Joint beamforming and channel estimation for pilot-aided WCDMA systems

The problem of joint beamforming and channel estimation for multi-rate multi-code systems is addressed. Usual schemes perform this filtering/estimation operation making use of a training sequence time-multiplexed with the transmitted data. However if pilot and traffic signals are transmitted simultaneously using distinct code allocation-as it is the case in recent standards such as cdma2000 or WCDMA-these schemes tend to fail. This paper proposes semi-blind techniques to overcome the uplink auto-interfering effects of such systems. It is shown that the semi-blind approach yields substantially better performance results thanks to the implicit modeling of the unknown traffic data.Peer ReviewedPostprint (published version

Pilot-aided ML schemes for joint beamforming and channel estimation in WCDMA systems

This paper proposes semi-blind channel estimation and interference cancellation schemes for the reception of pilot-aided signals in WCDMA systems. It is shown that the performance of classical training-based schemes is severely degraded due to the code-multiplexing (as opposed to time-multiplexing) of traffic and pilot signals. The time-dispersivity of the channel destroys the orthogonality between the traffic signal and the pilot, and consequently the traffic signal appears as a new interfering signal for the channel estimation/beamforming algorithm. In order to avoid this effect, we propose techniques that exploit both the presence of the training sequence and the structure of the traffic signal in a semi-blind fashion.Peer ReviewedPostprint (published version

Adaptive Beamforming and Adaptive Modulation-Assisted Network Performance of Multiuser Detection-Aided FDD and TDD CDMA Systems

The network performance of a frequency division duplex and time division duplex (TDD) code division multiple access (CDMA)-based system is investigated using system parameters similar to those of the Universal Mobile Telecommunication System. The new call blocking and call dropping probabilities, the probability of low-quality access, and the required average transmit power are quantified both with and without adaptive antenna arrays (AAAs), as well as when subjected to shadow fading. In some of the scenarios investigated, the system’s user capacity is doubled with the advent of adaptive antennas. The employment of adaptive modulation techniques in conjunction with AAAs resulted in further significant network capacity gains. This is particularly so in the context of TDD CDMA, where the system’s capacity becomes poor without adaptive antennas and adaptive modulation owing to the high base station (BS) to BS interference inflicted as a consequence of potentially using all time slots in both the uplink and downlink of the emerging wireless Internet. Index Terms—Adaptive beamforming, adaptive modulation, code division multiple access (CDMA) systems, Universal Mobile Telecommunication System Terrestrial Radio Access (UTRA), wireless network performance

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique for the reception of pilot-aided multirate multicode direct-sequence code division multiple access (DS/CDMA) systems such as wideband CDMA (WCDMA). These systems introduce a code-multiplexed pilot sequence that can be used for the estimation of the filter weights, but the presence of the traffic signal (transmitted at the same time as the pilot sequence) corrupts that estimation and degrades the performance of the filter significantly. This is caused by the fact that although the traffic and pilot signals are usually designed to be orthogonal, the frequency selectivity of the channel degrades this orthogonality at hte receiving end. Here, we propose a semi-blind technique that eliminates the self-noise caused by the code-multiplexing of the pilot. We derive analytically the asymptotic performance of both the training-only and the semi-blind techniques and compare them with the actual simulated performance. It is shown, both analytically and via simulation, that high gains can be achieved with respect to training-onlybased techniques.Peer Reviewe

A Semiblind Two-Way Training Method for Discriminatory Channel Estimation in MIMO Systems

Discriminatory channel estimation (DCE) is a recently developed strategy to enlarge the performance difference between a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. Specifically, it makes use of properly designed training signals to degrade channel estimation at the UR which in turn limits the UR's eavesdropping capability during data transmission. In this paper, we propose a new two-way training scheme for DCE through exploiting a whitening-rotation (WR) based semiblind method. To characterize the performance of DCE, a closed-form expression of the normalized mean squared error (NMSE) of the channel estimation is derived for both the LR and the UR. Furthermore, the developed analytical results on NMSE are utilized to perform optimal power allocation between the training signal and artificial noise (AN). The advantages of our proposed DCE scheme are two folds: 1) compared to the existing DCE scheme based on the linear minimum mean square error (LMMSE) channel estimator, the proposed scheme adopts a semiblind approach and achieves better DCE performance; 2) the proposed scheme is robust against active eavesdropping with the pilot contamination attack, whereas the existing scheme fails under such an attack.Comment: accepted for publication in IEEE Transactions on Communication

Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas

The main focus and contribution of this paper is a novel network-MIMO TDD architecture that achieves spectral efficiencies comparable with "Massive MIMO", with one order of magnitude fewer antennas per active user per cell. The proposed architecture is based on a family of network-MIMO schemes defined by small clusters of cooperating base stations, zero-forcing multiuser MIMO precoding with suitable inter-cluster interference constraints, uplink pilot signals reuse across cells, and frequency reuse. The key idea consists of partitioning the users population into geographically determined "bins", such that all users in the same bin are statistically equivalent, and use the optimal network-MIMO architecture in the family for each bin. A scheduler takes care of serving the different bins on the time-frequency slots, in order to maximize a desired network utility function that captures some desired notion of fairness. This results in a mixed-mode network-MIMO architecture, where different schemes, each of which is optimized for the served user bin, are multiplexed in time-frequency. In order to carry out the performance analysis and the optimization of the proposed architecture in a clean and computationally efficient way, we consider the large-system regime where the number of users, the number of antennas, and the channel coherence block length go to infinity with fixed ratios. The performance predicted by the large-system asymptotic analysis matches very well the finite-dimensional simulations. Overall, the system spectral efficiency obtained by the proposed architecture is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the number of antennas at the base stations (roughly, from 500 to 50 antennas).Comment: Full version with appendice (proofs of theorems). A shortened version without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B was revised after submissio

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems