307 research outputs found
Power Allocation Schemes for Multicell Massive MIMO Systems
This paper investigates the sum-rate gains brought by power allocation
strategies in multicell massive multipleinput multiple-output systems, assuming
time-division duplex transmission. For both uplink and downlink, we derive
tractable expressions for the achievable rate with zero-forcing receivers and
precoders respectively. To avoid high complexity joint optimization across the
network, we propose a scheduling mechanism for power allocation, where in a
single time slot, only cells that do not interfere with each other adjust their
transmit powers. Based on this, corresponding transmit power allocation
strategies are derived, aimed at maximizing the sum rate per-cell. These
schemes are shown to bring considerable gains over equal power allocation for
practical antenna configurations (e.g., up to a few hundred). However, with
fixed number of users (N), these gains diminish as M turns to infinity, and
equal power allocation becomes optimal. A different conclusion is drawn for the
case where both M and N grow large together, in which case: (i) improved rates
are achieved as M grows with fixed M/N ratio, and (ii) the relative gains over
the equal power allocation diminish as M/N grows. Moreover, we also provide
applicable values of M/N under an acceptable power allocation gain threshold,
which can be used as to determine when the proposed power allocation schemes
yield appreciable gains, and when they do not. From the network point of view,
the proposed scheduling approach can achieve almost the same performance as the
joint power allocation after one scheduling round, with much reduced
complexity
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
Impact of User Mobility on Optimal Linear Receivers in Cellular Networks
We consider the uplink of non-cooperative multi-cellular systems deploying
multiple antenna elements at the base stations (BS), covering both the cases of
conventional and very large number of antennas. Given the inevitable pilot
contamination and an arbitrary path-loss for each link, we address the impact
of time variation of the channel due to the relative movement between users and
BS antennas, which limits system's performance even if the number antennas is
increased, as shown. In particular, we propose an optimal linear receiver (OLR)
maximizing the received signal-to-interference-plus-noise (SINR). Closed-form
lower and upper bounds are derived as well as the deterministic equivalent of
the OLR is obtained. Numerical results reveal the outperformance of the
proposed OLR against known linear receivers, mostly in environments with high
interference and certain user mobility, as well as that massive MIMO is
preferable even in time-varying channel conditions.Comment: 3 figures, 6 pages, accepted in ICC 201
On the Performance of MRC Receiver with Unknown Timing Mismatch-A Large Scale Analysis
There has been extensive research on large scale multi-user multiple-input
multiple-output (MU-MIMO) systems recently. Researchers have shown that there
are great opportunities in this area, however, there are many obstacles in the
way to achieve full potential of using large number of receive antennas. One of
the main issues, which will be investigated thoroughly in this paper, is timing
asynchrony among signals of different users. Most of the works in the
literature, assume that received signals are perfectly aligned which is not
practical. We show that, neglecting the asynchrony can significantly degrade
the performance of existing designs, particularly maximum ratio combining
(MRC). We quantify the uplink achievable rates obtained by MRC receiver with
perfect channel state information (CSI) and imperfect CSI while the system is
impaired by unknown time delays among received signals. We then use these
results to design new algorithms in order to alleviate the effects of timing
mismatch. We also analyze the performance of introduced receiver design, which
is called MRC-ZF, with perfect and imperfect CSI. For performing MRC-ZF, the
only required information is the distribution of timing mismatch which
circumvents the necessity of time delay acquisition or synchronization. To
verify our analytical results, we present extensive simulation results which
thoroughly investigate the performance of the traditional MRC receiver and the
introduced MRC-ZF receiver
Employing Antenna Selection to Improve Energy-Efficiency in Massive MIMO Systems
Massive MIMO systems promise high data rates by employing large number of
antennas, which also increases the power usage of the system as a consequence.
This creates an optimization problem which specifies how many antennas the
system should employ in order to operate with maximal energy efficiency. Our
main goal is to consider a base station with a fixed number of antennas, such
that the system can operate with a smaller subset of antennas according to the
number of active user terminals, which may vary over time. Thus, in this paper
we propose an antenna selection algorithm which selects the best antennas
according to the better channel conditions with respect to the users, aiming at
improving the overall energy efficiency. Then, due to the complexity of the
mathematical formulation, a tight approximation for the consumed power is
presented, using the Wishart theorem, and it is used to find a deterministic
formulation for the energy efficiency. Simulation results show that the
approximation is quite tight and that there is significant improvement in terms
of energy efficiency when antenna selection is employed.Comment: To appear in Transactions on Emerging Telecommunications
Technologies, 12 pages, 8 figures, 2 table
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