arXiv subjects

Taufik Abrao

Publications and source records attributed to Taufik Abrao.

31 records · Page 2Linked to original sources

arXiv2019

Total Energy Efficiency of TD- and FD-MRC Receivers for Massive MIMO Uplink

This paper proposes a detailed investigation on the uplink (UL) performance of massive multiple-input-multiple-output (maMIMO) systems employing maximum-ratio combining at the receiver. While most papers in maMIMO literature assume orthogonal frequency-division multiplexing (OFDM), current standards like LTE employ single-carrier (SC) waveform in the UL due to several benefits. We thus perform a systemic comparison between two fundamental schemes: the time-reversal MRC (TRMRC) operating under SC, and the frequency-domain MRC (FDMRC) employed with OFDM. It was recently shown that TRMRC outperforms FDMRC in terms of achievable rates, since SC systems do not require the cyclic prefix (CP) of OFDM. On the other hand, the computational complexity of TRMRC algorithm is higher than that of FDMRC, even when efficient solutions are employed (e.g., fast convolution with the overlap-and-add method). Hence, the best scheme for the UL maMIMO systems still remains an open question. The main contribution of this paper is the comparison of the total energy efficiency of both TRMRC and FDMRC when used in the UL of maMIMO systems. Our results show that, for current typical system parameters, FDMRC/OFDM achieves a higher total energy efficiency than TRMRC/SC. However, if the cell radius is below 300m and/or the computational efficiency increases by 30% regarding the current processors, the TRMRC under SC waveform becomes more attractive for the UL of maMIMO systems.

eess.SP↗

arXiv2019

Exponential Spatial Correlation with Large-Scale Fading Variations in Massive MIMO Channel Estimation

To provide the vast exploitation of the large number of antennas on massive multiple-input-multiple-output (M-MIMO), it is crucial to know as accurately as possible the channel state information in the base station. This knowledge is canonically acquired through channel estimation procedures conducted after a pilot signaling phase, which adopts the widely accepted time-division duplex scheme. However, the quality of channel estimation is very impacted either by pilot contamination or by spatial correlation of the channels. There are several models that strive to match the spatial correlation in M-MIMO channels, the exponential correlation model being one of these. To observe how the channel estimation and pilot contamination are affected by this correlated fading model, this work proposes to investigate an M-MIMO scenario applying the standard minimum mean square error channel estimation approach over uniform linear arrays and uniform planar arrays (ULAs and UPAs, respectively) of antennas. Moreover, the elements of the array are considered to contribute unequally on the communication, owing to large-scale fading variations over the array. Thus, it was perceived that the spatially correlated channels generated by this combined model offer a reduction of pilot contamination, consequently the estimation quality is improved. The UPA acquired better results regarding pilot contamination since it has been demonstrated that this type of array generates stronger levels of spatial correlation than the ULA. In contrast to the favorable results in channel estimation, the channel hardening effect was impaired by the spatially correlated channels, where the UPA imposes the worst performance of this effect for the discussed model.

eess.SP↗

arXiv2018

3-D Localization with Multiple LEDs Lamps in OFDM-VLC system

Visible light communication (VLC) based localization is a potential candidate for wide range indoor localization applications. In this paper, we propose a VLC architecture based on orthogonal frequency division multiplexing (OFDM) with multiple functionalities integrated in the same system, i.e., the 3- D receiver location, the control of the room illumination intensity, as well as the data transmission capability. Herein we propose an original methodology for LED power discrimination applying spatial optical OFDM (SO-OFDM) structure for position estimation. The hybrid locator initially makes a first estimate using a weighted angle-of-arrival (WAoA)-based locator which is then used as the starting point of the recursive estimator based on the strength of the received signal (RSS). Hence, the first stage is deployed to increase convergence probability, reducing the root-mean-square error (RMSE) and the number of iterations of the second stage. Also, a performance vs computational complexity comparative analysis is carried out with parameter variations of these estimators. The numerical results indicate a decade improvement in the RMSE for each two decades of decrement of power noise on the receiver photodiode. The best clipping factor is obtained through the analysis of locator accuracy and transmission capacity for each simulated system. Finally, the numerical results also demonstrate effectiveness, robustness, and efficiency of the proposed architecture.

eess.SP↗

arXiv2018

Hybrid Hughes-Hartogs Power Allocation Algorithms for OFDMA Systems

This work analyzes the discrete solution of Hughes-Hartogs (HH) for the transmission rate maximization problem with power constraint in the OFDMA systems and explores mechanisms to reduce the computational complexity of greedy algorithms. In addition to the solution characterization, a computational complexity analysis is developed, considering the number of executed operations for running time purpose. Moreover, we have compared the system capacity via the throughput obtained with the HH solution, and its variants combined with three complexity reduction mechanisms. These tools consist of an initial allocation bit vector calculated by rounding the results of the water-filling (WF) solution, the multiple subchannels per iteration updating, and the adoption of a subchannel grouping procedure. Our findings indicate that the update of multiple subchannels and the subcarriers grouping techniques reduce the number of iterations required for convergence of the original HH, with some throughput degradation. Also, the bit-allocation mechanism based on the WF is deployed as an alternative to overcome the HH solution, increasing the computational complexity.

