277 research outputs found
A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination
An important challenge of wireless networks is to boost the cell edge
performance and enable multi-stream transmissions to cell edge users.
Interference mitigation techniques relying on multiple antennas and
coordination among cells are nowadays heavily studied in the literature.
Typical strategies in OFDMA networks include coordinated scheduling,
beamforming and power control. In this paper, we propose a novel and practical
type of coordination for OFDMA downlink networks relying on multiple antennas
at the transmitter and the receiver. The transmission ranks, i.e.\ the number
of transmitted streams, and the user scheduling in all cells are jointly
optimized in order to maximize a network utility function accounting for
fairness among users. A distributed coordinated scheduler motivated by an
interference pricing mechanism and relying on a master-slave architecture is
introduced. The proposed scheme is operated based on the user report of a
recommended rank for the interfering cells accounting for the receiver
interference suppression capability. It incurs a very low feedback and backhaul
overhead and enables efficient link adaptation. It is moreover robust to
channel measurement errors and applicable to both open-loop and closed-loop
MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A
system is shown through system level simulations.Comment: IEEE Transactions or Wireless Communications, Accepted for
Publicatio
Large-Scale MIMO versus Network MIMO for Multicell Interference Mitigation
This paper compares two important downlink multicell interference mitigation
techniques, namely, large-scale (LS) multiple-input multiple-output (MIMO) and
network MIMO. We consider a cooperative wireless cellular system operating in
time-division duplex (TDD) mode, wherein each cooperating cluster includes
base-stations (BSs), each equipped with multiple antennas and scheduling
single-antenna users. In an LS-MIMO system, each BS employs antennas not
only to serve its scheduled users, but also to null out interference caused to
the other users within the cooperating cluster using zero-forcing (ZF)
beamforming. In a network MIMO system, each BS is equipped with only
antennas, but interference cancellation is realized by data and channel state
information exchange over the backhaul links and joint downlink transmission
using ZF beamforming. Both systems are able to completely eliminate
intra-cluster interference and to provide the same number of spatial degrees of
freedom per user. Assuming the uplink-downlink channel reciprocity provided by
TDD, both systems are subject to identical channel acquisition overhead during
the uplink pilot transmission stage. Further, the available sum power at each
cluster is fixed and assumed to be equally distributed across the downlink
beams in both systems. Building upon the channel distribution functions and
using tools from stochastic ordering, this paper shows, however, that from a
performance point of view, users experience better quality of service, averaged
over small-scale fading, under an LS-MIMO system than a network MIMO system.
Numerical simulations for a multicell network reveal that this conclusion also
holds true with regularized ZF beamforming scheme. Hence, given the likely
lower cost of adding excess number of antennas at each BS, LS-MIMO could be the
preferred route toward interference mitigation in cellular networks.Comment: 13 pages, 7 figures; IEEE Journal of Selected Topics in Signal
Processing, Special Issue on Signal Processing for Large-Scale MIMO
Communication
Autonomous Algorithms for Centralized and Distributed Interference Coordination: A Virtual Layer Based Approach
Interference mitigation techniques are essential for improving the
performance of interference limited wireless networks. In this paper, we
introduce novel interference mitigation schemes for wireless cellular networks
with space division multiple access (SDMA). The schemes are based on a virtual
layer that captures and simplifies the complicated interference situation in
the network and that is used for power control. We show how optimization in
this virtual layer generates gradually adapting power control settings that
lead to autonomous interference minimization. Thereby, the granularity of
control ranges from controlling frequency sub-band power via controlling the
power on a per-beam basis, to a granularity of only enforcing average power
constraints per beam. In conjunction with suitable short-term scheduling, our
algorithms gradually steer the network towards a higher utility. We use
extensive system-level simulations to compare three distributed algorithms and
evaluate their applicability for different user mobility assumptions. In
particular, it turns out that larger gains can be achieved by imposing average
power constraints and allowing opportunistic scheduling instantaneously, rather
than controlling the power in a strict way. Furthermore, we introduce a
centralized algorithm, which directly solves the underlying optimization and
shows fast convergence, as a performance benchmark for the distributed
solutions. Moreover, we investigate the deviation from global optimality by
comparing to a branch-and-bound-based solution.Comment: revised versio
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
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
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