522 research outputs found
Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel
This paper investigates the problem of interference among the simultaneous
multiuser transmissions in the downlink of multiple antennas systems. Using
symbol level precoding, a new approach towards the multiuser interference is
discussed along this paper. The concept of exploiting the interference between
the spatial multiuser transmissions by jointly utilizing the data information
(DI) and channel state information (CSI), in order to design symbol-level
precoders, is proposed. In this direction, the interference among the data
streams is transformed under certain conditions to useful signal that can
improve the signal to interference noise ratio (SINR) of the downlink
transmissions. We propose a maximum ratio transmission (MRT) based algorithm
that jointly exploits DI and CSI to glean the benefits from constructive
multiuser interference. Subsequently, a relation between the constructive
interference downlink transmission and physical layer multicasting is
established. In this context, novel constructive interference precoding
techniques that tackle the transmit power minimization (min power) with
individual SINR constraints at each user's receivers is proposed. Furthermore,
fairness through maximizing the weighted minimum SINR (max min SINR) of the
users is addressed by finding the link between the min power and max min SINR
problems. Moreover, heuristic precoding techniques are proposed to tackle the
weighted sum rate problem. Finally, extensive numerical results show that the
proposed schemes outperform other state of the art techniques.Comment: Submitted to IEEE Transactions on Signal Processin
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
Linear Precoding and Equalization for Network MIMO with Partial Cooperation
A cellular multiple-input multiple-output (MIMO) downlink system is studied
in which each base station (BS) transmits to some of the users, so that each
user receives its intended signal from a subset of the BSs. This scenario is
referred to as network MIMO with partial cooperation, since only a subset of
the BSs are able to coordinate their transmission towards any user. The focus
of this paper is on the optimization of linear beamforming strategies at the
BSs and at the users for network MIMO with partial cooperation. Individual
power constraints at the BSs are enforced, along with constraints on the number
of streams per user. It is first shown that the system is equivalent to a MIMO
interference channel with generalized linear constraints (MIMO-IFC-GC). The
problems of maximizing the sum-rate(SR) and minimizing the weighted sum mean
square error (WSMSE) of the data estimates are non-convex, and suboptimal
solutions with reasonable complexity need to be devised. Based on this,
suboptimal techniques that aim at maximizing the sum-rate for the MIMO-IFC-GC
are reviewed from recent literature and extended to the MIMO-IFC-GC where
necessary. Novel designs that aim at minimizing the WSMSE are then proposed.
Extensive numerical simulations are provided to compare the performance of the
considered schemes for realistic cellular systems.Comment: 13 pages, 5 figures, published in IEEE Transactions on Vehicular
Technology, June 201
Transmit Optimization with Improper Gaussian Signaling for Interference Channels
This paper studies the achievable rates of Gaussian interference channels
with additive white Gaussian noise (AWGN), when improper or circularly
asymmetric complex Gaussian signaling is applied. For the Gaussian
multiple-input multiple-output interference channel (MIMO-IC) with the
interference treated as Gaussian noise, we show that the user's achievable rate
can be expressed as a summation of the rate achievable by the conventional
proper or circularly symmetric complex Gaussian signaling in terms of the
users' transmit covariance matrices, and an additional term, which is a
function of both the users' transmit covariance and pseudo-covariance matrices.
The additional degrees of freedom in the pseudo-covariance matrix, which is
conventionally set to be zero for the case of proper Gaussian signaling,
provide an opportunity to further improve the achievable rates of Gaussian
MIMO-ICs by employing improper Gaussian signaling. To this end, this paper
proposes widely linear precoding, which efficiently maps proper
information-bearing signals to improper transmitted signals at each transmitter
for any given pair of transmit covariance and pseudo-covariance matrices. In
particular, for the case of two-user Gaussian single-input single-output
interference channel (SISO-IC), we propose a joint covariance and
pseudo-covariance optimization algorithm with improper Gaussian signaling to
achieve the Pareto-optimal rates. By utilizing the separable structure of the
achievable rate expression, an alternative algorithm with separate covariance
and pseudo-covariance optimization is also proposed, which guarantees the rate
improvement over conventional proper Gaussian signaling.Comment: Accepted by IEEE Transactions on Signal Processin
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
- …