Maha Alodeh

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-antenna systems. Using symbol-level precoding, a new approach to exploit the multiuser interference is discussed. The concept of exploiting the interference between spatial multiuser transmissions by jointly utilizing data information (DI) and channel state information (CSI), in order to design symbol-level precoders, is proposed. To this end, 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. 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 users 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.

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 toward 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 systems energy efficiency. In this context, new constructive interference precoding techniques that tackle the transmit power minimization (min power) with individual SINR constraints at each users receiver have been proposed. In this paper, we generalize the constructive interference (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.

Constructive Interference through Symbol Level Precoding for Multi-Level Modulation

The constructive interference concept in the downlink of multiple-antenna systems is addressed in this paper. The concept of the joint exploitation of the channel state information (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 the previous work, different constructive interference precoding techniques have been proposed for the MPSK scenario. In this context, a novel constructive interference precoding technique that tackles the transmit power minimization (min-power) with individual SINR constraints at each users receivers is proposed assuming MQAM modulation. Extensive simulations are performed to validate the proposed technique.

A Multicast Approach for Constructive Interference Precoding in MISO Downlink Channel

This paper studies the concept of jointly utilizing the data information (DI) and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO) downlink channel. In this direction, the interference among the simultaneous data streams is transformed to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmissions (MRT) based algorithm that jointly exploits DI and CSI to gain the benefits from these useful signals. In this context, a novel framework to minimize the power consumption is proposed by formalizing the duality between the constructive interference downlink channel and the multicast channels. The numerical results have shown that the proposed schemes outperform other state of the art techniques.

Per-Antenna Power Minimization in Symbol-Level Precoding

This paper investigates the problem of the interference among multiple simultaneous transmissions in the downlink channel of a multi- antenna wireless system. A symbol-level precoding scheme is considered, where the data information is used, along with the channel state information, in order to exploit the multi-user interference and transform it into useful power at the receiver side. In this framework, it is important to consider the power limitations individually for each transmitting antenna, since a common practice in multi-antenna systems is the use of separate per-antenna amplifiers. Thus, herein the problem of per-antenna power minimization in symbol-level precoding is formulated and solved, under Quality-of-Service constraints. 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. Numerical results are presented to show the effectiveness of the proposed scheme, which outperforms the existing state of the art techniques in terms of reduction of the power peaks and of the peak-to-average power ratio across the transmitting antennas.

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

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.

Data aware user selection in cognitive downlink MISO precoding systems

This paper tackles the problem of data aware user selection in cognitive downlink MISO precoding. The new scheme is based on utilizing the data and channel information to select the cognitive users that minimize the transmit power at the cognitive base station (CBS). The role of data exploitation in user selection is discussed by classifying the interference into two types: destructive and constructive. Selecting a set of users whose simultaneous transmissions interact constructively from interference perspective is proposed in this paper. Therefore, the interference can be viewed as an additional source of desired energy that should be exploited. Optimal solutions for this problem can be prohibitively complex for online implementation at the base station. A novel suboptimal user selection scheme based on the joint utilization of channel and data information is proposed. To evaluate the performance of the proposed technique, intensive computer simulations are performed to compare it with conventional techniques.

Energy efficient symbol-level precoding in multiuser MISO channels

This paper investigates the idea of exploiting interference among the simultaneous multiuser transmissions in the downlink of multiple antennas 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). 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. In this context, new constructive interference precoding techniques that tackle the transmit power minimization (min power) with individual SINR constraints at each users receivers are proposed. Furthermore, we investigate the CI precoding design under the assumption that the received MPSK symbol can reside in a relaxed region in order to be correctly detected. Finally, extensive numerical results show that the proposed schemes outperform other state of the art techniques.

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

Symbol-level precoding is a new paradigm for multiuser multiple-antenna downlink systems aimed at creating constructive interference among 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 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 by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address the adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design the signal processing algorithms for minimizing the required power under per-user signal to interference noise ratio 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 Based Precoding in the Downlink of Cognitive MISO Channel

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 cognitive users as an additional source of useful energy that should be exploited. 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 conventional techniques.