References of "IEEE Transactions on Signal Processing"
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See detailEnergy efficiency optimization in MIMO interference channels: A successive pseudoconvex approximation approach
Yang, Yang UL; Pesavento, Marius; Chatzinotas, Symeon UL et al

in IEEE Transactions on Signal Processing (2019)

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See detailSymbol-Level Precoding Design Based on Distance Preserving Constructive Interference Regions
Haqiqatnejad, Alireza UL; Kayhan, Farbod UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2018), 66(22), 5817-5832

In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We consider generic two-dimensional constellations ... [more ▼]

In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We consider generic two-dimensional constellations with any shape and size, and confine ourselves to one of the main categories of constructive interference regions (CIR), namely, distance preserving CIR (DPCIR). We provide a comprehensive study of DPCIRs and derive several properties for these regions. Using these properties, we first show that any signal in a given DPCIR has a norm greater than or equal to the norm of the corresponding constellation point if and only if the convex hull of the constellation contains the origin. It is followed by proving that the power of the noise-free received signal in a DPCIR is a monotonic strictly increasing function of two parameters relating to the infinite Voronoi edges. Using the convex description of DPCIRs and their characteristics, we formulate two design problems, namely, the SLP power minimization with signal-to-interference-plus-noise ratio (SINR) constraints, and the SLP SINR balancing problem under max-min fairness criterion. The SLP power minimization based on DPCIRs can straightforwardly be written as a quadratic programming (QP). We derive a simplified reformulation of this problem which is less computationally complex. The SLP max-min SINR, however, is non-convex in its original form, and hence difficult to tackle. We propose alternative optimization approaches, including semidefinite programming (SDP) formulation and block coordinate descent (BCD) optimization. We discuss and evaluate the loss due to the proposed alternative methods through extensive simulation results. [less ▲]

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See detailSymbol-Level Precoding for the Nonlinear Multiuser MISO Downlink Channel
Spano, Danilo UL; Alodeh, Maha; Chatzinotas, Symeon UL et al

in IEEE Transactions on Signal Processing (2018), 66(5), 1331-1345

This paper investigates the problem of the interference among multiple simultaneous transmissions in the downlink channel of a multiantenna wireless system. A symbol-level precoding scheme is considered ... [more ▼]

This paper investigates the problem of the interference among multiple simultaneous transmissions in the downlink channel of a multiantenna wireless system. A symbol-level precoding scheme is considered, in order to exploit the multiuser interference and transform it into useful power at the receiver side, through a joint utilization of the data information and the channel state information. In this context, this paper presents novel strategies that exploit the potential of symbol-level precoding to control the per-antenna instantaneous transmit power. In particular, the power peaks among the transmitting antennas and the instantaneous power imbalances across the different transmitted streams are minimized. These objectives are particularly relevant with respect to the nonlinear amplitude and phase distortions induced by the per-antenna amplifiers, which are important sources of performance degradation in practical systems. More specifically, this paper proposes two different symbol-level precoding approaches. The first approach performs a weighted per-antenna power minimization, under quality-of-service constraints and under a lower bound constraint on the per-antenna transmit power. The second strategy performs a minimization of the spatial peak-to-average power ratio, evaluated among the transmitting antennas. Numerical results are presented in a comparative fashion to show the effectiveness of the proposed techniques, which outperform the state-of-the-art symbol-level precoding schemes in terms of spatial peak-to-average power ratio, spatial dynamic range, and symbol error rate over nonlinear channels. [less ▲]

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See detailEnergy-Efficient Multicell Multigroup Multicasting With Joint Beamforming and Antenna Selection
Tervo, Oskari; Tran, Le-Nam; Pennanen, Harri et al

in IEEE Transactions on Signal Processing (2018)

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See detailSymbol-level Precoding for the Non-linear Multiuser MISO Downlink Channel
Spano, Danilo UL; Alodeh, Maha; Chatzinotas, Symeon UL et al

in IEEE Transactions on Signal Processing (2017)

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 ... [more ▼]

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, in order to exploit the multi-user interference and transform it into useful power at the receiver side, through a joint utilization of the data information and the channel state information. In this context, this paper presents novel strategies which exploit the potential of symbol-level precoding to control the per-antenna instantaneous transmit power. In particular, the power peaks amongst the transmitting antennas and the instantaneous power imbalances across the different transmitted streams are minimized. These objectives are particularly relevant with respect to the non-linear amplitude and phase distortions induced by the per-antenna amplifiers, which are important sources of performance degradation in practical systems. More specifically, this work proposes two different symbol-level precoding approaches. A first approach performs a weighted per-antenna power minimization, under Quality-of-Service constraints and under a lower bound constraint on the per-antenna transmit power. A second strategy performs a minimization of the spatial peak-to-average power ratio, evaluated amongst the transmitting antennas. Numerical results are presented in a comparative fashion to show the effectiveness of the proposed techniques, which outperform the state of the art symbol-level precoding schemes in terms of spatial peak-to-average power ratio, spatial dynamic range, and symbol-error-rate over non-linear channels. [less ▲]

