2,320 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
Low Complexity WMMSE Power Allocation In NOMA-FD Systems
In this paper we study the problem of power and channel allocation with the
objective of maximizing the system sum-rate for multicarrier non-orthogonal
multiple access (NOMA) full duplex (FD) systems. Such an allocation problem is
non-convex and, thus, with the goal of designing a low complexity solution, we
propose a scheme based on the minimization of the weighted mean square error,
which achieves performance reasonably close to the optimum and allows to
clearly outperforms a conventional orthogonal multiple access approach.
Numerical results assess the effectiveness of our algorithm.Comment: 5 pages conference paper, 3 figures. Submitted on ICASSP 202
Random Access in Uplink Massive MIMO Systems: How to exploit asynchronicity and excess antennas
Massive MIMO systems, where the base stations are equipped with hundreds of
antennas, are an attractive way to handle the rapid growth of data traffic. As
the number of users increases, the initial access and handover in contemporary
networks will be flooded by user collisions. In this work, we propose a random
access procedure that resolves collisions and also performs timing, channel,
and power estimation by simply utilizing the large number of antennas
envisioned in massive MIMO systems and the inherent timing misalignments of
uplink signals during network access and handover. Numerical results are used
to validate the performance of the proposed solution under different settings.
It turns out that the proposed solution can detect all collisions with a
probability higher than 90%, at the same time providing reliable timing and
channel estimates. Moreover, numerical results demonstrate that it is robust to
overloaded situations.Comment: submitted to IEEE Globecom 2016, Washington, DC US
Beamforming Techniques for Non-Orthogonal Multiple Access in 5G Cellular Networks
In this paper, we develop various beamforming techniques for downlink
transmission for multiple-input single-output (MISO) non-orthogonal multiple
access (NOMA) systems. First, a beamforming approach with perfect channel state
information (CSI) is investigated to provide the required quality of service
(QoS) for all users. Taylor series approximation and semidefinite relaxation
(SDR) techniques are employed to reformulate the original non-convex power
minimization problem to a tractable one. Further, a fairness-based beamforming
approach is proposed through a max-min formulation to maintain fairness between
users. Next, we consider a robust scheme by incorporating channel
uncertainties, where the transmit power is minimized while satisfying the
outage probability requirement at each user. Through exploiting the SDR
approach, the original non-convex problem is reformulated in a linear matrix
inequality (LMI) form to obtain the optimal solution. Numerical results
demonstrate that the robust scheme can achieve better performance compared to
the non-robust scheme in terms of the rate satisfaction ratio. Further,
simulation results confirm that NOMA consumes a little over half transmit power
needed by OMA for the same data rate requirements. Hence, NOMA has the
potential to significantly improve the system performance in terms of transmit
power consumption in future 5G networks and beyond.Comment: accepted to publish in IEEE Transactions on Vehicular Technolog
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