1,919 research outputs found
Two-Layered Superposition of Broadcast/Multicast and Unicast Signals in Multiuser OFDMA Systems
We study optimal delivery strategies of one common and independent
messages from a source to multiple users in wireless environments. In
particular, two-layered superposition of broadcast/multicast and unicast
signals is considered in a downlink multiuser OFDMA system. In the literature
and industry, the two-layer superposition is often considered as a pragmatic
approach to make a compromise between the simple but suboptimal orthogonal
multiplexing (OM) and the optimal but complex fully-layered non-orthogonal
multiplexing. In this work, we show that only two-layers are necessary to
achieve the maximum sum-rate when the common message has higher priority than
the individual unicast messages, and OM cannot be sum-rate optimal in
general. We develop an algorithm that finds the optimal power allocation over
the two-layers and across the OFDMA radio resources in static channels and a
class of fading channels. Two main use-cases are considered: i) Multicast and
unicast multiplexing when users with uplink capabilities request both
common and independent messages, and ii) broadcast and unicast multiplexing
when the common message targets receive-only devices and users with uplink
capabilities additionally request independent messages. Finally, we develop a
transceiver design for broadcast/multicast and unicast superposition
transmission based on LTE-A-Pro physical layer and show with numerical
evaluations in mobile environments with multipath propagation that the capacity
improvements can be translated into significant practical performance gains
compared to the orthogonal schemes in the 3GPP specifications. We also analyze
the impact of real channel estimation and show that significant gains in terms
of spectral efficiency or coverage area are still available even with
estimation errors and imperfect interference cancellation for the two-layered
superposition system
D13.2 Techniques and performance analysis on energy- and bandwidth-efficient communications and networking
Deliverable D13.2 del projecte europeu NEWCOM#The report presents the status of the research work of the
various Joint Research Activities (JRA) in WP1.3 and the results
that were developed up to the second year of the project. For
each activity there is a description, an illustration of the
adherence to and relevance with the identified fundamental
open issues, a short presentation of the main results, and a
roadmap for the future joint research. In the Annex, for each
JRA, the main technical details on specific scientific activities
are described in detail.Peer ReviewedPostprint (published version
Enhancing massive MIMO: A new approach for Uplink training based on heterogeneous coherence time
Massive multiple-input multiple-output (MIMO) is one of the key technologies
in future generation networks. Owing to their considerable spectral and energy
efficiency gains, massive MIMO systems provide the needed performance to cope
with the ever increasing wireless capacity demand. Nevertheless, the number of
scheduled users stays limited in massive MIMO both in time division duplexing
(TDD) and frequency division duplexing (FDD) systems. This is due to the
limited coherence time, in TDD systems, and to limited feedback capacity, in
FDD mode. In current systems, the time slot duration in TDD mode is the same
for all users. This is a suboptimal approach since users are subject to
heterogeneous Doppler spreads and, consequently, different coherence times. In
this paper, we investigate a massive MIMO system operating in TDD mode in
which, the frequency of uplink training differs among users based on their
actual channel coherence times. We argue that optimizing uplink training by
exploiting this diversity can lead to considerable spectral efficiency gain. We
then provide a user scheduling algorithm that exploits a coherence interval
based grouping in order to maximize the achievable weighted sum rate
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