eess.SP↗

arXiv2018

FBMC Prototype Filter Design via Convex Optimization

In this work, we propose a prototype filter design for Filter Bank MultiCarrier (FBMC) systems based on convex optimization, aiming superior spectrum features while maintaining a high symbol reconstruction quality. Initially, the proposed design is written as a non-convex Quadratically Constrained Quadratic Programming (QCQP), which is relaxed into a convex QCQP guided by a line search. Through the resulting problem, we design three prototype filters: Type-I, II and III. In particular, the Type-II filter shows a slightly better performance than the classical Mirabasi-Martin design, while Type-I and III filters offer a much more contained spectrum than most of the prototype filters suitable for FBMC applications. Furthermore, numerical results corroborate the effectiveness of the designed filters as the proposed filters offer fast decay and contained spectrum while not jeopardizing symbol reconstruction in practice.

eess.SP↗

arXiv2018

Sequential likelihood ascent search detector for massive MIMO systems

In this paper, we have analyzed the performance-complexity tradeoff of {a selective} likelihood ascent search (LAS) algorithm initialized by a linear detector, such as matched filtering (MF), zero forcing (ZF) and minimum mean square error (MMSE), {and considering an optimization factor $ρ$ from the bit flipping rule}. The scenario is the uplink of a massive MIMO (M-MIMO) system, and the {analysis has }been developed by means of computer simulations. With the increasing number of base station (BS) antennas, the classical detectors become inefficient. Therefore, the LAS is employed for performance-complexity tradeoff improvement. Using an adjustable optimized threshold on the bit flip rule of LAS, much better solutions have been achieved in terms of BER with no further complexity increment, indicating that there is an optimal threshold for each scenario. Considering a $32\times32$ antennas scenario, {the large-scale MIMO system equipped with the proposed LAS detector with} factor $ρ$ = 0.8 {requires} 5 dB less {in terms of SNR than the conventional LAS of the} literature ($ρ$ = 1.0) to achieve the same bit error rate of $10^{-3}$.

eess.SP↗

arXiv2018

Improved Weighted Average Consensus in Distributed Cooperative Spectrum Sensing Networks

This work proposes a fully distributed improved weighted average consensus (IWAC and WAC-AE) technique applied to cooperative spectrum sensing problem in cognitive radio systems. This method allows the secondary users cooperate based on only local information exchange without a fusion centre (FC). We have compared four rules of average consensus (AC) algorithms. The first rule is the simple AC without weights. The AC rule presents {performance comparable to the traditional cooperative spectrum sensing} (CSS) techniques, such as the equal gain combining (EGC) rule, which is a soft combining centralised method. Another technique is the weighted average consensus (WAC) rule using the weights based on the SUs channel condition. This technique results in a performance similar to the maximum ratio combining (MRC) with soft combining (centralised CSS). Two new AC rules are analysed, namely weighted average consensus accuracy exchange (WAC-AE), and improved weighted average consensus (IWAC); the former relates the weights to the channel conditions of the SUs neighbours, while the latter combines the conditions of WAC and WAC-AE in the same rule. All methods are compared each other and with the hard combining centralised CSS. The WAC-AE results in a similar performance of WAC technique but with fast convergence, while the IWAC can deliver suitable performance with small complexity increment{. Moreover, IWAC method results in a similar convergence rate than the WAC-AE method but slightly higher than the AC and WAC methods}. Hence, the computational complexity of IWAC, WAC-AE, and WAC are proven to be very similar. The analyses are based on the numerical Monte-Carlo simulations (MCS), while algorithm's convergence is evaluated for both fixed and dynamic-mobile communication scenarios, and under AWGN and Rayleigh channels.

eess.SP↗

arXiv2018

Massive MIMO Pilot Assignment Optimization based on Total Capacity

We investigate the effects of pilot assignment in multi-cell massive multiple-input multiple-output systems. When deploying a large number of antennas at base station (BS), and linear detection/precoding algorithms, the system performance in both uplink (UL) and downlink (DL) is mainly limited by pilot contamination. This interference is proper of each pilot, and thus system performance can be improved by suitably assigning the pilot sequences to the users within the cell, according to the desired metric. We show in this paper that UL and DL performances constitute conflicting metrics, in such a way that one cannot achieve the best performance in UL and DL with a single pilot assignment configuration. Thus, we propose an alternative metric, namely total capacity, aiming to simultaneously achieve a suitable performance in both links. Since the PA problem is combinatorial, and the search space grows with the number of pilots in a factorial fashion, we also propose a low complexity suboptimal algorithm that achieves promising capacity performance avoiding the exhaustive search. Besides, the combination of our proposed PA schemes with an efficient power control algorithm unveils the great potential of the proposed techniques in providing improved performance for a higher number of users. Our numerical results demonstrate that with 64 BS antennas serving 10 users, our proposed method can assure a 95%-likely rate of 4.2 Mbps for both DL and UL, and a symmetric 95%-likely rate of 1.4 Mbps when serving 32 users.

