7,170 research outputs found
Efficient Detectors for MIMO-OFDM Systems under Spatial Correlation Antenna Arrays
This work analyzes the performance of the implementable detectors for
multiple-input-multiple-output (MIMO) orthogonal frequency division
multiplexing (OFDM) technique under specific and realistic operation system
condi- tions, including antenna correlation and array configuration.
Time-domain channel model has been used to evaluate the system performance
under realistic communication channel and system scenarios, including different
channel correlation, modulation order and antenna arrays configurations. A
bunch of MIMO-OFDM detectors were analyzed for the purpose of achieve high
performance combined with high capacity systems and manageable computational
complexity. Numerical Monte-Carlo simulations (MCS) demonstrate the channel
selectivity effect, while the impact of the number of antennas, adoption of
linear against heuristic-based detection schemes, and the spatial correlation
effect under linear and planar antenna arrays are analyzed in the MIMO-OFDM
context.Comment: 26 pgs, 16 figures and 5 table
Hybrid Beamforming via the Kronecker Decomposition for the Millimeter-Wave Massive MIMO Systems
Despite its promising performance gain, the realization of mmWave massive
MIMO still faces several practical challenges. In particular, implementing
massive MIMO in the digital domain requires hundreds of RF chains matching the
number of antennas. Furthermore, designing these components to operate at the
mmWave frequencies is challenging and costly. These motivated the recent
development of hybrid-beamforming where MIMO processing is divided for separate
implementation in the analog and digital domains, called the analog and digital
beamforming, respectively. Analog beamforming using a phase array introduces
uni-modulus constraints on the beamforming coefficients, rendering the
conventional MIMO techniques unsuitable and call for new designs. In this
paper, we present a systematic design framework for hybrid beamforming for
multi-cell multiuser massive MIMO systems over mmWave channels characterized by
sparse propagation paths. The framework relies on the decomposition of analog
beamforming vectors and path observation vectors into Kronecker products of
factors being uni-modulus vectors. Exploiting properties of Kronecker mixed
products, different factors of the analog beamformer are designed for either
nulling interference paths or coherently combining data paths. Furthermore, a
channel estimation scheme is designed for enabling the proposed hybrid
beamforming. The scheme estimates the AoA of data and interference paths by
analog beam scanning and data-path gains by analog beam steering. The
performance of the channel estimation scheme is analyzed. In particular, the
AoA spectrum resulting from beam scanning, which displays the magnitude
distribution of paths over the AoA range, is derived in closed-form. It is
shown that the inter-cell interference level diminishes inversely with the
array size, the square root of pilot sequence length and the spatial separation
between paths.Comment: Submitted to IEEE JSAC Special Issue on Millimeter Wave
Communications for Future Mobile Networks, minor revisio
Uplink Linear Receivers for Multi-cell Multiuser MIMO with Pilot Contamination: Large System Analysis
Base stations with a large number of transmit antennas have the potential to
serve a large number of users at high rates. However, the receiver processing
in the uplink relies on channel estimates which are known to suffer from pilot
interference. In this work, making use of the similarity of the uplink received
signal in CDMA with that of a multi-cell multi-antenna system, we perform a
large system analysis when the receiver employs an MMSE filter with a pilot
contaminated estimate. We assume a Rayleigh fading channel with different
received powers from users. We find the asymptotic Signal to Interference plus
Noise Ratio (SINR) as the number of antennas and number of users per base
station grow large while maintaining a fixed ratio. Through the SINR expression
we explore the scenario where the number of users being served are comparable
to the number of antennas at the base station. The SINR explicitly captures the
effect of pilot contamination and is found to be the same as that employing a
matched filter with a pilot contaminated estimate. We also find the exact
expression for the interference suppression obtained using an MMSE filter which
is an important factor when there are significant number of users in the system
as compared to the number of antennas. In a typical set up, in terms of the
five percentile SINR, the MMSE filter is shown to provide significant gains
over matched filtering and is within 5 dB of MMSE filter with perfect channel
estimate. Simulation results for achievable rates are close to large system
limits for even a 10-antenna base station with 3 or more users per cell.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models
The work identifies the first general, explicit, and non-random MIMO
encoder-decoder structures that guarantee optimality with respect to the
diversity-multiplexing tradeoff (DMT), without employing a computationally
expensive maximum-likelihood (ML) receiver. Specifically, the work establishes
the DMT optimality of a class of regularized lattice decoders, and more
importantly the DMT optimality of their lattice-reduction (LR)-aided linear
counterparts. The results hold for all channel statistics, for all channel
dimensions, and most interestingly, irrespective of the particular lattice-code
applied. As a special case, it is established that the LLL-based LR-aided
linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal
decoding of any lattice code at a worst-case complexity that grows at most
linearly in the data rate. This represents a fundamental reduction in the
decoding complexity when compared to ML decoding whose complexity is generally
exponential in rate.
The results' generality lends them applicable to a plethora of pertinent
communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI,
cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality
of the LR-aided linear decoder is guaranteed. The adopted approach yields
insight, and motivates further study, into joint transceiver designs with an
improved SNR gap to ML decoding.Comment: 16 pages, 1 figure (3 subfigures), submitted to the IEEE Transactions
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