547 research outputs found
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser downlink systems which
aims at creating constructive interference among the transmitted data streams.
This can be enabled by designing the precoded signal of the multiantenna
transmitter on a symbol level, taking into account both channel state
information and data symbols. Previous literature has studied this paradigm for
MPSK modulations by addressing various performance metrics, such as power
minimization and maximization of the minimum rate. In this paper, we extend
this to generic multi-level modulations i.e. MQAM and APSK by establishing
connection to PHY layer multicasting with phase constraints. Furthermore, we
address adaptive modulation schemes which are crucial in enabling the
throughput scaling of symbol-level precoded systems. In this direction, we
design signal processing algorithms for minimizing the required power under
per-user SINR or goodput constraints. Extensive numerical results show that the
proposed algorithm provides considerable power and energy efficiency gains,
while adapting the employed modulation scheme to match the requested data rate
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser multiple-antenna downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for Mary phase shift keying (MPSK) modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. Mary quadrature amplitude modulation (MQAM) by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user signal to interference noise ratio (SINR) or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate
Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel
This paper investigates the problem of interference among the simultaneous
multiuser transmissions in the downlink of multiple antennas systems. Using
symbol level precoding, a new approach towards the multiuser interference is
discussed along this paper. The concept of exploiting the interference between
the spatial multiuser transmissions by jointly utilizing the data information
(DI) and channel state information (CSI), in order to design symbol-level
precoders, is proposed. In this direction, the interference among the data
streams is transformed under certain conditions to useful signal that can
improve the signal to interference noise ratio (SINR) of the downlink
transmissions. We propose a maximum ratio transmission (MRT) based algorithm
that jointly exploits DI and CSI to glean the benefits from constructive
multiuser interference. Subsequently, a relation between the constructive
interference downlink transmission and physical layer multicasting is
established. In this context, novel constructive interference precoding
techniques that tackle the transmit power minimization (min power) with
individual SINR constraints at each user's receivers is proposed. Furthermore,
fairness through maximizing the weighted minimum SINR (max min SINR) of the
users is addressed by finding the link between the min power and max min SINR
problems. Moreover, heuristic precoding techniques are proposed to tackle the
weighted sum rate problem. Finally, extensive numerical results show that the
proposed schemes outperform other state of the art techniques.Comment: Submitted to IEEE Transactions on Signal Processin
Energy-Efficient Symbol-Level Precoding in Multiuser MISO Based on Relaxed Detection Region
This paper addresses the problem of exploiting interference among
simultaneous multiuser transmissions in the downlink of multiple-antenna
systems. Using symbol-level precoding, a new approach towards addressing the
multiuser interference is discussed through jointly utilizing the channel state
information (CSI) and data information (DI). The interference among the data
streams is transformed under certain conditions to a useful signal that can
improve the signal-to-interference noise ratio (SINR) of the downlink
transmissions and as a result the system's energy efficiency. In this context,
new constructive interference precoding techniques that tackle the transmit
power minimization (min power) with individual SINR constraints at each user's
receiver have been proposed. In this paper, we generalize the CI precoding
design under the assumption that the received MPSK symbol can reside in a
relaxed region in order to be correctly detected. Moreover, a weighted
maximization of the minimum SNR among all users is studied taking into account
the relaxed detection region. Symbol error rate analysis (SER) for the proposed
precoding is discussed to characterize the tradeoff between transmit power
reduction and SER increase due to the relaxation. Based on this tradeoff, the
energy efficiency performance of the proposed technique is analyzed. Finally,
extensive numerical results show that the proposed schemes outperform other
state-of-the-art techniques.Comment: Submitted to IEEE transactions on Wireless Communications. arXiv
admin note: substantial text overlap with arXiv:1408.470
A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
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