98 research outputs found
Towards a Simple Relationship to Estimate the Capacity of Static and Mobile Wireless Networks
Extensive research has been done on studying the capacity of wireless
multi-hop networks. These efforts have led to many sophisticated and customized
analytical studies on the capacity of particular networks. While most of the
analyses are intellectually challenging, they lack universal properties that
can be extended to study the capacity of a different network. In this paper, we
sift through various capacity-impacting parameters and present a simple
relationship that can be used to estimate the capacity of both static and
mobile networks. Specifically, we show that the network capacity is determined
by the average number of simultaneous transmissions, the link capacity and the
average number of transmissions required to deliver a packet to its
destination. Our result is valid for both finite networks and asymptotically
infinite networks. We then use this result to explain and better understand the
insights of some existing results on the capacity of static networks, mobile
networks and hybrid networks and the multicast capacity. The capacity analysis
using the aforementioned relationship often becomes simpler. The relationship
can be used as a powerful tool to estimate the capacity of different networks.
Our work makes important contributions towards developing a generic methodology
for network capacity analysis that is applicable to a variety of different
scenarios.Comment: accepted to appear in IEEE Transactions on Wireless Communication
Ultra-Dense Networks: Is There a Limit to Spatial Spectrum Reuse?
The aggressive spatial spectrum reuse (SSR) by network densification using
smaller cells has successfully driven the wireless communication industry
onward in the past decades. In our future journey toward ultra-dense networks
(UDNs), a fundamental question needs to be answered. Is there a limit to SSR?
In other words, when we deploy thousands or millions of small cell base
stations (BSs) per square kilometer, is activating all BSs on the same
time/frequency resource the best strategy? In this paper, we present
theoretical analyses to answer such question. In particular, we find that both
the signal and interference powers become bounded in practical UDNs with a
non-zero BS-to-UE antenna height difference and a finite UE density, which
leads to a constant capacity scaling law. As a result, there exists an optimal
SSR density that can maximize the network capacity. Hence, the limit to SSR
should be considered in the operation of future UDNs.Comment: conference submission in Oct. 201
Probability of Error for Optimal Codes in a Reconfigurable Intelligent Surface Aided URLLC System
The lower bound on the decoding error probability for the optimal code given
a signal-to-noise ratio and a code rate are investigated in this letter for the
reconfigurable intelligent surface (RIS) communication system over a Rician
fading channel at the short blocklength regime, which is the key characteristic
of ultra-reliable low-latency communications (URLLC) to meet the need for
strict adherence to quality of service (QoS) requirements. Sphere packing
technique is used to derive our main results. The Wald sequential t-test lemma
and the Gaussian-Chebyshev quadrature are the main tools to obtain the
closed-form expression for the lower bound. Numerical results are provided to
validate our results and demonstrate the tightness of our results compared to
the Polyanskiy-Poor-Verdu (PPV) bound
Spectrum Sharing in RF-Powered Cognitive Radio Networks using Game Theory
We investigate the spectrum sharing problem of a radio frequency (RF)-powered
cognitive radio network, where a multi-antenna secondary user (SU) harvests
energy from RF signals radiated by a primary user (PU) to boost its available
energy before information transmission. In this paper, we consider that both
the PU and SU are rational and self-interested. Based on whether the SU helps
forward the PU's information, we develop two different operation modes for the
considered network, termed as non-cooperative and cooperative modes. In the
non-cooperative mode, the SU harvests energy from the PU and then use its
available energy to transmit its own information without generating any
interference to the primary link. In the cooperative mode, the PU employs the
SU to relay its information by providing monetary incentives and the SU splits
its energy for forwarding the PU's information as well as transmitting its own
information. Optimization problems are respectively formulated for both
operation modes, which constitute a Stackelberg game with the PU as a leader
and the SU as a follower. We analyze the Stackelberg game by deriving solutions
to the optimization problems and the Stackelberg Equilibrium (SE) is
subsequently obtained. Simulation results show that the performance of the
Stackelberg game can approach that of the centralized optimization scheme when
the distance between the SU and its receiver is large enough.Comment: Presented at PIMRC'1
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