3,636 research outputs found
Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading
This paper investigates the spectral efficiency of multi-cell massive
multiple-input multiple-output systems with Ricean fading that utilize the
linear maximal-ratio combining detector. We firstly present closed-form
expressions for the effective signal-to-interference-plus-noise ratio (SINR)
with the least squares and minimum mean squared error (MMSE) estimation
methods, respectively, which apply for any number of base-station antennas
and any Ricean -factor. Also, the obtained results can be particularized in
Rayleigh fading conditions when the Ricean -factor is equal to zero. In the
following, novel exact asymptotic expressions of the effective SINR are derived
in the high and high Ricean -factor regimes. The corresponding analysis
shows that pilot contamination is removed by the MMSE estimator when we
consider both infinite and infinite Ricean -factor, while the pilot
contamination phenomenon persists for the rest of cases. All the theoretical
results are verified via Monte-Carlo simulations.Comment: 15 pages, 2 figures, the tenth International Conference on Wireless
Communications and Signal Processing (WCSP 2018), to appea
Pilot Power Allocation Through User Grouping in Multi-Cell Massive MIMO Systems
In this paper, we propose a relative channel estimation error (RCEE) metric,
and derive closed-form expressions for its expectation and
the achievable uplink rate holding for any number of base station antennas ,
with the least squares (LS) and minimum mean squared error (MMSE) estimation
methods. It is found that RCEE and converge to the same
constant value when , resulting in the pilot power
allocation (PPA) is substantially simplified and a PPA algorithm is proposed to
minimize the average per user with a total pilot power
budget in multi-cell massive multiple-input multiple-output systems.
Numerical results show that the PPA algorithm brings considerable gains for the
LS estimation compared with equal PPA (EPPA), while the gains are only
significant with large frequency reuse factor (FRF) for the MMSE estimation.
Moreover, for large FRF and large , the performance of the LS approaches to
the performance of the MMSE, which means that simple LS estimation method is a
very viable when co-channel interference is small. For the achievable uplink
rate, the PPA scheme delivers almost the same average achievable uplink rate
and improves the minimum achievable uplink rate compared with the EPPA scheme.Comment: 30 pages, 5 figures, submitted to IEEE Transactions on Communication
Power Scaling of Uplink Massive MIMO Systems with Arbitrary-Rank Channel Means
This paper investigates the uplink achievable rates of massive multiple-input
multiple-output (MIMO) antenna systems in Ricean fading channels, using
maximal-ratio combining (MRC) and zero-forcing (ZF) receivers, assuming perfect
and imperfect channel state information (CSI). In contrast to previous relevant
works, the fast fading MIMO channel matrix is assumed to have an arbitrary-rank
deterministic component as well as a Rayleigh-distributed random component. We
derive tractable expressions for the achievable uplink rate in the
large-antenna limit, along with approximating results that hold for any finite
number of antennas. Based on these analytical results, we obtain the scaling
law that the users' transmit power should satisfy, while maintaining a
desirable quality of service. In particular, it is found that regardless of the
Ricean -factor, in the case of perfect CSI, the approximations converge to
the same constant value as the exact results, as the number of base station
antennas, , grows large, while the transmit power of each user can be scaled
down proportionally to . If CSI is estimated with uncertainty, the same
result holds true but only when the Ricean -factor is non-zero. Otherwise,
if the channel experiences Rayleigh fading, we can only cut the transmit power
of each user proportionally to . In addition, we show that with an
increasing Ricean -factor, the uplink rates will converge to fixed values
for both MRC and ZF receivers
Cell-Free Massive MIMO versus Small Cells
A Cell-Free Massive MIMO (multiple-input multiple-output) system comprises a
very large number of distributed access points (APs)which simultaneously serve
a much smaller number of users over the same time/frequency resources based on
directly measured channel characteristics. The APs and users have only one
antenna each. The APs acquire channel state information through time-division
duplex operation and the reception of uplink pilot signals transmitted by the
users. The APs perform multiplexing/de-multiplexing through conjugate
beamforming on the downlink and matched filtering on the uplink. Closed-form
expressions for individual user uplink and downlink throughputs lead to max-min
power control algorithms. Max-min power control ensures uniformly good service
throughout the area of coverage. A pilot assignment algorithm helps to mitigate
the effects of pilot contamination, but power control is far more important in
that regard.
Cell-Free Massive MIMO has considerably improved performance with respect to
a conventional small-cell scheme, whereby each user is served by a dedicated
AP, in terms of both 95%-likely per-user throughput and immunity to shadow
fading spatial correlation. Under uncorrelated shadow fading conditions, the
cell-free scheme provides nearly 5-fold improvement in 95%-likely per-user
throughput over the small-cell scheme, and 10-fold improvement when shadow
fading is correlated.Comment: EEE Transactions on Wireless Communications, accepted for publicatio
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