528 research outputs found
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
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
Antenna selection and performance analysis of MIMO spatial multiplexing systems
Multiple-input multiple-output spatial multiplexing (MIMO-SM) systems offer an essential benefit referred to as spatial multiplexing gain. Two important signal reception techniques for MIMO-SM systems are the zero-forcing (ZF) and ordered successive interference cancellation (OSIC) as, for example, in the case of the decision-feedback detector (DFD). This thesis studies the communication and signal processing aspects of MIMO-SM. We first investigate the bit error rate (BER) performance of the ZF receiver over transmit correlated Ricean flat-fading channels. In particular, for a MIMO channel with M transmit and N receive antennas, we derive an approximation for the average BER of each sub-stream. A closed-form expression for the optimal transmit correlation coefficient, which achieves the maximum capacity (i.e., uncorrelated case) of two-input two-output spatial multiplexing (TITO-SM) systems, is presented. We further propose an antenna selection (AS) approach for the DFD over independent Rayleigh flat-fading channels. The selected transmit antennas are those that maximize both the post-processing signal-to-noise ratio (SNR) at the receiver end, and the system capacity. An upper bound on the outage probability for the AS approach is derived. It is shown that the AS approach achieves a performance comparable to optimal capacity-based selection based on exhaustive search, but at a lower complexity. Finally, we investigate a cross-layer transmit AS approach for the DFD over spatially correlated Ricean flat-fading channels. The selected transmit antennas are those that maximize the link layer throughput of correlated MIMO channels. A closed-form expression for the system throughput with perfect channel estimation is first derived. We further analyze the system performance with pilot-aided channel estimation. In that, we derive a closed-form expression for the post-detection signal-to-noise-plus-interference ratio (SNIR) of each transmitted substream, conditioned on the estimated channels. The derived SNIR is then used to evaluate the overall system throughput. It is observed that the cross-layer AS approach always assigns the transmission to the antenna combination which sees better channel conditions, resulting in a substantial improvement over the optimal capacity-based AS approach. Considering a training-based channel estimation technique, we compare the performance of the proposed cross-layer AS with that of optimal capacity-based AS when employed with a training-based channel estimation. Our results show that the latter is more robust to imperfect channel estimation. However, in all cases, the cross-layer AS delivers higher throughput gains than the capacity-based A
MIMO Systems
In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity
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