3,242 research outputs found
Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters
In a cooperative multiple-antenna downlink cellular network, maximization of
a concave function of user rates is considered. A new linear precoding
technique called soft interference nulling (SIN) is proposed, which performs at
least as well as zero-forcing (ZF) beamforming. All base stations share channel
state information, but each user's message is only routed to those that
participate in the user's coordination cluster. SIN precoding is particularly
useful when clusters of limited sizes overlap in the network, in which case
traditional techniques such as dirty paper coding or ZF do not directly apply.
The SIN precoder is computed by solving a sequence of convex optimization
problems. SIN under partial network coordination can outperform ZF under full
network coordination at moderate SNRs. Under overlapping coordination clusters,
SIN precoding achieves considerably higher throughput compared to myopic ZF,
especially when the clusters are large.Comment: 13 pages, 5 figure
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Interference Aware-Coordinated Beamforming System in a Two-Cell Environment
In this paper, we propose jointly optimized transceiver algorithms called interference aware coordinated beamforming (IA-CBF) for a two-cell system where each base station is equipped with multiple transmit antennas. The case of single stream transmission to two mobile stations with two or more receive antennas is considered. First we propose minimum-mean-square-error IA-CBF using a lower bound on the achievable sumrate. Next we derive optimal (under an assumption of zero other-cell interference) and suboptimal transmit beamforming vectors called zero-forcing IA-CBF. We also investigate the optimality of the proposed IA-CBF algorithms with respect to the number of receive antennas. Analytical and numerical results confirm that the proposed system with two transmit/receive antennas achieves full degrees of freedom (a.k.a. multiplexing gain) of the two-cell multiple-input multiple-output channel while showing a better sum rate performance than the conventional solutions such as non-cooperative eigen-beamforming and interference nulling.Engineering and Applied Science
Adaptive Bit Partitioning for Multicell Intercell Interference Nulling with Delayed Limited Feedback
Base station cooperation can exploit knowledge of the users' channel state
information (CSI) at the transmitters to manage co-channel interference. Users
have to feedback CSI of the desired and interfering channels using
finite-bandwidth backhaul links. Existing codebook designs for single-cell
limited feedback can be used for multicell cooperation by partitioning the
available feedback resources between the multiple channels. In this paper, a
new feedback-bit allocation strategy is proposed, as a function of the delays
in the communication links and received signal strengths in the downlink.
Channel temporal correlation is modeled as a function of delay using the
Gauss-Markov model. Closed-form expressions for bit partitions are derived to
allocate more bits to quantize the stronger channels with smaller delays and
fewer bits to weaker channels with larger delays, assuming random vector
quantization. Cellular network simulations are used to show that the proposed
algorithm yields higher sum-rates than an equal-bit allocation technique.Comment: Submitted to IEEE Transactions on Signal Processing, July 201
Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints
Block diagonalization (BD) is a practical linear precoding technique that
eliminates the inter-user interference in downlink multiuser multiple-input
multiple-output (MIMO) systems. In this paper, we apply BD to the downlink
transmission in a cooperative multi-cell MIMO system, where the signals from
different base stations (BSs) to all the mobile stations (MSs) are jointly
designed with the perfect knowledge of the downlink channels and transmit
messages. Specifically, we study the optimal BD precoder design to maximize the
weighted sum-rate of all the MSs subject to a set of per-BS power constraints.
