580 research outputs found
Bit-Interleaved Coded Multiple Beamforming with Perfect Coding
When the Channel State Information (CSI) is known by both the transmitter and
the receiver, beamforming techniques employing Singular Value Decomposition
(SVD) are commonly used in Multiple-Input Multiple-Output (MIMO) systems.
Without channel coding, there is a trade-off between full diversity and full
multiplexing. When channel coding is added, both of them can be achieved as
long as the code rate Rc and the number of employed subchannels S satisfy the
condition RcS<=1. By adding a properly designed constellation precoder, both
full diversity and full multiplexing can be achieved for both uncoded and coded
systems with the trade-off of a higher decoding complexity, e.g., Fully
Precoded Multiple Beamforming (FPMB) and Bit-Interleaved Coded Multiple
Beamforming with Full Precoding (BICMB-FP) without the condition RcS<=1.
Recently discovered Perfect Space-Time Block Code (PSTBC) is a full-rate
full-diversity space-time code, which achieves efficient shaping and high
coding gain for MIMO systems. In this paper, a new technique, Bit-Interleaved
Coded Multiple Beamforming with Perfect Coding (BICMB-PC), is introduced.
BICMB-PC transmits PSTBCs through convolutional coded SVD systems. Similar to
BICMB-FP, BICMB-PC achieves both full diversity and full multiplexing, and its
performance is almost the same as BICMB-FP. The advantage of BICMB-PC is that
it can provide a much lower decoding complexity than BICMB-FP, since the real
and imaginary parts of the received signal can be separated for BICMB-PC of
dimensions 2 and 4, and only the part corresponding to the coded bit is
required to acquire one bit metric for the Viterbi decoder.Comment: accepted to conference; Proc. IEEE ICC 201
Multiple Beamforming with Perfect Coding
Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate,
nonvanishing constant minimum determinant, uniform average transmitted energy
per antenna, and good shaping. However, the high decoding complexity is a
critical issue for practice. When the Channel State Information (CSI) is
available at both the transmitter and the receiver, Singular Value
Decomposition (SVD) is commonly applied for a Multiple-Input Multiple-Output
(MIMO) system to enhance the throughput or the performance. In this paper, two
novel techniques, Perfect Coded Multiple Beamforming (PCMB) and Bit-Interleaved
Coded Multiple Beamforming with Perfect Coding (BICMB-PC), are proposed,
employing both PSTBCs and SVD with and without channel coding, respectively.
With CSI at the transmitter (CSIT), the decoding complexity of PCMB is
substantially reduced compared to a MIMO system employing PSTBC, providing a
new prospect of CSIT. Especially, because of the special property of the
generation matrices, PCMB provides much lower decoding complexity than the
state-of-the-art SVD-based uncoded technique in dimensions 2 and 4. Similarly,
the decoding complexity of BICMB-PC is much lower than the state-of-the-art
SVD-based coded technique in these two dimensions, and the complexity gain is
greater than the uncoded case. Moreover, these aforementioned complexity
reductions are achieved with only negligible or modest loss in performance.Comment: accepted to journa
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser downlink systems which
aims at creating constructive interference among the transmitted data streams.
This can be enabled by designing the precoded signal of the multiantenna
transmitter on a symbol level, taking into account both channel state
information and data symbols. Previous literature has studied this paradigm for
MPSK modulations by addressing various performance metrics, such as power
minimization and maximization of the minimum rate. In this paper, we extend
this to generic multi-level modulations i.e. MQAM and APSK by establishing
connection to PHY layer multicasting with phase constraints. Furthermore, we
address adaptive modulation schemes which are crucial in enabling the
throughput scaling of symbol-level precoded systems. In this direction, we
design signal processing algorithms for minimizing the required power under
per-user SINR or goodput constraints. Extensive numerical results show that the
proposed algorithm provides considerable power and energy efficiency gains,
while adapting the employed modulation scheme to match the requested data rate
Golden Coded Multiple Beamforming
The Golden Code is a full-rate full-diversity space-time code, which achieves
maximum coding gain for Multiple-Input Multiple-Output (MIMO) systems with two
transmit and two receive antennas. Since four information symbols taken from an
M-QAM constellation are selected to construct one Golden Code codeword, a
maximum likelihood decoder using sphere decoding has the worst-case complexity
of O(M^4), when the Channel State Information (CSI) is available at the
receiver. Previously, this worst-case complexity was reduced to O(M^(2.5))
without performance degradation. When the CSI is known by the transmitter as
well as the receiver, beamforming techniques that employ singular value
decomposition are commonly used in MIMO systems. In the absence of channel
coding, when a single symbol is transmitted, these systems achieve the full
diversity order provided by the channel. Whereas this property is lost when
multiple symbols are simultaneously transmitted. However, uncoded multiple
beamforming can achieve the full diversity order by adding a properly designed
constellation precoder. For 2 \times 2 Fully Precoded Multiple Beamforming
(FPMB), the general worst-case decoding complexity is O(M). In this paper,
Golden Coded Multiple Beamforming (GCMB) is proposed, which transmits the
Golden Code through 2 \times 2 multiple beamforming. GCMB achieves the full
diversity order and its performance is similar to general MIMO systems using
the Golden Code and FPMB, whereas the worst-case decoding complexity of
O(sqrt(M)) is much lower. The extension of GCMB to larger dimensions is also
discussed.Comment: accepted to conferenc
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
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