205 research outputs found
Degrees of Freedom of Certain Interference Alignment Schemes with Distributed CSIT
In this work, we consider the use of interference alignment (IA) in a MIMO
interference channel (IC) under the assumption that each transmitter (TX) has
access to channel state information (CSI) that generally differs from that
available to other TXs. This setting is referred to as distributed CSIT. In a
setting where CSI accuracy is controlled by a set of power exponents, we show
that in the static 3-user MIMO square IC, the number of degrees-of-freedom
(DoF) that can be achieved with distributed CSIT is at least equal to the DoF
achieved with the worst accuracy taken across the TXs and across the
interfering links. We conjecture further that this represents exactly the DoF
achieved. This result is in strong contrast with the centralized CSIT
configuration usually studied (where all the TXs share the same, possibly
imperfect, channel estimate) for which it was shown that the DoF achieved at
receiver (RX) i is solely limited by the quality of its own feedback. This
shows the critical impact of CSI discrepancies between the TXs, and highlights
the price paid by distributed precoding.Comment: This is an extended version of a conference submission which will be
presented at the IEEE conference SPAWC, Darmstadt, June 201
A low complexity resource allocation algorithm for multicast service delivery in OFDMA networks
Allocating and managing radio resources to multicast transmissions in Orthogonal Frequency-Division Multiple Access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution (LTE) system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system
Energy Beamforming with One-Bit Feedback
Wireless energy transfer (WET) has attracted significant attention recently
for providing energy supplies wirelessly to electrical devices without the need
of wires or cables. Among different types of WET techniques, the radio
frequency (RF) signal enabled far-field WET is most practically appealing to
power energy constrained wireless networks in a broadcast manner. To overcome
the significant path loss over wireless channels, multi-antenna or
multiple-input multiple-output (MIMO) techniques have been proposed to enhance
the transmission efficiency and distance for RF-based WET. However, in order to
reap the large energy beamforming gain in MIMO WET, acquiring the channel state
information (CSI) at the energy transmitter (ET) is an essential task. This
task is particularly challenging for WET systems, since existing channel
training and feedback methods used for communication receivers may not be
implementable at the energy receiver (ER) due to its hardware limitation. To
tackle this problem, in this paper we consider a multiuser MIMO system for WET,
where a multiple-antenna ET broadcasts wireless energy to a group of
multiple-antenna ERs concurrently via transmit energy beamforming. By taking
into account the practical energy harvesting circuits at the ER, we propose a
new channel learning method that requires only one feedback bit from each ER to
the ET per feedback interval. The feedback bit indicates the increase or
decrease of the harvested energy by each ER between the present and previous
intervals, which can be measured without changing the existing hardware at the
ER. Based on such feedback information, the ET adjusts transmit beamforming in
different training intervals and at the same time obtains improved estimates of
the MIMO channels to ERs by applying a new approach termed analytic center
cutting plane method (ACCPM).Comment: This is the longer version of a paper to appear in IEEE Transactions
on Signal Processin
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