805 research outputs found
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
The main focus and contribution of this paper is a novel network-MIMO TDD
architecture that achieves spectral efficiencies comparable with "Massive
MIMO", with one order of magnitude fewer antennas per active user per cell. The
proposed architecture is based on a family of network-MIMO schemes defined by
small clusters of cooperating base stations, zero-forcing multiuser MIMO
precoding with suitable inter-cluster interference constraints, uplink pilot
signals reuse across cells, and frequency reuse. The key idea consists of
partitioning the users population into geographically determined "bins", such
that all users in the same bin are statistically equivalent, and use the
optimal network-MIMO architecture in the family for each bin. A scheduler takes
care of serving the different bins on the time-frequency slots, in order to
maximize a desired network utility function that captures some desired notion
of fairness. This results in a mixed-mode network-MIMO architecture, where
different schemes, each of which is optimized for the served user bin, are
multiplexed in time-frequency. In order to carry out the performance analysis
and the optimization of the proposed architecture in a clean and
computationally efficient way, we consider the large-system regime where the
number of users, the number of antennas, and the channel coherence block length
go to infinity with fixed ratios. The performance predicted by the large-system
asymptotic analysis matches very well the finite-dimensional simulations.
Overall, the system spectral efficiency obtained by the proposed architecture
is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the
number of antennas at the base stations (roughly, from 500 to 50 antennas).Comment: Full version with appendice (proofs of theorems). A shortened version
without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B
was revised after submissio
Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness
This paper addresses coordinated downlink beamforming optimization in
multicell time-division duplex (TDD) systems where a small number of parameters
are exchanged between cells but with no data sharing. With the goal to reach
the point on the Pareto boundary with max-min rate fairness, we first develop a
two-step centralized optimization algorithm to design the joint beamforming
vectors. This algorithm can achieve a further sum-rate improvement over the
max-min optimal performance, and is shown to guarantee max-min Pareto
optimality for scenarios with two base stations (BSs) each serving a single
user. To realize a distributed solution with limited intercell communication,
we then propose an iterative algorithm by exploiting an approximate
uplink-downlink duality, in which only a small number of positive scalars are
shared between cells in each iteration. Simulation results show that the
proposed distributed solution achieves a fairness rate performance close to the
centralized algorithm while it has a better sum-rate performance, and
demonstrates a better tradeoff between sum-rate and fairness than the Nash
Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201
Inter-micro-operator interference protection in dynamic TDD system
Abstract. This thesis considers the problem of weighted sum-rate maximization (WSRM) for a system of micro-operators subject to inter-micro-operator interference constraints with dynamic time division duplexing. The WSRM problem is non-convex and non-deterministic polynomial hard. Furthermore, micro-operators require minimum coordination among themselves making the inter-micro-operator interference management very challenging. In this regard, we propose two decentralized precoder design algorithm based on over-the-air bi-directional signalling strategy. We first propose a precoder design algorithm by considering the equivalent weighted minimum mean-squared error minimization reformulation of the WSRM problem. Later we propose precoder design algorithm by considering the weighted sum mean-squared error reformulation. In both approaches, to reduce the huge signalling requirements in centralized design, we use alternating direction method of multipliers technique, wherein each downlink-operator base station and uplink-operator user determines only the relevant set of transmit precoders by exchanging minimal information among the coordinating base stations and user equipments. To minimize the coordination between the uplink-opeator users, we propose interference budget allocation scheme based on reference signal measurements from downlink-operator users. Numerical simulations are provided to compare the performance of proposed algorithms with and without the inter-micro-operator interference constraints
Interference Management in 5G Reverse TDD HetNets with Wireless Backhaul: A Large System Analysis
This work analyzes a heterogeneous network (HetNet), which comprises a macro
base station (BS) equipped with a large number of antennas and an overlaid
dense tier of small cell access points (SCAs) using a wireless backhaul for
data traffic. The static and low mobility user equipment terminals (UEs) are
associated with the SCAs while those with medium-to-high mobility are served by
the macro BS. A reverse time division duplexing (TDD) protocol is used by the
two tiers, which allows the BS to locally estimate both the intra-tier and
inter-tier channels. This knowledge is then used at the BS either in the uplink
(UL) or in the downlink (DL) to simultaneously serve the macro UEs (MUEs) and
to provide the wireless backhaul to SCAs. A geographical separation of
co-channel SCAs is proposed to limit the interference coming from the UL
signals of MUEs. A concatenated linear precoding technique employing either
zero-forcing (ZF) or regularized ZF is used at the BS to simultaneously serve
MUEs and SCAs in DL while nulling interference toward those SCAs in UL. We
evaluate and characterize the performance of the system through the power
consumption of UL and DL transmissions under the assumption that target rates
must be satisfied and imperfect channel state information is available for
MUEs. The analysis is conducted in the asymptotic regime where the number of BS
antennas and the network size (MUEs and SCAs) grow large with fixed ratios.
Results from large system analysis are used to provide concise formulae for the
asymptotic UL and DL transmit powers and precoding vectors under the above
assumptions. Numerical results are used to validate the analysis in different
settings and to make comparisons with alternative network architectures.Comment: 14 pages, 12 figures. To appear IEEE J. Select. Areas Commun. --
Special Issue on HetNet
Interference Mitigation for Cognitive Radio MIMO Systems Based on Practical Precoding
In this paper, we propose two subspace-projection-based precoding schemes,
namely, full-projection (FP)- and partial-projection (PP)-based precoding, for
a cognitive radio multiple-input multiple-output (CR-MIMO) network to mitigate
its interference to a primary time-division-duplexing (TDD) system. The
proposed precoding schemes are capable of estimating interference channels
between CR and primary networks, and incorporating the interference from the
primary to the CR system into CR precoding via a novel sensing approach. Then,
the CR performance and resulting interference of the proposed precoding schemes
are analyzed and evaluated. By fully projecting the CR transmission onto a null
space of the interference channels, the FP-based precoding scheme can
effectively avoid interfering the primary system with boosted CR throughput.
While, the PP-based scheme is able to further improve the CR throughput by
partially projecting its transmission onto the null space.Comment: 12 pages, 4 figures, submitted to the IEEE Trans. Wireless
Communications in April 201
MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network
Ultra-dense network (UDN) has been considered as a promising candidate for
future 5G network to meet the explosive data demand. To realize UDN, a
reliable, Gigahertz bandwidth, and cost-effective backhaul connecting
ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite.
Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless
backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the
improved link reliability. In this article, we discuss the feasibility of
mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and
challenges are also addressed. Especially, we propose a digitally-controlled
phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave
massive MIMO, whereby the low-rank property of mmWave massive MIMO channel
matrix is leveraged to reduce the required cost and complexity of transceiver
with a negligible performance loss. One key feature of the proposed scheme is
that the macro-cell BS can simultaneously support multiple small-cell BSs with
multiple streams for each smallcell BS, which is essentially different from
conventional hybrid precoding/combining schemes typically limited to
single-user MIMO with multiple streams or multi-user MIMO with single stream
for each user. Based on the proposed scheme, we further explore the fundamental
issues of developing mmWave massive MIMO for wireless backhaul, and the
associated challenges, insight, and prospect to enable the mmWave massive MIMO
based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter
waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property
of mmWave massive MIMO channels, sparse channel estimation, compressive
sensing (CS), hybrid digital/analog precoding/combining, and hybrid
beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653
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