2,549 research outputs found
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
Asymptotic Task-Based Quantization with Application to Massive MIMO
Quantizers take part in nearly every digital signal processing system which
operates on physical signals. They are commonly designed to accurately
represent the underlying signal, regardless of the specific task to be
performed on the quantized data. In systems working with high-dimensional
signals, such as massive multiple-input multiple-output (MIMO) systems, it is
beneficial to utilize low-resolution quantizers, due to cost, power, and memory
constraints. In this work we study quantization of high-dimensional inputs,
aiming at improving performance under resolution constraints by accounting for
the system task in the quantizers design. We focus on the task of recovering a
desired signal statistically related to the high-dimensional input, and analyze
two quantization approaches: We first consider vector quantization, which is
typically computationally infeasible, and characterize the optimal performance
achievable with this approach. Next, we focus on practical systems which
utilize hardware-limited scalar uniform analog-to-digital converters (ADCs),
and design a task-based quantizer under this model. The resulting system
accounts for the task by linearly combining the observed signal into a lower
dimension prior to quantization. We then apply our proposed technique to
channel estimation in massive MIMO networks. Our results demonstrate that a
system utilizing low-resolution scalar ADCs can approach the optimal channel
estimation performance by properly accounting for the task in the system
design
Asymptotic Analysis of SU-MIMO Channels With Transmitter Noise and Mismatched Joint Decoding
Hardware impairments in radio-frequency components of a wireless system cause
unavoidable distortions to transmission that are not captured by the
conventional linear channel model. In this paper, a 'binoisy' single-user
multiple-input multiple-output (SU-MIMO) relation is considered where the
additional distortions are modeled via an additive noise term at the transmit
side. Through this extended SU-MIMO channel model, the effects of transceiver
hardware impairments on the achievable rate of multi-antenna point-to-point
systems are studied. Channel input distributions encompassing practical
discrete modulation schemes, such as, QAM and PSK, as well as Gaussian
signaling are covered. In addition, the impact of mismatched detection and
decoding when the receiver has insufficient information about the
non-idealities is investigated. The numerical results show that for realistic
system parameters, the effects of transmit-side noise and mismatched decoding
become significant only at high modulation orders.Comment: 16 pages, 7 figure
Capacity Results on Multiple-Input Single-Output Wireless Optical Channels
This paper derives upper and lower bounds on the capacity of the
multiple-input single-output free-space optical intensity channel with
signal-independent additive Gaussian noise subject to both an average-intensity
and a peak-intensity constraint. In the limit where the signal-to-noise ratio
(SNR) tends to infinity, the asymptotic capacity is specified, while in the
limit where the SNR tends to zero, the exact slope of the capacity is also
given.Comment: Submitted to IEEE Transactions on Information Theor
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