2,260 research outputs found
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
Random Beamforming with Heterogeneous Users and Selective Feedback: Individual Sum Rate and Individual Scaling Laws
This paper investigates three open problems in random beamforming based
communication systems: the scheduling policy with heterogeneous users, the
closed form sum rate, and the randomness of multiuser diversity with selective
feedback. By employing the cumulative distribution function based scheduling
policy, we guarantee fairness among users as well as obtain multiuser diversity
gain in the heterogeneous scenario. Under this scheduling framework, the
individual sum rate, namely the average rate for a given user multiplied by the
number of users, is of interest and analyzed under different feedback schemes.
Firstly, under the full feedback scheme, we derive the closed form individual
sum rate by employing a decomposition of the probability density function of
the selected user's signal-to-interference-plus-noise ratio. This technique is
employed to further obtain a closed form rate approximation with selective
feedback in the spatial dimension. The analysis is also extended to random
beamforming in a wideband OFDMA system with additional selective feedback in
the spectral dimension wherein only the best beams for the best-L resource
blocks are fed back. We utilize extreme value theory to examine the randomness
of multiuser diversity incurred by selective feedback. Finally, by leveraging
the tail equivalence method, the multiplicative effect of selective feedback
and random observations is observed to establish the individual rate scaling.Comment: Submitted in March 2012. To appear in IEEE Transactions on Wireless
Communications. Part of this paper builds upon the following letter: Y. Huang
and B. D. Rao, "Closed form sum rate of random beamforming", IEEE Commun.
Lett., vol. 16, no. 5, pp. 630-633, May 201
Achieving Large Multiplexing Gain in Distributed Antenna Systems via Cooperation with pCell Technology
In this paper we present pCellTM technology, the first commercial-grade
wireless system that employs cooperation between distributed transceiver
stations to create concurrent data links to multiple users in the same
spectrum. First we analyze the per-user signal-to-interference-plus-noise ratio
(SINR) employing a geometrical spatial channel model to define volumes in space
of coherent signal around user antennas (or personal cells, i.e., pCells). Then
we describe the system architecture consisting of a general-purpose-processor
(GPP) based software-defined radio (SDR) wireless platform implementing a
real-time LTE protocol stack to communicate with off-the-shelf LTE devices.
Finally we present experimental results demonstrating up to 16 concurrent
spatial channels for an aggregate average spectral efficiency of 59.3 bps/Hz in
the downlink and 27.5 bps/Hz in the uplink, providing data rates of 200 Mbps
downlink and 25 Mbps uplink in 5 MHz of TDD spectrum.Comment: IEEE Asilomar Conference on Signals, Systems, and Computers, Nov.
8-11th 2015, Pacific Grove, CA, US
Power Efficient and Secure Full-Duplex Wireless Communication Systems
In this paper, we study resource allocation for a full-duplex (FD) radio base
station serving multiple half-duplex (HD) downlink and uplink users
simultaneously. The considered resource allocation algorithm design is
formulated as a non-convex optimization problem taking into account minimum
required receive signal-to-interference-plus-noise ratios (SINRs) for downlink
and uplink communication and maximum tolerable SINRs at potential
eavesdroppers. The proposed optimization framework enables secure downlink and
uplink communication via artificial noise generation in the downlink for
interfering the potential eavesdroppers. We minimize the weighted sum of the
total downlink and uplink transmit power by jointly optimizing the downlink
beamformer, the artificial noise covariance matrix, and the uplink transmit
power. We adopt a semidefinite programming (SDP) relaxation approach to obtain
a tractable solution for the considered problem. The tightness of the SDP
relaxation is revealed by examining a sufficient condition for the global
optimality of the solution. Simulation results demonstrate the excellent
performance achieved by the proposed scheme and the significant transmit power
savings enabled optimization of the artificial noise covariance matrix.Comment: 6 pages, invited paper, IEEE Conference on Communications and Network
Security (CNS) 2015 in Florence, Italy, on September 30, 201
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
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