1,145 research outputs found
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
Maximizing the Sum Rate in Cellular Networks Using Multi-Convex Optimization
In this paper, we propose a novel algorithm to maximize the sum rate in
interference-limited scenarios where each user decodes its own message with the
presence of unknown interferences and noise considering the
signal-to-interference-plus-noise-ratio. It is known that the problem of
adapting the transmit and receive filters of the users to maximize the sum rate
with a sum transmit power constraint is non-convex. Our novel approach is to
formulate the sum rate maximization problem as an equivalent multi-convex
optimization problem by adding two sets of auxiliary variables. An iterative
algorithm which alternatingly adjusts the system variables and the auxiliary
variables is proposed to solve the multi-convex optimization problem. The
proposed algorithm is applied to a downlink cellular scenario consisting of
several cells each of which contains a base station serving several mobile
stations. We examine the two cases, with or without several half-duplex
amplify-and-forward relays assisting the transmission. A sum power constraint
at the base stations and a sum power constraint at the relays are assumed.
Finally, we show that the proposed multi-convex formulation of the sum rate
maximization problem is applicable to many other wireless systems in which the
estimated data symbols are multi-affine functions of the system variables.Comment: 24 pages, 5 figure
On Design of Collaborative Beamforming for Two-Way Relay Networks
We consider a two-way relay network, where two source nodes, S1 and S2,
exchange information through a cluster of relay nodes. The relay nodes receive
the sum signal from S1 and S2 in the first time slot. In the second time slot,
each relay node multiplies its received signal by a complex coefficient and
retransmits the signal to the two source nodes, which leads to a collaborative
two-way beamforming system. By applying the principle of analog network coding,
each receiver at S1 and S2 cancels the "self-interference" in the received
signal from the relay cluster and decodes the message. This paper studies the
2-dimensional achievable rate region for such a two-way relay network with
collaborative beamforming. With different assumptions of channel reciprocity
between the source-relay and relay-source channels, the achievable rate region
is characterized under two setups. First, with reciprocal channels, we
investigate the achievable rate regions when the relay cluster is subject to a
sum-power constraint or individual-power constraints. We show that the optimal
beamforming vectors obtained from solving the weighted sum inverse-SNR
minimization (WSISMin) problems are sufficient to characterize the
corresponding achievable rate region. Furthermore, we derive the closed form
solutions for those optimal beamforming vectors and consequently propose the
partially distributed algorithms to implement the optimal beamforming, where
each relay node only needs the local channel information and one global
parameter. Second, with the non-reciprocal channels, the achievable rate
regions are also characterized for both the sum-power constraint case and the
individual-power constraint case. Although no closed-form solutions are
available under this setup, we present efficient numerical algorithms.Comment: new version of the previously posted, single column double spacing,
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