12,042 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
Low-Complexity OFDM Spectral Precoding
This paper proposes a new large-scale mask-compliant spectral precoder
(LS-MSP) for orthogonal frequency division multiplexing systems. In this paper,
we first consider a previously proposed mask-compliant spectral precoding
scheme that utilizes a generic convex optimization solver which suffers from
high computational complexity, notably in large-scale systems. To mitigate the
complexity of computing the LS-MSP, we propose a divide-and-conquer approach
that breaks the original problem into smaller rank 1 quadratic-constraint
problems and each small problem yields closed-form solution. Based on these
solutions, we develop three specialized first-order low-complexity algorithms,
based on 1) projection on convex sets and 2) the alternating direction method
of multipliers. We also develop an algorithm that capitalizes on the
closed-form solutions for the rank 1 quadratic constraints, which is referred
to as 3) semi-analytical spectral precoding. Numerical results show that the
proposed LS-MSP techniques outperform previously proposed techniques in terms
of the computational burden while complying with the spectrum mask. The results
also indicate that 3) typically needs 3 iterations to achieve similar results
as 1) and 2) at the expense of a slightly increased computational complexity.Comment: Accepted in IEEE International Workshop on Signal Processing Advances
in Wireless Communications (SPAWC), 201
Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression
This paper proposes a multistage decomposition for blind adaptive parameter estimation in the Krylov subspace with the code-constrained constant modulus (CCM) design criterion. Based on constrained optimization of the constant modulus cost function and utilizing the Lanczos algorithm and Arnoldi-like iterations, a multistage decomposition is developed for blind parameter estimation. A family of computationally efficient blind adaptive reduced-rank stochastic gradient (SG) and recursive least squares (RLS) type algorithms along with an automatic rank selection procedure are also devised and evaluated against existing methods. An analysis of the convergence properties of the method is carried out and convergence conditions for the reduced-rank adaptive algorithms are established. Simulation results consider the application of the proposed techniques to the suppression of multiaccess and intersymbol interference in DS-CDMA systems
Space-Time Signal Design for Multilevel Polar Coding in Slow Fading Broadcast Channels
Slow fading broadcast channels can model a wide range of applications in
wireless networks. Due to delay requirements and the unavailability of the
channel state information at the transmitter (CSIT), these channels for many
applications are non-ergodic. The appropriate measure for designing signals in
non-ergodic channels is the outage probability. In this paper, we provide a
method to optimize STBCs based on the outage probability at moderate SNRs.
Multilevel polar coded-modulation is a new class of coded-modulation techniques
that benefits from low complexity decoders and simple rate matching. In this
paper, we derive the outage optimality condition for multistage decoding and
propose a rule for determining component code rates. We also derive an upper
bound on the outage probability of STBCs for designing the
set-partitioning-based labelling. Finally, due to the optimality of the
outage-minimized STBCs for long codes, we introduce a novel method for the
joint optimization of short-to-moderate length polar codes and STBCs
Low-Complexity Reduced-Rank Beamforming Algorithms
A reduced-rank framework with set-membership filtering (SMF) techniques is
presented for adaptive beamforming problems encountered in radar systems. We
develop and analyze stochastic gradient (SG) and recursive least squares
(RLS)-type adaptive algorithms, which achieve an enhanced convergence and
tracking performance with low computational cost as compared to existing
techniques. Simulations show that the proposed algorithms have a superior
performance to prior methods, while the complexity is lower.Comment: 7 figure
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