797 research outputs found
Joint Design of Multi-Tap Analog Cancellation and Digital Beamforming for Reduced Complexity Full Duplex MIMO Systems
Incorporating full duplex operation in Multiple Input Multiple Output (MIMO)
systems provides the potential of boosting throughput performance. However, the
hardware complexity of the analog self-interference canceller scales with the
number of transmit and receive antennas, thus exploiting the benefits of analog
cancellation becomes impractical for full duplex MIMO transceivers. In this
paper, we present a novel architecture for the analog canceller comprising of
reduced number of taps (tap refers to a line of fixed delay and variable phase
shifter and attenuator) and simple multiplexers for efficient signal routing
among the transmit and receive radio frequency chains. In contrast to the
available analog cancellation architectures, the values for each tap and the
configuration of the multiplexers are jointly designed with the digital
beamforming filters according to certain performance objectives. Focusing on a
narrowband flat fading channel model as an example, we present a general
optimization framework for the joint design of analog cancellation and digital
beamforming. We also detail a particular optimization objective together with
its derived solution for the latter architectural components. Representative
computer simulation results demonstrate the superiority of the proposed low
complexity full duplex MIMO system over lately available ones.Comment: 8 pages, 4 figures, IEEE ICC 201
Channel correlation-based approach for feedback overhead reduction in massive MIMO
For frequency-division duplex multiple-input-multiple-output (MIMO) systems, the channel state information at the transmitter is usually obtained by sending pilots or reference signals from all elements of the antenna array. The channel is then estimated by the receiver and communicated back to the transmitter. However, for massive MIMO, this periodical estimation of the full transfer matrix can lead to prohibitive overhead. To reduce the amount of data, we propose to estimate the updated channel matrix from the knowledge of the full correlation matrix at the transmitter made during some initialization time and the instantaneous measured channel matrix of smaller size, characterizing the link between the user and a limited number of reference array elements. The proposed algorithm is validated with measured massive MIMO channel transfer functions at 3.5GHz between a uniform rectangular array and different user positions. Since measurements were made in static conditions, the criteria chosen for evaluating the performance of the algorithm are based on a comparison of the predicted channel capacity calculated from either the measured or estimated channel matrix
Energy Efficiency and Sum Rate when Massive MIMO meets Device-to-Device Communication
This paper considers a scenario of short-range communication, known as
device-to-device (D2D) communication, where D2D users reuse the downlink
resources of a cellular network to transmit directly to their corresponding
receivers. In addition, multiple antennas at the base station (BS) are used in
order to simultaneously support multiple cellular users using multiuser or
massive MIMO. The network model considers a fixed number of cellular users and
that D2D users are distributed according to a homogeneous Poisson point process
(PPP). Two metrics are studied, namely, average sum rate (ASR) and energy
efficiency (EE). We derive tractable expressions and study the tradeoffs
between the ASR and EE as functions of the number of BS antennas and density of
D2D users for a given coverage area.Comment: 6 pages, 7 figures, to be presented at the IEEE International
Conference on Communications (ICC) Workshop on Device-to-Device Communication
for Cellular and Wireless Networks, London, UK, June 201
Signal Processing in Arrayed MIMO Systems
Multiple-Input Multiple-Output (MIMO) systems, using antenna arrays at both
receiver and transmitter, have shown great potential to provide high bandwidth
utilization efficiency. Unlike other reported research on MIMO systems which
often assumes independent antennas, in this thesis an arrayed MIMO system
framework is proposed, which provides a richer description of the channel charac-
teristics and additional degrees of freedom in designing communication systems.
Firstly, the spatial correlated MIMO system is studied as an array-to-array
system with each array (Tx or Rx) having predefined constrained aperture. The
MIMO system is completely characterized by its transmit and receive array man-
ifolds and a new spatial correlation model other than Kronecker-based model is
proposed. As this model is based on array manifolds, it enables the study of the
effect of array geometry on the capacity of correlated MIMO channels.
Secondly, to generalize the proposed arrayed MIMO model to a frequency
selective fading scenario, the framework of uplink MIMO DS-CDMA (Direct-
Sequence Code Division Multiple Access) systems is developed. DOD estimation
is developed based on transmit beamrotation. A subspace-based joint DOA/TOA
estimation scheme as well as various spatial temporal reception algorithms is also
proposed.
Finally, the downlink MIMO-CDMA systems in multiple-access multipath fading channels are investigated. Linear precoder and decoder optimization problems
are studied under different criterions. Optimization approaches with different
power allocation schemes are investigated. Sub-optimization approaches with
close-form solution and thus less computation complexity are also proposed
Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
Backscatter communication (BSC) is being realized as the core technology for
pervasive sustainable Internet-of-Things applications. However, owing to the
resource-limitations of passive tags, the efficient usage of multiple antennas
at the reader is essential for both downlink excitation and uplink detection.
This work targets at maximizing the achievable sum-backscattered-throughput by
jointly optimizing the transceiver (TRX) design at the reader and
backscattering coefficients (BC) at the tags. Since, this joint problem is
nonconvex, we first present individually-optimal designs for the TRX and BC. We
show that with precoder and {combiner} designs at the reader respectively
targeting downlink energy beamforming and uplink Wiener filtering operations,
the BC optimization at tags can be reduced to a binary power control problem.
Next, the asymptotically-optimal joint-TRX-BC designs are proposed for both low
and high signal-to-noise-ratio regimes. Based on these developments, an
iterative low-complexity algorithm is proposed to yield an efficient
jointly-suboptimal design. Thereafter, we discuss the practical utility of the
proposed designs to other application settings like wireless powered
communication networks and BSC with imperfect channel state information.
Lastly, selected numerical results, validating the analysis and shedding novel
insights, demonstrate that the proposed designs can yield significant
enhancement in the sum-backscattered throughput over existing benchmarks.Comment: 17 pages, 5 figures, accepted for publication in IEEE Transactions on
Communication
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