10,446 research outputs found
Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges
As a promising paradigm for fifth generation (5G) wireless communication
systems, cloud radio access networks (C-RANs) have been shown to reduce both
capital and operating expenditures, as well as to provide high spectral
efficiency (SE) and energy efficiency (EE). The fronthaul in such networks,
defined as the transmission link between a baseband unit (BBU) and a remote
radio head (RRH), requires high capacity, but is often constrained. This
article comprehensively surveys recent advances in fronthaul-constrained
C-RANs, including system architectures and key techniques. In particular, key
techniques for alleviating the impact of constrained fronthaul on SE/EE and
quality of service for users, including compression and quantization,
large-scale coordinated processing and clustering, and resource allocation
optimization, are discussed. Open issues in terms of software-defined
networking, network function virtualization, and partial centralization are
also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin
note: text overlap with arXiv:1407.3855 by other author
Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems
In this paper, we consider the problem of achieving max-min fairness amongst
multiple co-channel multicast groups through transmit beamforming. We
explicitly focus on overloaded scenarios in which the number of transmitting
antennas is insufficient to neutralize all inter-group interference. Such
scenarios are becoming increasingly relevant in the light of growing
low-latency content delivery demands, and also commonly appear in multibeam
satellite systems. We derive performance limits of classical beamforming
strategies using DoF analysis unveiling their limitations; for example, rates
saturate in overloaded scenarios due to inter-group interference. To tackle
interference, we propose a strategy based on degraded beamforming and
successive interference cancellation. While the degraded strategy resolves the
rate-saturation issue, this comes at a price of sacrificing all spatial
multiplexing gains. This motivates the development of a unifying strategy that
combines the benefits of the two previous strategies. We propose a beamforming
strategy based on rate-splitting (RS) which divides the messages intended to
each group into a degraded part and a designated part, and transmits a
superposition of both degraded and designated beamformed streams. The
superiority of the proposed strategy is demonstrated through DoF analysis.
Finally, we solve the RS beamforming design problem and demonstrate significant
performance gains through simulations
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
Magazin
Underlay Cognitive Radio with Full or Partial Channel Quality Information
Underlay cognitive radios (UCRs) allow a secondary user to enter a primary
user's spectrum through intelligent utilization of multiuser channel quality
information (CQI) and sharing of codebook. The aim of this work is to study
two-user Gaussian UCR systems by assuming the full or partial knowledge of
multiuser CQI. Key contribution of this work is motivated by the fact that the
full knowledge of multiuser CQI is not always available. We first establish a
location-aided UCR model where the secondary user is assumed to have partial
CQI about the secondary-transmitter to primary-receiver link as well as full
CQI about the other links. Then, new UCR approaches are proposed and carefully
analyzed in terms of the secondary user's achievable rate, denoted by ,
the capacity penalty to primary user, denoted by , and capacity
outage probability. Numerical examples are provided to visually compare the
performance of UCRs with full knowledge of multiuser CQI and the proposed
approaches with partial knowledge of multiuser CQI.Comment: 29 Pages, 8 figure
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