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See detailA unified successive pseudoconvex approximation framework
Yang, Yang UL; Pesavento, Marius

in IEEE Transactions on Signal Processing (2017), 65(13), 3313-3328

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See detailDistributed Optimization for Coordinated Multi-cell Multigroup Multicast Beamforming: Power Minimization and SINR Balancing
Tervo; Pennanen; Christopoulos et al

in IEEE Transactions on Signal Processing (2017)

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See detailCodebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems
He, S.; Wang, J.; Huang, Y. et al

in IEEE Transactions on Signal Processing (2017), 65(20), 5289-5304

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See detailAdaptive Cloud Radio Access Networks: Compression and Optimization
Vu, Thang Xuan UL; Nguyen, Hieu Duy; Quek, Tony Q.S. et al

in IEEE Transactions on Signal Processing (2017), 65(1), 228-241

Future mobile networks are facing with exponential data growth due to the proliferation of diverse mobile equipment and data-hungry applications. Among promising technology candidates to overcome this ... [more ▼]

Future mobile networks are facing with exponential data growth due to the proliferation of diverse mobile equipment and data-hungry applications. Among promising technology candidates to overcome this problem, cloud radio access network (CRAN) has received much attention. In this work, we investigate the design of fronthaul in C-RAN uplink by focusing on the compression and optimization in fronthaul uplinks based on the statistics of wireless fading channels. First, we derive the system block error rate (BLER) under Rayleigh fading channels. In particular, upper and lower bounds of the BLER union bound are obtained in closed-form. From these bounds, we gain insight in terms of diversity order and limits of the BLER. Next, we propose adaptive compression schemes to minimize the fronthaul transmission rate subject to a BLER constraint. Furthermore, a fronthaul rate allocation is proposed to minimize the system BLER. It is shown that the uniform rate allocation approaches the optimal scheme as the total fronthauls’ bandwidth increases. Lastly, numerical results are presented to demonstrate the effectiveness of our proposed optimizations. [less ▲]

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See detailPer-antenna constant envelope precoding and antenna subset selection: A geometric approach
Zhang, J.; Huang, Y.; Wang, J. et al

in IEEE Transactions on Signal Processing (2016), 64(23), 6089-6104

Constant envelope (CE) precoding can efficiently control the peak-to-average power ratio (PAPR) and improve the power efficiency of power amplifiers in large-scale antenna array systems. Antenna subset ... [more ▼]

Constant envelope (CE) precoding can efficiently control the peak-to-average power ratio (PAPR) and improve the power efficiency of power amplifiers in large-scale antenna array systems. Antenna subset selection (ASS), combined with CE precoding, can further improve power efficiency by using a part of antennas to combine the desired signal. However, due to the inherent nonlinearity, the joint optimization of CE precoding and ASS is very challenging and satisfactory solutions are yet not available. In this paper, we present new methods for CE precoding and ASS optimization from a geometric perspective. First, we show the equivalence between the CE precoder design and a polygon construction problem in the complex plane, thus transforming the algebraic problem into a geometric problem. Aiming to minimize the computational complexity, we further transform the CE precoder design into a triangle construction problem, and propose a novel algorithm to achieve the optimal CE precoder with only linear complexity in the number of used antennas. Then, we investigate the joint optimization of ASS and CE precoding to minimize the total transmit power while satisfying the QoS requirement. Based on the geometric interpretation, we develop an efficient ASS algorithm, which, using only addition and comparison operations, is guaranteed to find the globally optimal solution and provides robustness to channel uncertainty. The complexity of the proposed ASS algorithm is at most quadratic in the number of antennas in the worst case. The optimality and superiority of the proposed geometric methods are demonstrated via numerical results. [less ▲]

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See detailA parallel decomposition method for nonconvex stochastic multi-agent optimization problems
Yang, Yang UL; Scutari, Gesualdo; Palomar, Daniel et al

in IEEE Transactions on Signal Processing (2016), 64(11), 2949-2964

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See detailSpatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels
Alodeh, Maha UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

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 ▲]

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See detailConstructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel
Alodeh, Maha UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2015)

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 ... [more ▼]

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 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. [less ▲]

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See detailData Predistortion for Multicarrier Satellite Channels Based on Direct Learning
Piazza, Roberto UL; Shankar, Bhavani UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2014), 62(22),

Satellite communication is facing the urgent need of improving data rate and efficiency to compete with the quality of service offered by terrestrial communication systems. An imminent gain, achievable ... [more ▼]

Satellite communication is facing the urgent need of improving data rate and efficiency to compete with the quality of service offered by terrestrial communication systems. An imminent gain, achievable without the need of upgrading current satellite technology, can be obtained by exploiting multicarrier operation at the transponder and using highly efficient modulation schemes. However, on-board multicarrier joint amplification of high order modulation schemes is a critical operation as it brings severe non-linear distortion effects. These distortions increase as the on-board High Power Amplifier (HPA) is operated to yield higher power efficiencies. In this work, we propose novel techniques to implement on ground predistortion that enable multicarrier transmission of highly efficient modulation schemes over satellite channels without impacting infrastructure on the downlink. [less ▲]

