7,411 research outputs found
Distributed energy-efficient power optimization in cellular relay networks with minimum rate constraints
In this work, we derive a distributed power control algo- rithm for energy-efficient uplink transmissions in interference- limited cellular networks, equipped with either multiple or shared relays. The proposed solution is derived by model- ing the mobile terminals as utility-driven rational agents that engage in a noncooperative game, under minimum-rate con- straints. The theoretical analysis of the game equilibrium is used to compare the performance of the two different cellular architectures. Extensive simulations show that the shared relay concept outperforms the distributed one in terms of energy efficiency in most network configurations
Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks
The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter
Energy-Efficient Power Control: A Look at 5G Wireless Technologies
This work develops power control algorithms for energy efficiency (EE)
maximization (measured in bit/Joule) in wireless networks. Unlike previous
related works, minimum-rate constraints are imposed and the
signal-to-interference-plus-noise ratio takes a more general expression, which
allows one to encompass some of the most promising 5G candidate technologies.
Both network-centric and user-centric EE maximizations are considered. In the
network-centric scenario, the maximization of the global EE and the minimum EE
of the network are performed. Unlike previous contributions, we develop
centralized algorithms that are guaranteed to converge, with affordable
computational complexity, to a Karush-Kuhn-Tucker point of the considered
non-convex optimization problems. Moreover, closed-form feasibility conditions
are derived. In the user-centric scenario, game theory is used to study the
equilibria of the network and to derive convergent power control algorithms,
which can be implemented in a fully decentralized fashion. Both scenarios above
are studied under the assumption that single or multiple resource blocks are
employed for data transmission. Numerical results assess the performance of the
proposed solutions, analyzing the impact of minimum-rate constraints, and
comparing the network-centric and user-centric approaches.Comment: Accepted for Publication in the IEEE Transactions on Signal
Processin
Power allocation in wireless multi-user relay networks
In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel power allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit power over all sources; iii) maximize the network throughput. Moreover, due to limited power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal power allocation is performed. Although the joint optimal admission control and power allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed power allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Resource Allocation for Energy-Efficient 3-Way Relay Channels
Throughput and energy efficiency in 3-way relay channels are studied in this
paper. Unlike previous contributions, we consider a circular message exchange.
First, an outer bound and achievable sum rate expressions for different
relaying protocols are derived for 3-way relay channels. The sum capacity is
characterized for certain SNR regimes. Next, leveraging the derived achievable
sum rate expressions, cooperative and competitive maximization of the energy
efficiency are considered. For the cooperative case, both low-complexity and
globally optimal algorithms for joint power allocation at the users and at the
relay are designed so as to maximize the system global energy efficiency. For
the competitive case, a game theoretic approach is taken, and it is shown that
the best response dynamics is guaranteed to converge to a Nash equilibrium. A
power consumption model for mmWave board-to-board communications is developed,
and numerical results are provided to corroborate and provide insight on the
theoretical findings.Comment: Submitted to IEEE Transactions on Wireless Communication
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