135 research outputs found
Signal Processing and Learning for Next Generation Multiple Access in 6G
Wireless communication systems to date primarily rely on the orthogonality of
resources to facilitate the design and implementation, from user access to data
transmission. Emerging applications and scenarios in the sixth generation (6G)
wireless systems will require massive connectivity and transmission of a deluge
of data, which calls for more flexibility in the design concept that goes
beyond orthogonality. Furthermore, recent advances in signal processing and
learning have attracted considerable attention, as they provide promising
approaches to various complex and previously intractable problems of signal
processing in many fields. This article provides an overview of research
efforts to date in the field of signal processing and learning for
next-generation multiple access, with an emphasis on massive random access and
non-orthogonal multiple access. The promising interplay with new technologies
and the challenges in learning-based NGMA are discussed
Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits
The use of large-scale antenna arrays has the potential to bring substantial
improvements in energy efficiency and/or spectral efficiency to future wireless
systems, due to the greatly improved spatial beamforming resolution. Recent
asymptotic results show that by increasing the number of antennas one can
achieve a large array gain and at the same time naturally decorrelate the user
channels; thus, the available energy can be focused very accurately at the
intended destinations without causing much inter-user interference. Since these
results rely on asymptotics, it is important to investigate whether the
conventional system models are still reasonable in the asymptotic regimes. This
paper analyzes the fundamental limits of large-scale multiple-input
single-output (MISO) communication systems using a generalized system model
that accounts for transceiver hardware impairments. As opposed to the case of
ideal hardware, we show that these practical impairments create finite ceilings
on the estimation accuracy and capacity of large-scale MISO systems.
Surprisingly, the performance is only limited by the hardware at the
single-antenna user terminal, while the impact of impairments at the
large-scale array vanishes asymptotically. Furthermore, we show that an
arbitrarily high energy efficiency can be achieved by reducing the power while
increasing the number of antennas.Comment: Published at International Conference on Digital Signal Processing
(DSP 2013), 6 pages, 5 figure
- …