24,570 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
Coordinated user scheduling in the multi-cell MIMO downlink
We propose a novel, coordinated user scheduling (CUS) algorithm for inter-cell interference (ICI) mitigation in the downlink of a multi-cell multi-user MIMO system. In the proposed algorithm, ICI mitigation is performed through the exchange of necessary channel state information (CSI) among the base stations, and the revision of the scheduling decisions and beamformer designs at each base station. Furthermore, ICI mitigation is performed only for the cell-edge users so that the amount of inter-base station signaling overhead is minimized. Our simulation results demonstrate that the proposed coordination scheduling algorithm significantly improves the cell-edge users' throughput compared to conventional systems with only a negligible amount of CSI sharing among the base stations and a relatively small throughput loss for the cell-interior users
Quasi-Dynamic Frame Coordination For Ultra- Reliability and Low-Latency in 5G TDD Systems
The fifth generation (5G) mobile technology features the ultra-reliable and
low-latency communications (URLLC) as a major service class. URLLC applications
demand a tight radio latency with extreme link reliability. In 5G dynamic time
division duplexing (TDD) systems, URLLC requirements become further challenging
to achieve due to the severe and fast-varying cross link interference (CLI) and
the switching time of the radio frame configurations (RFCs). In this work, we
propose a quasi-dynamic inter-cell frame coordination algorithm using hybrid
frame design and a cyclic-offset-based RFC code-book. The proposed solution
adaptively updates the RFCs in time such that both the average CLI and the
user-centric radio latency are minimized. Compared to state-of-the-art dynamic
TDD studies, the proposed scheme shows a significant improvement in the URLLC
outage latency, i.e., 92% reduction gain, while boosting the cell-edge capacity
by 189% and with a greatly reduced coordination overhead space, limited to
B-bit
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
Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks
In the context of resource allocation in cloud-radio access networks, recent
studies assume either signal-level or scheduling-level coordination. This
paper, instead, considers a hybrid level of coordination for the scheduling
problem in the downlink of a multi-cloud radio-access network, as a means to
benefit from both scheduling policies. Consider a multi-cloud radio access
network, where each cloud is connected to several base-stations (BSs) via high
capacity links, and therefore allows joint signal processing between them.
Across the multiple clouds, however, only scheduling-level coordination is
permitted, as it requires a lower level of backhaul communication. The frame
structure of every BS is composed of various time/frequency blocks, called
power-zones (PZs), and kept at fixed power level. The paper addresses the
problem of maximizing a network-wide utility by associating users to clouds and
scheduling them to the PZs, under the practical constraints that each user is
scheduled, at most, to a single cloud, but possibly to many BSs within the
cloud, and can be served by one or more distinct PZs within the BSs' frame. The
paper solves the problem using graph theory techniques by constructing the
conflict graph. The scheduling problem is, then, shown to be equivalent to a
maximum-weight independent set problem in the constructed graph, in which each
vertex symbolizes an association of cloud, user, BS and PZ, with a weight
representing the utility of that association. Simulation results suggest that
the proposed hybrid scheduling strategy provides appreciable gain as compared
to the scheduling-level coordinated networks, with a negligible degradation to
signal-level coordination
Joint Scheduling and Power Control in Coordinated Multi-Point Clusters
In this paper, we address the problem of designing a joint scheduling and power control algorithm in a downlink coordinated multi-point (CoMP) cluster supporting CoMP joint transmission. The objective is to maximize the cell-edge throughput under per-point power constraints. By an analytical derivation, binary power control is proved to be the optimal solution for any given selected user group. Utilizing this analytical result, a centralized and a semi-distributed version of joint user selection and power control algorithms are proposed. Compared to algorithms without considering joint transmission and algorithms without considering power control, simulation results show that the proposed algorithms achieve a good trade-off between joint transmission and interference coordination, which helps to improve the cell-edge performance
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