3,041 research outputs found
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
Design guidelines for spatial modulation
A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants
High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation
In this paper, we present a low-complexity algorithm for detection in
high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that
achieve high spectral efficiencies of the order of tens of bps/Hz. We also
present a training-based iterative detection/channel estimation scheme for such
large STBC MIMO systems. Our simulation results show that excellent bit error
rate and nearness-to-capacity performance are achieved by the proposed
multistage likelihood ascent search (M-LAS) detector in conjunction with the
proposed iterative detection/channel estimation scheme at low complexities. The
fact that we could show such good results for large STBCs like 16x16 and 32x32
STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in
excess of 20 bps/Hz (even after accounting for the overheads meant for pilot
based training for channel estimation and turbo coding) establishes the
effectiveness of the proposed detector and channel estimator. We decode perfect
codes of large dimensions using the proposed detector. With the feasibility of
such a low-complexity detection/channel estimation scheme, large-MIMO systems
with tens of antennas operating at several tens of bps/Hz spectral efficiencies
can become practical, enabling interesting high data rate wireless
applications.Comment: v3: Performance/complexity comparison of the proposed scheme with
other large-MIMO architectures/detectors has been added (Sec. IV-D). The
paper has been accepted for publication in IEEE Journal of Selected Topics in
Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO
Systems. v2: Section V on Channel Estimation is update
Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding
In this work, we propose a subspace-based algorithm for DOA estimation which
iteratively reduces the disturbance factors of the estimated data covariance
matrix and incorporates prior knowledge which is gradually obtained on line. An
analysis of the MSE of the reshaped data covariance matrix is carried out along
with comparisons between computational complexities of the proposed and
existing algorithms. Simulations focusing on closely-spaced sources, where they
are uncorrelated and correlated, illustrate the improvements achieved.Comment: 7 figures. arXiv admin note: text overlap with arXiv:1703.1052
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