This design problem is formulated in an auxiliary MIMO broadcast channel (BC)
with a set of transmit power constraints corresponding to those for individual
BSs in the multi-cell system. By applying convex optimization techniques, this
paper develops an efficient algorithm to solve this problem, and derives the
closed-form expression for the optimal BD precoding matrix. It is revealed that
the optimal BD precoding vectors for each MS in the per-BS power constraint
case are in general non-orthogonal, which differs from the conventional
orthogonal BD precoder design for the MIMO-BC under one single sum-power
constraint. Moreover, for the special case of single-antenna BSs and MSs, the
proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF)
precoder design for the weighted sum-rate maximization in the multiple-input
single-output (MISO) BC with per-antenna power constraints. Suboptimal and
low-complexity BD/ZF-BF precoding schemes are also presented, and their
achievable rates are compared against those with the optimal schemes.Comment: accepted in JSAC, special issue on cooperative communications on
cellular networks, June 201
Downlink Noncoherent Cooperation without Transmitter Phase Alignment
Multicell joint processing can mitigate inter-cell interference and thereby
increase the spectral efficiency of cellular systems. Most previous work has
assumed phase-aligned (coherent) transmissions from different base transceiver
stations (BTSs), which is difficult to achieve in practice. In this work, a
noncoherent cooperative transmission scheme for the downlink is studied, which
does not require phase alignment. The focus is on jointly serving two users in
adjacent cells sharing the same resource block. The two BTSs partially share
their messages through a backhaul link, and each BTS transmits a superposition
of two codewords, one for each receiver. Each receiver decodes its own message,
and treats the signals for the other receiver as background noise. With
narrowband transmissions the achievable rate region and maximum achievable
weighted sum rate are characterized by optimizing the power allocation (and the
beamforming vectors in the case of multiple transmit antennas) at each BTS
between its two codewords. For a wideband (multicarrier) system, a dual
formulation of the optimal power allocation problem across sub-carriers is
presented, which can be efficiently solved by numerical methods. Results show
that the proposed cooperation scheme can improve the sum rate substantially in
the low to moderate signal-to-noise ratio (SNR) range.Comment: 30 pages, 6 figures, submitted to IEEE Transactions on Wireless
Communication
Energy Efficient Coordinated Beamforming for Multi-cell MISO Systems
In this paper, we investigate the optimal energy efficient coordinated
beamforming in multi-cell multiple-input single-output (MISO) systems with
multiple-antenna base stations (BS) and single-antenna mobile stations
(MS), where each BS sends information to its own intended MS with cooperatively
designed transmit beamforming. We assume single user detection at the MS by
treating the interference as noise. By taking into account a realistic power
model at the BS, we characterize the Pareto boundary of the achievable energy
efficiency (EE) region of the links, where the EE of each link is defined
as the achievable data rate at the MS divided by the total power consumption at
the BS. Since the EE of each link is non-cancave (which is a non-concave
function over an affine function), characterizing this boundary is difficult.
To meet this challenge, we relate this multi-cell MISO system to cognitive
radio (CR) MISO channels by applying the concept of interference temperature
(IT), and accordingly transform the EE boundary characterization problem into a
set of fractional concave programming problems. Then, we apply the fractional
concave programming technique to solve these fractional concave problems, and
correspondingly give a parametrization for the EE boundary in terms of IT
levels. Based on this characterization, we further present a decentralized
algorithm to implement the multi-cell coordinated beamforming, which is shown
by simulations to achieve the EE Pareto boundary.Comment: 6 pages, 2 figures, to be presented in IEEE GLOBECOM 201
Coordinated Multicast Beamforming in Multicell Networks
We study physical layer multicasting in multicell networks where each base
station, equipped with multiple antennas, transmits a common message using a
single beamformer to multiple users in the same cell. We investigate two
coordinated beamforming designs: the quality-of-service (QoS) beamforming and
the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The
goal of the QoS beamforming is to minimize the total power consumption while
guaranteeing that received SINR at each user is above a predetermined
threshold. We present a necessary condition for the optimization problem to be
feasible. Then, based on the decomposition theory, we propose a novel
decentralized algorithm to implement the coordinated beamforming with limited
information sharing among different base stations. The algorithm is guaranteed
to converge and in most cases it converges to the optimal solution. The max-min
SINR (MMS) beamforming is to maximize the minimum received SINR among all users
under per-base station power constraints. We show that the MMS problem and a
weighted peak-power minimization (WPPM) problem are inverse problems. Based on
this inversion relationship, we then propose an efficient algorithm to solve
the MMS problem in an approximate manner. Simulation results demonstrate
significant advantages of the proposed multicast beamforming algorithms over
conventional multicasting schemes.Comment: 10pages, 9 figure
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