(RACE) was held in the Narragansett Bay, Rhode Island,
March 2008. The water depths in the area range from 9 to
about 14 meters. The primary source of an ITC1007 transducer
for acoustic transmissions was located approximately 4 meters
above the bottom. A vertical source array consisting of three
AT-12ET transducers with a spacing of 60 cm between each
transducer was deployed below the primary source. The top of
the source array was approximately 1 meter below the primary
source. The system parameters are listed in Table II.
PERFORMANCE RESULTS: VHF08
This experiment was conducted in the Buzzards Bay, MA,
April 2008. The water depth was 12 meters. Two transmitters
were about 6 meters below a surface buoy. The receiving array
was about 6 meters below a boat. The array was 1 meter in
aperture with 6 hydrophones. The transmission distance was
450 meters with a very high frequency (VHF) signal used. We
scale the basic design of the K = 1024 case for the AUV07
experiment to two different bandwidths: B = 31.25 kHz and
B = 62.5 kHz, following the design rules outlined in [23].
The parameters used are listed in Table VI.
CONCLUSIONS
In this paper, a MIMO-OFDM system with spatial multiplexing
was presented. The receiver works on a block-by-block
basis where null and pilot subcarriers are used for Doppler and
channel estimation, respectively, and an iterative structure is
used for MIMO detection and decoding. We reported on the
performance results based on data processing from three different
experiments, showing very high spectral efficiency via
parallel data multiplexing with high order constellations. These
example results suggest that MIMO-OFDM is an appealing
choice for high data rate underwater acoustic communications.
Further investigations on MIMO underwater acoustic communications,
both single- and multi-carrier approaches, are
warranted, especially on the capacity limits in underwater
channels, advanced receiver designs, and experimental results
in more challenging channel conditions with large Doppler
spread.