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See detailStatistical Framework for Optimization in the Multi-User MIMO Uplink With ZF-DFE
Järmyr, Simon; Ottersten, Björn UL; Jorswieck, Eduard A.

in IEEE Transactions on Signal Processing (2014), 62(10), 2730-2745

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially ... [more ▼]

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially precoded and conveyed over a fading narrowband multiple-input multiple-output (MIMO) channel. All users' data streams are decoded successively at the receiving base station using zero-forcing decision feedback equalization (ZF-DFE). We target the joint optimization of a decoding order and linear precoders for all users based on long-term channel information. For a class of general MIMO channel models, including the separable-correlation and double-scattering models, we show that the choice of precoder for a certain user does not affect the performance of the others. This leads to a particularly straightforward characterization of general user utility regions as a polyblock, or a convex polytope if time-sharing is allowed. We formulate the decoding-ordering problem under transmit-correlated Rayleigh fading as a linear assignment problem, enabling the use of existing efficient algorithms. Combining decoding ordering with single-user precoder optimization by means of alternating optimization, we propose an efficient iterative scheme that is verified numerically to converge fast and perform close to optimally, successfully reaping the benefits of both precoding and ordering in the MIMO uplink. [less ▲]

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See detailCoordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency
He, Shiwen; Huang, Yongming; Yang, Luxi et al

in IEEE Transactions on Signal Processing (2014), 62(3), 741-751

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser ... [more ▼]

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency. [less ▲]

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See detailCompressive Sparsity Order Estimation for Wideband Cognitive Radio Receiver
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2014)

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity ... [more ▼]

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity pattern. However, the sparsity order of the channel occupancy is time-varying and the sampling rate of the CS receiver needs to be adjusted based on its value in order to fully exploit the potential of CS-based techniques. In this context, investigating blind Sparsity Order Estimation (SOE) techniques is an open research issue. To address this, we study an eigenvalue-based compressive SOE technique using asymptotic Random Matrix Theory. We carry out detailed theoretical analysis for the signal plus noise case to derive the asymptotic eigenvalue probability distribution function (aepdf) of the measured signal’s covariance matrix for sparse signals. Subsequently, based on the derived aepdf expressions, we propose a technique to estimate the sparsity order of the wideband spectrum with compressive measurements using the maximum eigenvalue of the measured signal’s covariance matrix. The performance of the proposed technique is evaluated in terms of normalized SOE Error (SOEE). It is shown that the sparsity order of the wideband spectrum can be reliably estimated using the proposed technique for a variety of scenarios. [less ▲]

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See detailMulti-portfolio optimization: A potential game approach
Yang, Yang UL; Rubio, Francisco; Scutari, Gesualdo et al

in IEEE Transactions on Signal Processing (2013)

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See detailImproving Physical Layer Secrecy Using Full-Duplex Jamming Receivers
Zheng, Gan UL; Krikidis, Ioannis; Jiangyuan, Li et al

in IEEE Transactions on Signal Processing (2013), 20(61), 4962-4974

This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy ... [more ▼]

This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy performance as the system is interference-limited. In the literature, assuming that the receiver operates in half duplex (HD) mode, the aforementioned problem has been addressed via use of cooperating nodes who act as jammers to confound the eavesdropper. This paper investigates an alternative solution, which assumes the availability of a full duplex (FD) receiver. In particular, while receiving data, the receiver transmits jamming noise to degrade the eavesdropper channel. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. For the case in which global channel state information is available, we aim to design the optimal jamming covariance matrix that maximizes the secrecy rate and mitigates loop interference associated with the FD operation. We consider both fixed and optimal linear receiver design at the destination, and show that the optimal jamming covariance matrix is rank-1, and can be found via an efficient 1-D search. For the case in which only statistical information on the eavesdropper channel is available, the optimal power allocation is studied in terms of ergodic and outage secrecy rates. Simulation results verify the analysis and demonstrate substantial performance gain over conventional HD operation at the destination. [less ▲]

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See detailTransceiver design for distributed STBC based AF cooperative networks in the presence of timing and frequency offsets
Nasir, A.A.; Mehrpouyan, H.; Durrani, S. et al

in IEEE Transactions on Signal Processing (2013), 12(61), 3143-3158

In multi-relay cooperative systems, the signal at the destination is affected by impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs ... [more ▼]

In multi-relay cooperative systems, the signal at the destination is affected by impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs). In this paper we account for all these impairments and propose a new transceiver structure at the relays and a novel receiver design at the destination in distributed space-time block code (DSTBC) based amplify-and-forward (AF) cooperative networks. The Cramér-Rao lower bounds and a least squares (LS) estimator for the multi-parameter estimation problem are derived. In order to significantly reduce the receiver complexity at the destination, a differential evolution (DE) based estimation algorithm is applied and the initialization and constraints for the convergence of the proposed DE algorithm are investigated. In order to detect the signal from multiple relays in the presence of unknown channels, MTOs, and MCFOs, novel optimal and sub-optimal minimum mean-square error receiver designs at the destination node are proposed. Simulation results show that the proposed estimation and compensation methods achieve full diversity gain in the presence of channel and synchronization impairments in multi-relay AF cooperative networks. [less ▲]

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