58 research outputs found
Grouping Based Blind Interference Alignment for -user MISO Interference Channels
We propose a blind interference alignment (BIA) through staggered antenna
switching scheme with no ideal channel assumption. Contrary to the ideal
assumption that channels remain constant during BIA symbol extension period,
when the coherence time of the channel is relatively short, channel
coefficients may change during a given symbol extension period. To perform BIA
perfectly with realistic channel assumption, we propose a grouping based
supersymbol structure for -user interference channels which can adjust a
supersymbol length to given coherence time. It is proved that the supersymbol
length could be reduced significantly by an appropriate grouping. Furthermore,
it is also shown that the grouping based supersymbol achieves higher degrees of
freedom than the conventional method with given coherence time.Comment: 5 pages, 3 figures, to appear in IEEE ISIT 201
Interference Alignment with Limited Feedback on Two-cell Interfering Two-User MIMO-MAC
In this paper, we consider a two-cell interfering two-user multiple-input
multiple-output multiple access channel (MIMO-MAC) with limited feedback. We
first investigate the multiplexing gain of such channel when users have perfect
channel state information at transmitter (CSIT) by exploiting an interference
alignment scheme. In addition, we propose a feedback framework for the
interference alignment in the limited feedback system. On the basis of the
proposed feedback framework, we analyze the rate gap loss and it is shown that
in order to keep the same multiplexing gain with the case of perfect CSIT, the
number of feedback bits per receiver scales as , where and denote the number of
transmit antennas and a constant, respectively. Throughout the simulation
results, it is shown that the sum-rate performance coincides with the derived
results.Comment: 6 pages, 2 figures, Submitted ICC 201
Optimal Beamforming for Gaussian MIMO Wiretap Channels with Two Transmit Antennas
A Gaussian multiple-input multiple-output wiretap channel in which the
eavesdropper and legitimate receiver are equipped with arbitrary numbers of
antennas and the transmitter has two antennas is studied in this paper. Under
an average power constraint, the optimal input covariance to obtain the secrecy
capacity of this channel is unknown, in general. In this paper, the input
covariance matrix required to achieve the capacity is determined. It is shown
that the secrecy capacity of this channel can be achieved by linear precoding.
The optimal precoding and power allocation schemes that maximize the achievable
secrecy rate, and thus achieve the capacity, are developed subsequently. The
secrecy capacity is then compared with the achievable secrecy rate of
generalized singular value decomposition (GSVD)-based precoding, which is the
best previously proposed technique for this problem. Numerical results
demonstrate that substantial gain can be obtained in secrecy rate between the
proposed and GSVD-based precodings.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
Interference Alignment Through User Cooperation for Two-cell MIMO Interfering Broadcast Channels
This paper focuses on two-cell multiple-input multiple-output (MIMO) Gaussian
interfering broadcast channels (MIMO-IFBC) with cooperating users on the
cell-boundary of each BS. It corresponds to a downlink scenario for cellular
networks with two base stations (BSs), and users equipped with Wi-Fi
interfaces enabling to cooperate among users on a peer-to-peer basis. In this
scenario, we propose a novel interference alignment (IA) technique exploiting
user cooperation. Our proposed algorithm obtains the achievable degrees of
freedom (DoF) of 2K when each BS and user have transmit antennas and
receive antennas, respectively. Furthermore, the algorithm requires only
a small amount of channel feedback information with the aid of the user
cooperation channels. The simulations demonstrate that not only are the
analytical results valid, but the achievable DoF of our proposed algorithm also
outperforms those of conventional techniques.Comment: This paper will appear in IEEE GLOBECOM 201
Securing Downlink Non-Orthogonal Multiple Access Systems by Trusted Relays
A downlink single-input single-output non-orthogonal multiple access system
is considered in which a base station (BS) is communicating with two legitimate
users in the presence of an external eavesdropper. A group of trusted
cooperative half-duplex relay nodes, powered by the BS, is employed to assist
the BS's transmission. The goal is to design relaying schemes such that the
legitimate users' secrecy rate region is maximized subject to a total power
constraint on the BS and the relays' transmissions. Three relaying schemes are
investigated: cooperative jamming, decode-and-forward, and amplify-and-forward.
Depending on the scheme, secure beamforming signals are carefully designed for
the relay nodes that either diminish the eavesdropper's rate without affecting
that of the legitimate users, or increase the legitimate users' rates without
increasing that of the eavesdropper. The results show that there is no relaying
scheme that fits all conditions; the best relaying scheme depends on the system
parameters, namely, the relays' and eavesdropper's distances from the BS, and
the number of relays. They also show that the relatively simple cooperative
jamming scheme outperforms other schemes when the relays are far from the BS
and/or close to the eavesdropper.Comment: To appear in IEEE Globecom 201
Sum-Rate Maximization of RSMA-based Aerial Communications with Energy Harvesting: A Reinforcement Learning Approach
In this letter, we investigate a joint power and beamforming design problem
for rate-splitting multiple access (RSMA)-based aerial communications with
energy harvesting, where a self-sustainable aerial base station serves multiple
users by utilizing the harvested energy. Considering maximizing the sum-rate
from the long-term perspective, we utilize a deep reinforcement learning (DRL)
approach, namely the soft actor-critic algorithm, to restrict the maximum
transmission power at each time based on the stochastic property of the channel
environment, harvested energy, and battery power information. Moreover, for
designing precoders and power allocation among all the private/common streams
of the RSMA, we employ sequential least squares programming (SLSQP) using the
Han-Powell quasi-Newton method to maximize the sum-rate for the given
transmission power via DRL. Numerical results show the superiority of the
proposed scheme over several baseline methods in terms of the average sum-rate
performance.Comment: 13 pages, 4 figures, submitted to IEEE Wireless Communications
Letter
Retrospective Interference Alignment for Two-Cell Uplink MIMO Cellular Networks with Delayed CSIT
In this paper, we propose a new retrospective interference alignment for
two-cell multiple-input multiple-output (MIMO) interfering multiple access
channels (IMAC) with the delayed channel state information at the transmitters
(CSIT). It is shown that having delayed CSIT can strictly increase the sum-DoF
compared to the case of no CSIT. The key idea is to align multiple interfering
signals from adjacent cells onto a small dimensional subspace over time by
fully exploiting the previously received signals as side information with
outdated CSIT in a distributed manner. Remarkably, we show that the
retrospective interference alignment can achieve the optimal sum-DoF in the
context of two-cell two-user scenario by providing a new outer bound.Comment: 7 pages, 2 figures, to appear in IEEE ICC 201
- …