921 research outputs found
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser downlink systems which
aims at creating constructive interference among the transmitted data streams.
This can be enabled by designing the precoded signal of the multiantenna
transmitter on a symbol level, taking into account both channel state
information and data symbols. Previous literature has studied this paradigm for
MPSK modulations by addressing various performance metrics, such as power
minimization and maximization of the minimum rate. In this paper, we extend
this to generic multi-level modulations i.e. MQAM and APSK by establishing
connection to PHY layer multicasting with phase constraints. Furthermore, we
address adaptive modulation schemes which are crucial in enabling the
throughput scaling of symbol-level precoded systems. In this direction, we
design signal processing algorithms for minimizing the required power under
per-user SINR or goodput constraints. Extensive numerical results show that the
proposed algorithm provides considerable power and energy efficiency gains,
while adapting the employed modulation scheme to match the requested data rate
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
Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications
The present work focuses on the forward link of a broadband multibeam
satellite system that aggressively reuses the user link frequency resources.
Two fundamental practical challenges, namely the need to frame multiple users
per transmission and the per-antenna transmit power limitations, are addressed.
To this end, the so-called frame-based precoding problem is optimally solved
using the principles of physical layer multicasting to multiple co-channel
groups under per-antenna constraints. In this context, a novel optimization
problem that aims at maximizing the system sum rate under individual power
constraints is proposed. Added to that, the formulation is further extended to
include availability constraints. As a result, the high gains of the sum rate
optimal design are traded off to satisfy the stringent availability
requirements of satellite systems. Moreover, the throughput maximization with a
granular spectral efficiency versus SINR function, is formulated and solved.
Finally, a multicast-aware user scheduling policy, based on the channel state
information, is developed. Thus, substantial multiuser diversity gains are
gleaned. Numerical results over a realistic simulation environment exhibit as
much as 30% gains over conventional systems, even for 7 users per frame,
without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless
Communications, 201
Coordinated Multicasting with Opportunistic User Selection in Multicell Wireless Systems
Physical layer multicasting with opportunistic user selection (OUS) is
examined for multicell multi-antenna wireless systems. By adopting a two-layer
encoding scheme, a rate-adaptive channel code is applied in each fading block
to enable successful decoding by a chosen subset of users (which varies over
different blocks) and an application layer erasure code is employed across
multiple blocks to ensure that every user is able to recover the message after
decoding successfully in a sufficient number of blocks. The transmit signal and
code-rate in each block determine opportunistically the subset of users that
are able to successfully decode and can be chosen to maximize the long-term
multicast efficiency. The employment of OUS not only helps avoid
rate-limitations caused by the user with the worst channel, but also helps
coordinate interference among different cells and multicast groups. In this
work, efficient algorithms are proposed for the design of the transmit
covariance matrices, the physical layer code-rates, and the target user subsets
in each block. In the single group scenario, the system parameters are
determined by maximizing the group-rate, defined as the physical layer
code-rate times the fraction of users that can successfully decode in each
block. In the multi-group scenario, the system parameters are determined by
considering a group-rate balancing optimization problem, which is solved by a
successive convex approximation (SCA) approach. To further reduce the feedback
overhead, we also consider the case where only part of the users feed back
their channel vectors in each block and propose a design based on the balancing
of the expected group-rates. In addition to SCA, a sample average approximation
technique is also introduced to handle the probabilistic terms arising in this
problem. The effectiveness of the proposed schemes is demonstrated by computer
simulations.Comment: Accepted by IEEE Transactions on Signal Processin
Real Coded Genetic Algorithm with Enhanced Abilities for Adaptation Applied to Optimisation of MIMO Systems
This article presents an investigation of real coded Genetic Algorithm Blend
Crossover Alpha modification, with enhanced ability for adaptation, applied to minimisation of transmit power in multiple-input multiple-output (MIMO) systems beamforming. The goal is to formulate transmit power minimisation task as a black box software object and evaluate an alternative to currently existing methods for optimisation of transmit energy in multicast system constrained by signal to noise ratio. The novelty of this adaptive methodology for determination of minimal power level within certain Quality of Service criteria is that it guarantees satisfaction of the constraint and 100% feasibility of achieved solutions. In addition this methodology excludes retuning algorithms parameters by using black box model for the problem definition. Experiments are conducted for identification of weight vectors assigned for signal strength and direction. Achieved experimental results are presented and analysed
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