3,060 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
A universal space-time architecture for multiple-antenna aided systems
In this tutorial, we first review the family of conventional multiple-antenna techniques, and then we provide a general overview of the recent concept of the powerful Multiple-Input Multiple-Output (MIMO) family based on a universal Space-Time Shift Keying (STSK) philosophy. When appropriately configured, the proposed STSK scheme has the potential of outperforming conventional MIMO arrangements
Fundamental Limits in MIMO Broadcast Channels
This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system paramaters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling
Pulse Shaping Diversity to Enhance Throughput in Ultra-Dense Small Cell Networks
Spatial multiplexing (SM) gains in multiple input multiple output (MIMO)
cellular networks are limited when used in combination with ultra-dense small
cell networks. This limitation is due to large spatial correlation among
channel pairs. More specifically, it is due to i) line-of-sight (LOS)
communication between user equipment (UE) and base station (BS) and ii)
in-sufficient spacing between antenna elements. We propose to shape transmit
signals at adjacent antennas with distinct interpolating filters which
introduces pulse shaping diversity eventually leading to improved SINR and
throughput at the UEs. In this technique, each antenna transmits its own data
stream with a relative offset with respect to adjacent antenna. The delay which
must be a fraction of symbol period is interpolated with the pulse shaped
signal and generates a virtual MIMO channel that leads to improved diversity
and SINR at the receiver. Note that non-integral sampling periods with
inter-symbol interference (ISI) should be mitigated at the receiver. For this,
we propose to use a fractionally spaced equalizer (FSE) designed based on the
minimum mean squared error (MMSE) criterion. Simulation results show that for a
2x2 MIMO and with inter-site-distance (ISD) of 50 m, the median received SINR
and throughput at the UE improves by a factor of 11 dB and 2x, respectively,
which verifies that pulse shaping can overcome poor SM gains in ultra-dense
small cell networks.Comment: Accepted to 17th IEEE International Workshop on Signal Processing
Advances in Wireless Communication
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
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