15,879 research outputs found
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
Limited Feedback Design for Interference Alignment on MIMO Interference Networks with Heterogeneous Path Loss and Spatial Correlations
Interference alignment is degree of freedom optimal in K -user MIMO
interference channels and many previous works have studied the transceiver
designs. However, these works predominantly focus on networks with perfect
channel state information at the transmitters and symmetrical interference
topology. In this paper, we consider a limited feedback system with
heterogeneous path loss and spatial correlations, and investigate how the
dynamics of the interference topology can be exploited to improve the feedback
efficiency. We propose a novel spatial codebook design, and perform dynamic
quantization via bit allocations to adapt to the asymmetry of the interference
topology. We bound the system throughput under the proposed dynamic scheme in
terms of the transmit SNR, feedback bits and the interference topology
parameters. It is shown that when the number of feedback bits scales with SNR
as C_{s}\cdot\log\textrm{SNR}, the sum degrees of freedom of the network are
preserved. Moreover, the value of scaling coefficient C_{s} can be
significantly reduced in networks with asymmetric interference topology.Comment: 30 pages, 6 figures, accepted by IEEE transactions on signal
processing in Feb. 201
The Practical Challenges of Interference Alignment
Interference alignment (IA) is a revolutionary wireless transmission strategy
that reduces the impact of interference. The idea of interference alignment is
to coordinate multiple transmitters so that their mutual interference aligns at
the receivers, facilitating simple interference cancellation techniques. Since
IA's inception, researchers have investigated its performance and proposed
improvements, verifying IA's ability to achieve the maximum degrees of freedom
(an approximation of sum capacity) in a variety of settings, developing
algorithms for determining alignment solutions, and generalizing transmission
strategies that relax the need for perfect alignment but yield better
performance. This article provides an overview of the concept of interference
alignment as well as an assessment of practical issues including performance in
realistic propagation environments, the role of channel state information at
the transmitter, and the practicality of interference alignment in large
networks.Comment: submitted to IEEE Wireless Communications Magazin
On the Benefits of Edge Caching for MIMO Interference Alignment
In this contribution, we jointly investigate the benefits of caching and
interference alignment (IA) in multiple-input multiple-output (MIMO)
interference channel under limited backhaul capacity. In particular, total
average transmission rate is derived as a function of various system parameters
such as backhaul link capacity, cache size, number of active
transmitter-receiver pairs as well as the quantization bits for channel state
information (CSI). Given the fact that base stations are equipped both with
caching and IA capabilities and have knowledge of content popularity profile,
we then characterize an operational regime where the caching is beneficial.
Subsequently, we find the optimal number of transmitter-receiver pairs that
maximizes the total average transmission rate. When the popularity profile of
requested contents falls into the operational regime, it turns out that caching
substantially improves the throughput as it mitigates the backhaul usage and
allows IA methods to take benefit of such limited backhaul.Comment: 20 pages, 5 figures. A shorter version is to be presented at 16th
IEEE International Workshop on Signal Processing Advances in Wireless
Communications (SPAWC'2015), Stockholm, Swede
Interference Management in Heterogeneous Networks with Blind Transmitters
Future multi-tier communication networks will require enhanced network
capacity and reduced overhead. In the absence of Channel State Information
(CSI) at the transmitters, Blind Interference Alignment (BIA) and Topological
Interference Management (TIM) can achieve optimal Degrees of Freedom (DoF),
minimising network's overhead. In addition, Non-Orthogonal Multiple Access
(NOMA) can increase the sum rate of the network, compared to orthogonal radio
access techniques currently adopted by 4G networks. Our contribution is two
interference management schemes, BIA and a hybrid TIM-NOMA scheme, employed in
heterogeneous networks by applying user-pairing and Kronecker Product
representation. BIA manages inter- and intra-cell interference by antenna
selection and appropriate message scheduling. The hybrid scheme manages
intra-cell interference based on NOMA and inter-cell interference based on TIM.
We show that both schemes achieve at least double the rate of TDMA. The hybrid
scheme always outperforms TDMA and BIA in terms of Degrees of Freedom (DoF).
Comparing the two proposed schemes, BIA achieves more DoF than TDMA under
certain restrictions, and provides better Bit-Error-Rate (BER) and sum rate
performance to macrocell users, whereas the hybrid scheme improves the
performance of femtocell users.Comment: 30 pages, 18 figure
Opportunistic Scheduling for Full-Duplex Uplink-Downlink Networks
We study opportunistic scheduling and the sum capacity of cellular networks
with a full-duplex multi-antenna base station and a large number of
single-antenna half-duplex users. Simultaneous uplink and downlink over the
same band results in uplink-to-downlink interference, degrading performance. We
present a simple opportunistic joint uplink-downlink scheduling algorithm that
exploits multiuser diversity and treats interference as noise. We show that in
homogeneous networks, our algorithm achieves the same sum capacity as what
would have been achieved if there was no uplink-to-downlink interference,
asymptotically in the number of users. The algorithm does not require
interference CSI at the base station or uplink users. It is also shown that for
a simple class of heterogeneous networks without sufficient channel diversity,
it is not possible to achieve the corresponding interference-free system
capacity. We discuss the potential for using device-to-device side-channels to
overcome this limitation in heterogeneous networks.Comment: 10 pages, 2 figures, to appear at IEEE International Symposium on
Information Theory (ISIT) '1
Dynamic Interference Mitigation for Generalized Partially Connected Quasi-static MIMO Interference Channel
Recent works on MIMO interference channels have shown that interference
alignment can significantly increase the achievable degrees of freedom (DoF) of
the network. However, most of these works have assumed a fully connected
interference graph. In this paper, we investigate how the partial connectivity
can be exploited to enhance system performance in MIMO interference networks.
We propose a novel interference mitigation scheme which introduces constraints
for the signal subspaces of the precoders and decorrelators to mitigate "many"
interference nulling constraints at a cost of "little" freedoms in precoder and
decorrelator design so as to extend the feasibility region of the interference
alignment scheme. Our analysis shows that the proposed algorithm can
significantly increase system DoF in symmetric partially connected MIMO
interference networks. We also compare the performance of the proposed scheme
with various baselines and show via simulations that the proposed algorithms
could achieve significant gain in the system performance of randomly connected
interference networks.Comment: 30 pages, 10 figures, accepted by IEEE Transaction on Signal
Processin
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