15,180 research outputs found
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
Relays for Interference Mitigation in Wireless Networks
Wireless links play an important role in the last mile network connectivity. In contrast to the strictly centralized approach of today's wireless systems, the future promises decentralization of network management. Nodes potentially engage in localized grouping and organization based on their neighborhood to carry out complex goals such as end-to-end communication. The quadratic energy dissipation of the wireless medium necessitates the presence of certain relay nodes in the network. Conventionally, the role of such relays is limited to passing messages in a chain in a point-point hopping architecture. With the decentralization, multiple nodes could potentially interfere with each other. This work proposes a technique to exploit the presence of relays in a way that mitigates interference between the network nodes. Optimal spatial locations and transmission schemes which enhance this gain are identified
Code designs for MIMO broadcast channels
Recent information-theoretic results show the optimality of dirty-paper coding (DPC) in achieving the full capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This paper presents a DPC based code design for BCs. We consider the case in which there is an individual rate/signal-to-interference-plus-noise ratio (SINR) constraint for each user. For a fixed transmitter power, we choose the linear transmit precoding matrix such that the SINRs at users are uniformly maximized, thus ensuring the best bit-error rate performance. We start with Cover's simplest two-user Gaussian BC and present a coding scheme that operates 1.44 dB from the boundary of the capacity region at the rate of one bit per real sample (b/s) for each user. We then extend the coding strategy to a two-user MIMO Gaussian BC with two transmit antennas at the base-station and develop the first limit-approaching code design using nested turbo codes for DPC. At the rate of 1 b/s for each user, our design operates 1.48 dB from the capacity region boundary. We also consider the performance of our scheme over a slow fading BC. For two transmit antennas, simulation results indicate a performance loss of only 1.4 dB, 1.64 dB and 1.99 dB from the theoretical limit in terms of the total transmission power for the two, three and four user case, respectively
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
An overview of game-theoretic approaches to energy-efficient resource
allocation in wireless networks is presented. Focusing on multiple-access
networks, it is demonstrated that game theory can be used as an effective tool
to study resource allocation in wireless networks with quality-of-service (QoS)
constraints. A family of non-cooperative (distributed) games is presented in
which each user seeks to choose a strategy that maximizes its own utility while
satisfying its QoS requirements. The utility function considered here measures
the number of reliable bits that are transmitted per joule of energy consumed
and, hence, is particulary suitable for energy-constrained networks. The
actions available to each user in trying to maximize its own utility are at
least the choice of the transmit power and, depending on the situation, the
user may also be able to choose its transmission rate, modulation, packet size,
multiuser receiver, multi-antenna processing algorithm, or carrier allocation
strategy. The best-response strategy and Nash equilibrium for each game is
presented. Using this game-theoretic framework, the effects of power control,
rate control, modulation, temporal and spatial signal processing, carrier
allocation strategy and delay QoS constraints on energy efficiency and network
capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on
Resource-Constrained Signal Processing, Communications and Networking, May
200
Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks
Optimizing activation and deactivation of base station transmissions provides
an instrument for improving energy efficiency in cellular networks. In this
paper, we study optimal cell clustering and scheduling of activation duration
for each cluster, with the objective of minimizing the sum energy, subject to a
time constraint of delivering the users' traffic demand. The cells within a
cluster are simultaneously in transmission and napping modes, with cluster
activation and deactivation, respectively. Our optimization framework accounts
for the coupling relation among cells due to the mutual interference. Thus, the
users' achievable rates in a cell depend on the cluster composition. On the
theoretical side, we provide mathematical formulation and structural
characterization for the energy-efficient cell clustering and scheduling
optimization problem, and prove its NP hardness. On the algorithmic side, we
first show how column generation facilitates problem solving, and then present
our notion of local enumeration as a flexible and effective means for dealing
with the trade-off between optimality and the combinatorial nature of cluster
formation, as well as for the purpose of gauging the deviation from optimality.
Numerical results demonstrate that our solutions achieve more than 60% energy
saving over existing schemes, and that the solutions we obtain are within a few
percent of deviation from global optimum.Comment: Revision, IEEE Transactions on Wireless Communication
Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
The combination of source coding with decoder side-information (Wyner-Ziv
problem) and channel coding with encoder side-information (Gel'fand-Pinsker
problem) can be optimally solved using the separation principle. In this work
we show an alternative scheme for the quadratic-Gaussian case, which merges
source and channel coding. This scheme achieves the optimal performance by a
applying modulo-lattice modulation to the analog source. Thus it saves the
complexity of quantization and channel decoding, and remains with the task of
"shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme
approaches the optimal performance using an SNR-independent encoder, thus it is
robust to unknown SNR at the encoder.Comment: Submitted to IEEE Transactions on Information Theory. Presented in
part in ISIT-2006, Seattle. New version after revie
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