126 research outputs found
Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection
This paper studies energy-efficient coordinated beamforming in multi-cell
multi-user multigroup multicast multiple-input single-output systems. We aim at
maximizing the network energy efficiency by taking into account the fact that
some of the radio frequency chains can be switched off in order to save power.
We consider the antenna specific maximum power constraints to avoid non-linear
distortion in power amplifiers and user-specific quality of service (QoS)
constraints to guarantee a certain QoS levels. We first introduce binary
antenna selection variables and use the perspective formulation to model the
relation between them and the beamformers. Subsequently, we propose a new
formulation which reduces the feasible set of the continuous relaxation,
resulting in better performance compared to the original perspective
formulation based problem. However, the resulting optimization problem is a
mixed-Boolean non-convex fractional program, which is difficult to solve. We
follow the standard continuous relaxation of the binary antenna selection
variables, and then reformulate the problem such that it is amendable to
successive convex approximation. Thereby, solving the continuous relaxation
mostly results in near-binary solution. To recover the binary variables from
the continuous relaxation, we switch off all the antennas for which the
continuous values are smaller than a small threshold. Numerical results
illustrate the superior convergence result and significant achievable gains in
terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International
Workshop on 5G RAN Desig
General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-valued OSTBC
In this paper we consider optimal multiuser downlink beamforming in the
presence of a massive number of arbitrary quadratic shaping constraints. We
combine beamforming with full-rate high dimensional real-valued orthogonal
space time block coding (OSTBC) to increase the number of beamforming weight
vectors and associated degrees of freedom in the beamformer design. The
original multi-constraint beamforming problem is converted into a convex
optimization problem using semidefinite relaxation (SDR) which can be solved
efficiently. In contrast to conventional (rank-one) beamforming approaches in
which an optimal beamforming solution can be obtained only when the SDR
solution (after rank reduction) exhibits the rank-one property, in our approach
optimality is guaranteed when a rank of eight is not exceeded. We show that our
approach can incorporate up to 79 additional shaping constraints for which an
optimal beamforming solution is guaranteed as compared to a maximum of two
additional constraints that bound the conventional rank-one downlink
beamforming designs. Simulation results demonstrate the flexibility of our
proposed beamformer design
Massive MIMO Multicasting in Noncooperative Cellular Networks
We study the massive multiple-input multiple-output (MIMO) multicast
transmission in cellular networks where each base station (BS) is equipped with
a large-scale antenna array and transmits a common message using a single
beamformer to multiple mobile users. We first show that when each BS knows the
perfect channel state information (CSI) of its own served users, the
asymptotically optimal beamformer at each BS is a linear combination of the
channel vectors of its multicast users. Moreover, the optimal combining
coefficients are obtained in closed form. Then we consider the imperfect CSI
scenario where the CSI is obtained through uplink channel estimation in
timedivision duplex systems. We propose a new pilot scheme that estimates the
composite channel which is a linear combination of the individual channels of
multicast users in each cell. This scheme is able to completely eliminate pilot
contamination. The pilot power control for optimizing the multicast beamformer
at each BS is also derived. Numerical results show that the asymptotic
performance of the proposed scheme is close to the ideal case with perfect CSI.
Simulation also verifies the effectiveness of the proposed scheme with finite
number of antennas at each BS.Comment: to appear in IEEE JSAC Special Issue on 5G Wireless Communication
System
Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems
In this paper, we consider the problem of achieving max-min fairness amongst
multiple co-channel multicast groups through transmit beamforming. We
explicitly focus on overloaded scenarios in which the number of transmitting
antennas is insufficient to neutralize all inter-group interference. Such
scenarios are becoming increasingly relevant in the light of growing
low-latency content delivery demands, and also commonly appear in multibeam
satellite systems. We derive performance limits of classical beamforming
strategies using DoF analysis unveiling their limitations; for example, rates
saturate in overloaded scenarios due to inter-group interference. To tackle
interference, we propose a strategy based on degraded beamforming and
successive interference cancellation. While the degraded strategy resolves the
rate-saturation issue, this comes at a price of sacrificing all spatial
multiplexing gains. This motivates the development of a unifying strategy that
combines the benefits of the two previous strategies. We propose a beamforming
strategy based on rate-splitting (RS) which divides the messages intended to
each group into a degraded part and a designated part, and transmits a
superposition of both degraded and designated beamformed streams. The
superiority of the proposed strategy is demonstrated through DoF analysis.
Finally, we solve the RS beamforming design problem and demonstrate significant
performance gains through simulations
Coordinated Multicast Beamforming in Multicell Networks
We study physical layer multicasting in multicell networks where each base
station, equipped with multiple antennas, transmits a common message using a
single beamformer to multiple users in the same cell. We investigate two
coordinated beamforming designs: the quality-of-service (QoS) beamforming and
the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The
goal of the QoS beamforming is to minimize the total power consumption while
guaranteeing that received SINR at each user is above a predetermined
threshold. We present a necessary condition for the optimization problem to be
feasible. Then, based on the decomposition theory, we propose a novel
decentralized algorithm to implement the coordinated beamforming with limited
information sharing among different base stations. The algorithm is guaranteed
to converge and in most cases it converges to the optimal solution. The max-min
SINR (MMS) beamforming is to maximize the minimum received SINR among all users
under per-base station power constraints. We show that the MMS problem and a
weighted peak-power minimization (WPPM) problem are inverse problems. Based on
this inversion relationship, we then propose an efficient algorithm to solve
the MMS problem in an approximate manner. Simulation results demonstrate
significant advantages of the proposed multicast beamforming algorithms over
conventional multicasting schemes.Comment: 10pages, 9 figure
Multicast Beamformer Design for MIMO Coded Caching Systems
Coded caching (CC) techniques have been shown to be conveniently applicable
in multi-input multi-output (MIMO) systems. In a -user network with spatial
multiplexing gains of at the transmitter and at every receiver, if each
user can cache a fraction of the file library, a total number of
data streams can be served in parallel. In this paper, we focus
on improving the finite-SNR performance of MIMO-CC systems. We first consider a
MIMO-CC scheme that relies only on unicasting individual data streams, and
then, introduce a decomposition strategy to design a new scheme that delivers
the same data streams through multicasting of parallel codewords. We
discuss how optimized beamformers could be designed for each scheme and use
numerical simulations to compare their finite-SNR performance. It is shown that
while both schemes serve the same number of streams, multicasting provides
notable performance improvements. This is because, with multicasting,
transmission vectors are built with fewer beamformers, leading to more
efficient usage of available power resources
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