411 research outputs found
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
Exploiting Full-duplex Receivers for Achieving Secret Communications in Multiuser MISO Networks
We consider a broadcast channel, in which a multi-antenna transmitter (Alice)
sends confidential information signals to legitimate users (Bobs) in
the presence of eavesdroppers (Eves). Alice uses MIMO precoding to generate
the information signals along with her own (Tx-based) friendly jamming.
Interference at each Bob is removed by MIMO zero-forcing. This, however, leaves
a "vulnerability region" around each Bob, which can be exploited by a nearby
Eve. We address this problem by augmenting Tx-based friendly jamming (TxFJ)
with Rx-based friendly jamming (RxFJ), generated by each Bob. Specifically,
each Bob uses self-interference suppression (SIS) to transmit a friendly
jamming signal while simultaneously receiving an information signal over the
same channel. We minimize the powers allocated to the information, TxFJ, and
RxFJ signals under given guarantees on the individual secrecy rate for each
Bob. The problem is solved for the cases when the eavesdropper's channel state
information is known/unknown. Simulations show the effectiveness of the
proposed solution. Furthermore, we discuss how to schedule transmissions when
the rate requirements need to be satisfied on average rather than
instantaneously. Under special cases, a scheduling algorithm that serves only
the strongest receivers is shown to outperform the one that schedules all
receivers.Comment: IEEE Transactions on Communication
Distributed Linear Precoding and User Selection in Coordinated Multicell Systems
In this manuscript we tackle the problem of semi-distributed user selection
with distributed linear precoding for sum rate maximization in multiuser
multicell systems. A set of adjacent base stations (BS) form a cluster in order
to perform coordinated transmission to cell-edge users, and coordination is
carried out through a central processing unit (CU). However, the message
exchange between BSs and the CU is limited to scheduling control signaling and
no user data or channel state information (CSI) exchange is allowed. In the
considered multicell coordinated approach, each BS has its own set of cell-edge
users and transmits only to one intended user while interference to
non-intended users at other BSs is suppressed by signal steering (precoding).
We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF)
and Distributed Virtual Signal-to-Interference-plus-Noise Ratio (DVSINR).
Considering multiple users per cell and the backhaul limitations, the BSs rely
on local CSI to solve the user selection problem. First we investigate how the
signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs affect
the effective channel gain (the magnitude of the channels after precoding) and
its relationship with multiuser diversity. Considering that user selection must
be based on the type of implemented precoding, we develop metrics of
compatibility (estimations of the effective channel gains) that can be computed
from local CSI at each BS and reported to the CU for scheduling decisions.
Based on such metrics, we design user selection algorithms that can find a set
of users that potentially maximizes the sum rate. Numerical results show the
effectiveness of the proposed metrics and algorithms for different
configurations of users and antennas at the base stations.Comment: 12 pages, 6 figure
A Hierarchical Rate Splitting Strategy for FDD Massive MIMO under Imperfect CSIT
In a multiuser MIMO broadcast channel, the rate performance is affected by
the multiuser interference when the Channel State Information at the
Transmitter (CSIT) is imperfect. To tackle the interference problem, a
Rate-Splitting (RS) approach has been proposed recently, which splits one
user's message into a common and a private part, and superimposes the common
message on top of the private messages. The common message is drawn from a
public codebook and should be decoded by all users. In this paper, we propose a
novel and general framework, denoted as Hierarchical Rate Splitting (HRS), that
is particularly suited to FDD massive MIMO systems. HRS simultaneously
transmits private messages intended to each user and two kinds of common
messages that can be decoded by all users and by a subset of users,
respectively. We analyse the asymptotic sum rate of HRS under imperfect CSIT. A
closed-form power allocation is derived which provides insights into the
effects of system parameters. Finally, simulation results validate the
significant sum rate gain of HRS over various baselines.Comment: Accepted paper at IEEE CAMAD 201
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