226 research outputs found
Cooperative Feedback for Multi-Antenna Cognitive Radio Networks
Cognitive beamforming (CB) is a multi-antenna technique for efficient
spectrum sharing between primary users (PUs) and secondary users (SUs) in a
cognitive radio network. Specifically, a multi-antenna SU transmitter applies
CB to suppress the interference to the PU receivers as well as enhance the
corresponding SU-link performance. In this paper, for a
multiple-input-single-output (MISO) SU channel coexisting with a
single-input-single-output (SISO) PU channel, we propose a new and practical
paradigm for designing CB based on the finite-rate cooperative feedback from
the PU receiver to the SU transmitter. Specifically, the PU receiver
communicates to the SU transmitter the quantized SU-to-PU channel direction
information (CDI) for computing the SU transmit beamformer, and the
interference power control (IPC) signal that regulates the SU transmission
power according to the tolerable interference margin at the PU receiver. Two CB
algorithms based on cooperative feedback are proposed: one restricts the SU
transmit beamformer to be orthogonal to the quantized SU-to-PU channel
direction and the other relaxes such a constraint. In addition, cooperative
feedforward of the SU CDI from the SU transmitter to the PU receiver is
exploited to allow more efficient cooperative feedback. The outage
probabilities of the SU link for different CB and cooperative
feedback/feedforward algorithms are analyzed, from which the optimal
bit-allocation tradeoff between the CDI and IPC feedback is characterized.Comment: 26 pages; to appear in IEEE Trans. Signal Processin
Cooperative Precoding with Limited Feedback for MIMO Interference Channels
Multi-antenna precoding effectively mitigates the interference in wireless
networks. However, the resultant performance gains can be significantly
compromised in practice if the precoder design fails to account for the
inaccuracy in the channel state information (CSI) feedback. This paper
addresses this issue by considering finite-rate CSI feedback from receivers to
their interfering transmitters in the two-user multiple-input-multiple-output
(MIMO) interference channel, called cooperative feedback, and proposing a
systematic method for designing transceivers comprising linear precoders and
equalizers. Specifically, each precoder/equalizer is decomposed into inner and
outer components for nulling the cross-link interference and achieving array
gain, respectively. The inner precoders/equalizers are further optimized to
suppress the residual interference resulting from finite-rate cooperative
feedback. Further- more, the residual interference is regulated by additional
scalar cooperative feedback signals that are designed to control transmission
power using different criteria including fixed interference margin and maximum
sum throughput. Finally, the required number of cooperative precoder feedback
bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011
and will appear in IEEE Trans. on Wireless Com
Coverage and Economy of Cellular Networks with Many Base Stations
The performance of a cellular network can be significantly improved by
employing many base stations (BSs), which shortens transmission distances.
However, there exist no known results on quantifying the performance gains from
deploying many BSs. To address this issue, we adopt a stochastic-geometry model
of the downlink cellular network and analyze the mobile outage probability.
Specifically, given Poisson distributed BSs, the outage probability is shown to
diminish inversely with the increasing ratio between the BS and mobile
densities. Furthermore, we analyze the optimal tradeoff between the performance
gain from increasing the BS density and the resultant network cost accounting
for energy consumption, BS hardware and backhaul cables. The optimal BS density
is proved to be proportional to the square root of the mobile density and the
inverse of the square root of the cost factors considered.Comment: 3 pages, 3 figures, to appear in IEEE Communications Letter
Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio
Multimedia content especially videos is expected to dominate data traffic in
next-generation mobile networks. Caching popular content at the network edge
has emerged to be a solution for low-latency content delivery. Compared with
the traditional wireless communication, content delivery has a key
characteristic that many signals coexisting in the air carry identical popular
content. They, however, can interfere with each other at a receiver if their
modulation-and-coding (MAC) schemes are adapted to individual channels
following the classic approach. To address this issue, we present a novel idea
of content adaptive MAC (CAMAC) where adapting MAC schemes to content ensures
that all signals carry identical content are encoded using an identical MAC
scheme, achieving spatial MAC alignment. Consequently, interference can be
harnessed as signals, to improve the reliability of wireless delivery. In the
remaining part of the paper, we focus on quantifying the gain CAMAC can bring
to a content-delivery network using a stochastic-geometry model. Specifically,
content helpers are distributed as a Poisson point process, each of which
transmits a file from a content database based on a given popularity
distribution. It is discovered that the successful content-delivery probability
is closely related to the distribution of the ratio of two independent shot
noise processes, named a shot-noise ratio. The distribution itself is an open
mathematical problem that we tackle in this work. Using stable-distribution
theory and tools from stochastic geometry, the distribution function is derived
in closed form. Extending the result in the context of content-delivery
networks with CAMAC yields the content-delivery probability in different closed
forms. In addition, the gain in the probability due to CAMAC is shown to grow
with the level of skewness in the content popularity distribution.Comment: 32 pages, to appear in IEEE Trans. on Wireless Communicatio
Cooperative Feedback for MIMO Interference Channels
Multi-antenna precoding effectively mitigates the interference in wireless
networks. However, the precoding efficiency can be significantly degraded by
the overhead due to the required feedback of channel state information (CSI).
This paper addresses such an issue by proposing a systematic method of
designing precoders for the two-user multiple-input-multiple-output (MIMO)
interference channels based on finite-rate CSI feedback from receivers to their
interferers, called cooperative feedback. Specifically, each precoder is
decomposed into inner and outer precoders for nulling interference and
improving the data link array gain, respectively. The inner precoders are
further designed to suppress residual interference resulting from finite-rate
cooperative feedback. To regulate residual interference due to precoder
quantization, additional scalar cooperative feedback signals are designed to
control transmitters' power using different criteria including applying
interference margins, maximizing sum throughput, and minimizing outage
probability. Simulation shows that such additional feedback effectively
alleviates performance degradation due to quantized precoder feedback.Comment: 5 pages; submitted to IEEE ICC 201
Wirelessly Powered Backscatter Communication Networks: Modeling, Coverage and Capacity
Future Internet-of-Things (IoT) will connect billions of small computing
devices embedded in the environment and support their device-to-device (D2D)
communication. Powering this massive number of embedded devices is a key
challenge of designing IoT since batteries increase the devices' form factors
and battery recharging/replacement is difficult. To tackle this challenge, we
propose a novel network architecture that enables D2D communication between
passive nodes by integrating wireless power transfer and backscatter
communication, which is called a wirelessly powered backscatter communication
(WP-BackCom) network. In the network, standalone power beacons (PBs) are
deployed for wirelessly powering nodes by beaming unmodulated carrier signals
to targeted nodes. Provisioned with a backscatter antenna, a node transmits
data to an intended receiver by modulating and reflecting a fraction of a
carrier signal. Such transmission by backscatter consumes orders-of-magnitude
less power than a traditional radio. Thereby, the dense deployment of
low-complexity PBs with high transmission power can power a large-scale IoT. In
this paper, a WP-BackCom network is modeled as a random Poisson cluster process
in the horizontal plane where PBs are Poisson distributed and active ad-hoc
pairs of backscatter communication nodes with fixed separation distances form
random clusters centered at PBs. The backscatter nodes can harvest energy from
and backscatter carrier signals transmitted by PBs. Furthermore, the
transmission power of each node depends on the distance from the associated PB.
Applying stochastic geometry, the network coverage probability and transmission
capacity are derived and optimized as functions of backscatter parameters,
including backscatter duty cycle and reflection coefficient, as well as the PB
density. The effects of the parameters on network performance are
characterized.Comment: 28 pages, 11 figures, has been submitted to IEEE Trans. on Wireless
Communicatio
- …