4 research outputs found
A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multi-Carrier Wireless Networks
This paper proposes computationally efficient algorithms to maximize the
energy efficiency in multi-carrier wireless interference networks, by a
suitable allocation of the system radio resources, namely the transmit powers
and subcarrier assignment. The problem is formulated as the maximization of the
system Global Energy-Efficiency subject to both maximum power and minimum rate
constraints. This leads to a challenging non-convex fractional problem, which
is tackled through an interplay of fractional programming, learning, and game
theory. The proposed algorithmic framework is provably convergent and has a
complexity linear in both the number of users and subcarriers, whereas other
available solutions can only guarantee a polynomial complexity in the number of
users and subcarriers. Numerical results show that the proposed method performs
similarly as other, more complex, algorithms
Joint energy-spectral-efficiency optimization of CoMP and BS deployment in dense large-scale cellular networks
In this paper, the energy-spectral efficiency (ESE) benefiting from the joint optimization of coordinated multipoint (CoMP) transmission and base station (BS) deployment is evaluated in the context of dense large-scale cellular network. We first derive a closed-form network ESE expression for a largescale CoMP-enhanced network, which allows us to quantify the influence of key network parameters on the achievable network ESE, including the BS density and the cooperation activation probability, characterized by a CoMP activation factor as well as the usersâ behaviors, such as their geographical mobile-traffic intensity and average user rate. With the aid of this tractable ESE expression and for a given BS density, we next formulate a cellular scenario-aware CoMP activation optimization problem while considering the usersâ outage probability as constraints to maximize the networkâs ESE.We then jointly optimize the CoMP activation factor and the BS density to maximize the network ESE, again under the constraint of the usersâ outage probability. Our simulation results confirm the accuracy of our analysis and verify the impact of several key parameters on the network ESE. Finally, the ESE improvement of our proposed strategies is evaluated under diverse scenarios, which provides valuable insight into the joint CoMP and BS deployment optimization in dense large-scale cellular networks
On Dependable Wireless Communications through Multi-Connectivity
The realization of wireless ultra-reliable low-latency communications (URLLC) is one of the key challenges of the fifth generation (5G) of mobile communications systems and beyond. Ensuring ultra-high reliability together with a latency in the (sub-)millisecond range is expected to enable self-driving cars, wireless factory automation, and the Tactile Internet. In wireless communications, reliability is usually only considered as percentage of successful packet delivery, aiming for 1 â 10â»â” up to 1 â 10â»âč in URLLC