eess.SP↗

arXiv2018

Efficient ZF-WF Strategy for Sum-Rate Maximization of MU-MISO Cognitive Radio Networks

This article presents an efficient quasi-optimal sum rate (SR) maximization technique based on zero-forcing water-filling (ZFWF) algorithm directly applied to cognitive radio networks (CRNs). We have defined the non-convexity nature of the optimization problem in the context of CRNs while we have offered all necessary conditions to solve the related SR maximization problem, which considers power limit at cognitive transmitter and interference levels at primary users (PUs) and secondary users (SUs). A general expression capable to determine the optimal number of users as a function of the main system parameters, namely the signal-to-interference-plus-noise ratio (SINR) and the number of BS antennas is proposed. Our numerical results for the CRN performance are analyzed in terms of both BER and sum-capacity for the proposed ZF-WF precoding technique, and compared to the classical minimum mean square error (MMSE), corroborating the effectiveness of the proposed technique operating in multi user multiple input single output (MU-MISO) CRNs

eess.SP↗

arXiv2018

DE/PSO-aided Hybrid Linear Detectors for MIMO-OFDM Systems under Correlated Arrays

In this paper, we analyze the performance of evolutionary heuristic-aided linear detectors deployed in Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency-Division Multiplexing (OFDM) systems, considering realistic operating scenarios. Hybrid linear-heuristic detectors under different initial solutions provided by linear detectors are considered, namely differential evolution (DE) and particle swarm optimization (PSO). Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matched filter (MF) detectors. Furthermore, we discuss how the complexity of the presented algorithms scales with the number of antennas, besides of verifying the spatial correlation effects on MIMO-OFDM performance assisted by linear, heuristic and hybrid detection schemes. The influence of the initial point in the performance improvement and complexity reduction is evaluated numerically.

eess.SP↗

arXiv2018

Efficient Detectors for MIMO-OFDM Systems under Spatial Correlation Antenna Arrays

This work analyzes the performance of the implementable detectors for multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technique under specific and realistic operation system condi- tions, including antenna correlation and array configuration. Time-domain channel model has been used to evaluate the system performance under realistic communication channel and system scenarios, including different channel correlation, modulation order and antenna arrays configurations. A bunch of MIMO-OFDM detectors were analyzed for the purpose of achieve high performance combined with high capacity systems and manageable computational complexity. Numerical Monte-Carlo simulations (MCS) demonstrate the channel selectivity effect, while the impact of the number of antennas, adoption of linear against heuristic-based detection schemes, and the spatial correlation effect under linear and planar antenna arrays are analyzed in the MIMO-OFDM context.

eess.SP↗

arXiv2018

Closed-Form Directivity Expression for Arbitrary Volumetric Antenna Arrays

It is proposed a closed-form expression of directivity for an arbitrary volumetric antenna arrays using a general element pattern expression of type $\sin^u{(θ)}\cos^v{(θ)}$, with $v > -\frac{1}{2}$ and $u > -1$, and $u, v \in \mathbb{Z}$. Variations of this expression for different values of $v$ and $u$ are analyzed from the analytical and numerical perspectives. The parameters found in the closed-form expression are related to the order $v$ and $u$ of the element patterns, the rectangular spatial coordinate of each antenna element, the magnitude and phase excitation coefficients (complex excitation) of all elements, and the desired angle in spherical coordinates $(θ_0, ϕ_0)$. The expression found in this work has been validated by numerical results, considering distinct configuration scenarios.

eess.SP↗

arXiv2016

Pilot Distribution Optimization and Power Control in Multi-Cellular Large Scale MIMO Systems

Massive MIMO communication systems have been identified as one of the most prominent technologies of the next generation wireless standards, such as 5G, due to the large gains in energy and spectral efficiency that can be achieved. In the asymptotic condition of infinite number of antennas at the base station (BS), the performance bottleneck of these systems is due to the pilot contamination effect, i.e., the directional interference arising from users in adjacent cells that reuse the same set of orthogonal training sequences, and thus the interference seen by each user is determined by the pilot sequence assigned to him. We show in this paper that the system performance can be improved by appropriately assigning the pilot sequences to the users, in the so-called pilot allocation scheme. Depending on the optimization metric adopted, it is more advantageous to a user with certain long- term fading coefficient be assigned to a specific pilot sequence, whose interference can be completely estimated in advance by the BS by only knowing the long term fading coefficients of users in adjacent cells. Besides, if the objective is to maximize the number of users with a target quality of service, we have shown that the pilot allocation schemes can be combined with power control algorithms, resulting in much more improvements for the system. For unitary frequency reuse factor, we have found that the data throughput provided for 95% of the users increases when applying power control algorithm from 134kbps to 1.461Mbps with no pilot allocation, while this performance gain provided by power control changes from 793kbps to 6.743Mbps when pilot allocation is employed. If the reuse factor increases to 3, a 95%-likely data throughput of 17.310Mbps can be assured when pilot allocation and power control are suitably combined.

cs.IT↗