User Selection for symbol-level multigroup multicasting precoding in the downlink of MISO channels

in 2018 IEEE International Conference on Communications (ICC) (2018)

We consider the problem of user selection for symbol-level multigroup multicasting in the downlink of multiuser MISO systems. Symbol-level precoding is a new paradigm for multiuser multiple-antenna ... [more ▼]

We consider the problem of user selection for symbol-level multigroup multicasting in the downlink of multiuser MISO systems. Symbol-level precoding is a new paradigm for multiuser multiple-antenna downlink systems which aims at creating constructive interference among the simultaneous 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. This work proposes a user selection algorithm to facilitate serving multiple groups of users, by transmitting a stream of common symbols to each group on symbol-by-symbol basis if we have large number of users. We provide numerical results to validate the proposed algorithm. [less ▲]

Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels

in The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (2017, March)

Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

in IEEE Transactions on Wireless Communications (2017)

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 ... [more ▼]

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. [less ▲]

Peak Power Minimization in Symbol-level Precoding for Cognitive MISO Downlink Channels

in IEEE Digital Signal Processing Conference (2016, October 16)

This paper proposes a new symbol-level precoding scheme at the cognitive transmitter that jointly utilizes the data and channel information to reduce the effect of nonlinear amplifiers, by reducing the ... [more ▼]

This paper proposes a new symbol-level precoding scheme at the cognitive transmitter that jointly utilizes the data and channel information to reduce the effect of nonlinear amplifiers, by reducing the maximum antenna power under quality of service constraint at the cognitive receivers. In practice, each transmit antenna has a separate amplifier with individual characteristics. In the proposed approach, the precoding design is optimized in order to control the instantaneous power transmitted by the antennas, and more specifically to limit the power peaks, while guaranteeing some specific target signal-to-noise ratios at the receivers and respecting the interference temperature constraint imposed by the primary system. Numerical results show the effectiveness of the proposed scheme, which outperforms the existing state of the art techniques in terms of reduction of the power peaks. [less ▲]

Energy-Efficient Symbol-Level Precoding in Multiuser MISO Based on Relaxed Detection Region

in IEEE Transactions on Wireless Communications (2016)

Interference in Multiple-antenna Communications: From Channel Estimation to Exploitation

Doctoral thesis (2015)

Multi-antenna technologies have emerged as attractive techniques of providing efficient and reliable communications in future wireless communications. The potential gain of multiple antennas in the ... [more ▼]

Multi-antenna technologies have emerged as attractive techniques of providing efficient and reliable communications in future wireless communications. The potential gain of multiple antennas in the downlink of wireless systems is well-known: if the spatial dimension is exploited to deliver simultaneous data streams to multiple users, the total data throughput increases linearly with the number of transmit antennas. However, interference in multiple-antenna communications presents a challenging factor that should be dealt with wisely in cellular systems. This thesis is concerned with tackling the interference at two different steps in the communications process: channel estimation, and downlink data transmissions. The interference at estimation process can occur in reciprocity based channel state information (CSI) acquisition if the utilized pilots are reused in the network. On the other hand, the interference at downlink occurs when the base station serves multiple users simultaneously over the same spectrum. This first part of the thesis focuses on the channel estimation in multiple antenna multicell interference-limited networks. The channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in de-signing accurate precoders that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and Least Squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination and enhance the quality of estimation. The second part of the thesis focuses on the precoding techniques in the downlink of a single cell. The constructive interference concept in the downlink of multiple-antenna systems is addressed in this paper. The concept of the joint exploitation of CSI and data information (DI) is discussed. Using symbol-level precoding, the interference between data streams is transformed under certain conditions into useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. In this thesis, not only different constructive interference precoding techniques are proposed for different types of modulation, but also a transmitter architecture that can accommodate them. These schemes optimize the performance of the symbol-level precoding with respect to different objectives such as: minimizing the transmit power under per user quality of service constraint, maximizing the fairness among different users under total power constraint. Extensive simulations are performed to validate our proposed techniques and show that they outperform the conventional precoding schemes. [less ▲]

Symbol Based Precoding in the Downlink of Cognitive MISO Channel

in Proceedings of CROWNCOM 2015 (2015, April)

This paper proposes symbol level precoding in the downlink of a MISO cognitive system. The new scheme tries to jointly utilize the data and channel information to design a precoding that minimizes the ... [more ▼]

This paper proposes symbol level precoding in the downlink of a MISO cognitive system. The new scheme tries to jointly utilize the data and channel information to design a precoding that minimizes the transmit power at a cognitive base station (CBS); without violating the interference temperature constraint imposed by the primary system. In this framework, the data information is handled at symbol level which enables the characterization the intra-user interference among the cog- nitive users as an additional source of useful energy that should be ex- ploited. A relation between the constructive multiuser transmissions and physical-layer multicast system is established. Extensive simulations are performed to validate the proposed technique and compare it with con- ventional techniques [less ▲]

Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels

in IEEE Transactions on Signal Processing (2015)

This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks ... [more ▼]

This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and Least Squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas. [less ▲]

Spatial DCT-Based Least Square Estimation in Multi-antenna Multi-cell Interference Channels

in IEEE International Conference on Communications(ICC) (2014, June)

Enhanced Service Delivery for Cognitive Systems within Multiple Antenna Scenarios

in IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (2013, December)