696 research outputs found
A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends
Multiple antennas have been exploited for spatial multiplexing and diversity
transmission in a wide range of communication applications. However, most of
the advances in the design of high speed wireless multiple-input multiple
output (MIMO) systems are based on information-theoretic principles that
demonstrate how to efficiently transmit signals conforming to Gaussian
distribution. Although the Gaussian signal is capacity-achieving, signals
conforming to discrete constellations are transmitted in practical
communication systems. As a result, this paper is motivated to provide a
comprehensive overview on MIMO transmission design with discrete input signals.
We first summarize the existing fundamental results for MIMO systems with
discrete input signals. Then, focusing on the basic point-to-point MIMO
systems, we examine transmission schemes based on three most important criteria
for communication systems: the mutual information driven designs, the mean
square error driven designs, and the diversity driven designs. Particularly, a
unified framework which designs low complexity transmission schemes applicable
to massive MIMO systems in upcoming 5G wireless networks is provided in the
first time. Moreover, adaptive transmission designs which switch among these
criteria based on the channel conditions to formulate the best transmission
strategy are discussed. Then, we provide a survey of the transmission designs
with discrete input signals for multiuser MIMO scenarios, including MIMO uplink
transmission, MIMO downlink transmission, MIMO interference channel, and MIMO
wiretap channel. Additionally, we discuss the transmission designs with
discrete input signals for other systems using MIMO technology. Finally,
technical challenges which remain unresolved at the time of writing are
summarized and the future trends of transmission designs with discrete input
signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE
Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A Survey, Classification and Challenges
Precoding has been conventionally considered as an effective means of
mitigating the interference and efficiently exploiting the available in the
multiantenna downlink channel, where multiple users are simultaneously served
with independent information over the same channel resources. The early works
in this area were focused on transmitting an individual information stream to
each user by constructing weighted linear combinations of symbol blocks
(codewords). However, more recent works have moved beyond this traditional view
by: i) transmitting distinct data streams to groups of users and ii) applying
precoding on a symbol-per-symbol basis. In this context, the current survey
presents a unified view and classification of precoding techniques with respect
to two main axes: i) the switching rate of the precoding weights, leading to
the classes of block- and symbol-level precoding, ii) the number of users that
each stream is addressed to, hence unicast-/multicast-/broadcast- precoding.
Furthermore, the classified techniques are compared through representative
numerical results to demonstrate their relative performance and uncover
fundamental insights. Finally, a list of open theoretical problems and
practical challenges are presented to inspire further research in this area.Comment: Submitted to IEEE Communications Surveys & Tutorial
Joint User Selection, Power Allocation, and Precoding Design with Imperfect CSIT for Multi-Cell MU-MIMO Downlink Systems
In this paper, a new optimization framework is presented for the joint design
of user selection, power allocation, and precoding in multi-cell multi-user
multiple-input multiple-output (MU-MIMO) systems when imperfect channel state
information at transmitter (CSIT) is available. By representing the joint
optimization variables in a higher-dimensional space, the weighted sum-spectral
efficiency maximization is formulated as the maximization of the product of
Rayleigh quotients. Although this is still a non-convex problem, a
computationally efficient algorithm, referred to as generalized power iteration
precoding (GPIP), is proposed. The algorithm converges to a stationary point
(local maximum) of the objective function and therefore it guarantees the
first-order optimality of the solution. By adjusting the weights in the
weighted sum-spectral efficiency, the GPIP yields a joint solution for user
selection, power allocation, and downlink precoding. The GPIP is also extended
to a multi-cell scenario, where cooperative base stations perform joint user
selection and design their precoding vectors by sharing global yet imperfect
CSIT within the cooperative BSs. System-level simulations show the gains of the
proposed approach with respect to conventional user selection and linear
downlink precoding.Comment: 35 pages, 6 figure
Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues
As a promising paradigm to reduce both capital and operating expenditures,
the cloud radio access network (C-RAN) has been shown to provide high spectral
efficiency and energy efficiency. Motivated by its significant theoretical
performance gains and potential advantages, C-RANs have been advocated by both
the industry and research community. This paper comprehensively surveys the
recent advances of C-RANs, including system architectures, key techniques, and
open issues. The system architectures with different functional splits and the
corresponding characteristics are comprehensively summarized and discussed. The
state-of-the-art key techniques in C-RANs are classified as: the fronthaul
compression, large-scale collaborative processing, and channel estimation in
the physical layer; and the radio resource allocation and optimization in the
upper layer. Additionally, given the extensiveness of the research area, open
issues and challenges are presented to spur future investigations, in which the
involvement of edge cache, big data mining, social-aware device-to-device,
cognitive radio, software defined network, and physical layer security for
C-RANs are discussed, and the progress of testbed development and trial test
are introduced as well.Comment: 27 pages, 11 figure
QoS Constrained Power Minimization in the MISO Broadcast Channel with Imperfect CSI
We consider the design of linear precoders and receivers in a Multiple-Input
Single-Output (MISO) Broadcast Channel (BC). We aim at minimizing the transmit
power while fullfiling a set of per-user Quality-of-Service (QoS) constraints
expressed in terms of per-user average rate requirements. The Channel State
Information (CSI) is assumed to be perfectly known at the receivers but only
partially at the transmitter. To solve the problem we transform the QoS
constraints into Minimum Mean Square Error (MMSE) constraints. We then leverage
the MSE duality between the BC and the Multiple Access Channel (MAC), as well
as standard interference functions in the dual MAC, to perform power
minimization by means of an Alternating Optimization (AO) algorithm. Problem
