22,966 research outputs found
Achieving Max-Min Throughput in LoRa Networks
With growing popularity, LoRa networks are pivotally enabling Long Range
connectivity to low-cost and power-constrained user equipments (UEs). Due to
its wide coverage area, a critical issue is to effectively allocate wireless
resources to support potentially massive UEs in the cell while resolving the
prominent near-far fairness problem for cell-edge UEs, which is challenging to
address due to the lack of tractable analytical model for the LoRa network and
its practical requirement for low-complexity and low-overhead design. To
achieve massive connectivity with fairness, we investigate the problem of
maximizing the minimum throughput of all UEs in the LoRa network, by jointly
designing high-level policies of spreading factor (SF) allocation, power
control, and duty cycle adjustment based only on average channel statistics and
spatial UE distribution. By leveraging on the Poisson rain model along with
tailored modifications to our considered LoRa network, we are able to account
for channel fading, aggregate interference and accurate packet overlapping, and
still obtain a tractable and yet accurate closed-form formula for the packet
success probability and hence throughput. We further propose an iterative
balancing (IB) method to allocate the SFs in the cell such that the overall
max-min throughput can be achieved within the considered time period and cell
area. Numerical results show that the proposed scheme with optimized design
greatly alleviates the near-far fairness issue, and significantly improves the
cell-edge throughput.Comment: 6 pages, 4 figures, published in Proc. International Conference on
Computing, Networking and Communications (ICNC), 2020. This paper proposes
stochastic-geometry based analytical framework for a single-cell LoRa
network, with joint optimization to achieve max-min throughput for the users.
Extended journal version for large-scale multi-cell LoRa network:
arXiv:2008.0743
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
Ubiquitous Cell-Free Massive MIMO Communications
Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and
Networking on August 5, 201
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