1,723 research outputs found
Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference
User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the
core of high rate data-oriented downlink schemes of the next-generation of
cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users
according to their channels vector directions and SINR levels. However, when
scheduling is applied independently in each cell, the inter-cell interference
(ICI) power at each user receiver is not known in advance since it changes at
each new scheduling slot depending on the scheduling decisions of all
interfering base stations. In order to cope with this uncertainty, we consider
the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat
reQuest (ARQ). We develop a game-theoretic framework for this problem and build
on stochastic optimization techniques in order to find optimal scheduling and
ARQ schemes. Particularizing our framework to the case of "outage service
rates", we obtain a scheme based on adaptive variable-rate coding at the
physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then,
we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ)
that is able to achieve a throughput performance arbitrarily close to the
"genie-aided service rates", with no need for a genie that provides
non-causally the ICI power levels. The novel HARQ scheme is both easier to
implement and superior in performance with respect to the conventional
combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small
correction
Relay-Assisted User Scheduling in Wireless Networks with Hybrid-ARQ
This paper studies the problem of relay-assisted user scheduling for downlink
wireless transmission. The base station or access point employs hybrid
automatic-repeat-request (HARQ) with the assistance of a set of fixed relays to
serve a set of mobile users. By minimizing a cost function of the queue lengths
at the base station and the number of retransmissions of the head-of-line
packet for each user, the base station can schedule an appropriate user in each
time slot and an appropriate transmitter to serve it. It is shown that a
priority-index policy is optimal for a linear cost function with packets
arriving according to a Poisson process and for an increasing convex cost
function where packets must be drained from the queues at the base station.Comment: 14 pages, 5 figures, submitted to the IEEE Transactions on Vehicular
Technology in October 2008, revised in March 2009 and May 200
Integration of Carrier Aggregation and Dual Connectivity for the ns-3 mmWave Module
Thanks to the wide availability of bandwidth, the millimeter wave (mmWave)
frequencies will provide very high data rates to mobile users in next
generation 5G cellular networks. However, mmWave links suffer from high
isotropic pathloss and blockage from common materials, and are subject to an
intermittent channel quality. Therefore, protocols and solutions at different
layers in the cellular network and the TCP/IP protocol stack have been proposed
and studied. A valuable tool for the end-to-end performance analysis of mmWave
cellular networks is the ns-3 mmWave module, which already models in detail the
channel, Physical (PHY) and Medium Access Control (MAC) layers, and extends the
Long Term Evolution (LTE) stack for the higher layers. In this paper we present
an implementation for the ns-3 mmWave module of multi connectivity techniques
for 3GPP New Radio (NR) at mmWave frequencies, namely Carrier Aggregation (CA)
and Dual Connectivity (DC), and discuss how they can be integrated to increase
the functionalities offered by the ns-3 mmWave module.Comment: 9 pages, 7 figures, submitted to the Workshop on ns-3 (WNS3) 201
HARQ in relay-assisted transmission for machine type communications
This letter describes the impact of unknown channel access delay on the timeline of the hybrid automatic repeat request (HARQ) process in the 3rd generation partnership project long term evolution (3GPP LTE) system when a relay node (RN) is used for coverage extension of machine type communication (MTC) devices. A solution is also proposed for the determination of unknown channel access delay when the RN operates in the unlicensed spectrum band. The proposed mechanism is expected to help MTC operation in typical coverage holes areas such as smart meters located in the basement of buildings
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G
We investigate Early Hybrid Automatic Repeat reQuest (E-HARQ) feedback
schemes enhanced by machine learning techniques as a path towards
ultra-reliable and low-latency communication (URLLC). To this end, we propose
machine learning methods to predict the outcome of the decoding process ahead
of the end of the transmission. We discuss different input features and
classification algorithms ranging from traditional methods to newly developed
supervised autoencoders. These methods are evaluated based on their prospects
of complying with the URLLC requirements of effective block error rates below
at small latency overheads. We provide realistic performance
estimates in a system model incorporating scheduling effects to demonstrate the
feasibility of E-HARQ across different signal-to-noise ratios, subcode lengths,
channel conditions and system loads, and show the benefit over regular HARQ and
existing E-HARQ schemes without machine learning.Comment: 14 pages, 15 figures; accepted versio
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