feasibility is also studied to determine whether the QoS constraints can be
fulfilled or not. Finally, we present an algorithm to balance the average rates
and manage situations that may be unfeasible or lead to an unacceptably high
transmit power
Semidefinite Relaxation-Based PAPR-Aware Precoding for Massive MIMO-OFDM Systems
Massive MIMO requires a large number of antennas and the same amount of power
amplifiers (PAs), one per antenna. As opposed to 4G base stations, which could
afford highly linear PAs, next-generation base stations will need to use
inexpensive PAs, which have a limited region of linear amplification. One of
the research challenges is effectively handling signals which have high
peak-to-average power ratios (PAPRs), such as orthogonal frequency division
multiplexing (OFDM). This paper introduces a PAPR-aware precoding scheme that
exploits the excessive spatial degrees-of-freedom of large scale multiple-input
multipleoutput (MIMO) antenna systems. This typically requires finding a
solution to a nonconvex optimization problem. Instead of relaxing the problem
to minimize the peak power, we introduce a practical semidefinite relaxation
(SDR) framework that enables accurately and efficiently approximating the
theoretical PAPR-aware precoding performance for OFDM-based massive MIMO
systems. The framework allows incorporating channel uncertainties and intercell
coordination. Numerical results show that several orders of magnitude
improvements can be achieved w.r.t. state of the art techniques, such as
instantaneous power consumption reduction and multiuser interference
cancellation. The proposed PAPRaware precoding can be effectively handled along
with the multicell signal processing by the centralized baseband processing
platforms of next-generation radio access networks. Performance can be traded
for the computing efficiency for other platform
Learning-Based Adaptive Transmission for Limited Feedback Multiuser MIMO-OFDM
Performing link adaptation in a multiantenna and multiuser system is
challenging because of the coupling between precoding, user selection, spatial
mode selection and use of limited feedback about the channel. The problem is
exacerbated by the difficulty of selecting the proper modulation and coding
scheme when using orthogonal frequency division multiplexing (OFDM). This paper
presents a data-driven approach to link adaptation for multiuser multiple input
mulitple output (MIMO) OFDM systems. A machine learning classifier is used to
select the modulation and coding scheme, taking as input the SNR values in the
different subcarriers and spatial streams. A new approximation is developed to
estimate the unknown interuser interference due to the use of limited feedback.
This approximation allows to obtain SNR information at the transmitter with a
minimum communication overhead. A greedy algorithm is used to perform spatial
mode and user selection with affordable complexity, without resorting to an
exhaustive search. The proposed adaptation is studied in the context of the
IEEE 802.11ac standard, and is shown to schedule users and adjust the
transmission parameters to the channel conditions as well as to the rate of the
feedback channel
Generalized Multicast Multibeam Precoding for Satellite Communications
This paper deals with the problem of precoding in multibeam satellite
systems. In contrast to general multiuser multiple-input-multiple-output (MIMO)
cellular schemes, multibeam satellite architectures suffer from different
challenges. First, satellite communications standards embed more than one user
in each frame in order to increase the channel coding gain. This leads to the
different so-called multigroup multicast model, whose optimization requires
computationally complex operations. Second, when the data traffic is generated
by several Earth stations (gateways), the precoding matrix must be
distributively computed and attain additional payload restrictions. Third,
since the feedback channel is adverse (large delay and quantization errors),
the precoding must be able to deal with such uncertainties. In order to solve
the aforementioned problems, we propose a two-stage precoding design in order
to both limit the multibeam interference and to enhance the intra-beam minimum
user signal power (i.e. the one that dictates the rate allocation per beam). A
robust version of the proposed precoder based on a first perturbation model is
presented. This mechanism behaves well when the channel state information is
corrupted. Furthermore, we propose a per beam user grouping mechanism together
with its robust version in order to increase the precoding gain. Finally, a
method for dealing with the multiple gateway architecture is presented, which
offers high throughputs with a low inter-gateway communication. The conceived
designs are evaluated in a close-to-real beam pattern and the latest broadband
communication standard for satellite communications
Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks
With years of tremendous traffic and energy consumption growth, green radio
has been valued not only for theoretical research interests but also for the
operational expenditure reduction and the sustainable development of wireless
communications. Fundamental green tradeoffs, served as an important framework
for analysis, include four basic relationships: spectrum efficiency (SE) versus
energy efficiency (EE), deployment efficiency (DE) versus energy efficiency
(EE), delay (DL) versus power (PW), and bandwidth (BW) versus power (PW). In
this paper, we first provide a comprehensive overview on the extensive on-going
research efforts and categorize them based on the fundamental green tradeoffs.
We will then focus on research progresses of 4G and 5G communications, such as
orthogonal frequency division multiplexing (OFDM) and non-orthogonal
aggregation (NOA), multiple input multiple output (MIMO), and heterogeneous
networks (HetNets). We will also discuss potential challenges and impacts of
fundamental green tradeoffs, to shed some light on the energy efficient
research and design for future wireless networks.Comment: revised from IEEE Communications Surveys & Tutorial
NOMA Schemes for Multibeam Satellite Communications
Non-orthogonal multiple access (NOMA) schemes are being considered in 5G new
radio developments and beyond. Although seminal papers demonstrated that NOMA
outperforms orthogonal access in terms of capacity and user fairness, the
majority of works have been devoted to the wireless terrestrial arena.
Therefore, it is worth to study how NOMA can be implemented in other types of
communications, as for instance the satellite ones, which are also part of the
5G infrastructure. Although communications through a satellite present a
different architecture than those in the wireless terrestrial links, NOMA can
be an important asset to improve their performance. This article introduces a
general overview of how NOMA can be applied to this different architecture. A
novel taxonomy is presented based on different multibeam transmission schemes
and guidelines that open new avenues for research in this topic are provided
- …