Wiener-based smoother and predictor for massive-MIMO downlink system under pilot contamination

One of the challenges in massive-MIMO system is pilot contamination during the channel estimation process. Pilot contamination can cause error or inaccurate channel estimation process for future fifth generation (5G) downlink transmissions. This paper considers using a Wiener-based filter to smooth and predict the channel estimation to reduce the pilot contamination for more accurate CSI during channel estimation. The simulation results show that the Wiener-based smoothing and predicting technique reduces the effect of pilot contamination and increases the accuracy of CSI during channel estimation process. Wiener smoother (WS) is implemented based on Wiener-based filtering technique. The previous estimated CSI and weight coefficient vector are used to smooth the current estimated CSI by using block data formulation to reduce the effect of pilot contamination. However, WS technique suffers from pilot contamination due to pilot training. This motivates the development of two Wiener predictors (WP), known as WP1 and WP2. The WP1 and WP2 run a prediction technique for CSI and number of pilot training during the prediction period, which is missing from the original WS. Comparison results show that the proposed WS and WP outperforms the conventional minimum mean square error and least square, in terms of channel estimation error and per-cell rate. WP2 perform better than WS and WP1 because of the algorithm complexity that required more information to be updated, stored and processed for prediction. Thus, WP2 requires large computation and matrix operation compared to WS and WP1. The results indicate that the channel estimation error due to pilot contamination can be reduced by using the Wiener-based approaches.     

Learning Automata-Based Algorithms for Solving the Target Coverage Problem in Directional Sensor Networks

Recently, directional sensor networks have received a great deal of attention due to their wide range of applications in different fields. A unique characteristic of directional sensors is their limitation in both sensing angle and battery power, which highlights the significance of covering all the targets and, at the same time, extending the network lifetime. It is known as the target coverage problem that has been proved as an NP-complete problem. In this paper, we propose four learning automata-based algorithms to solve this problem. Additionally, several pruning rules are designed to improve the performance of these algorithms. To evaluate the performance of the proposed algorithms, several experiments were carried out. The theoretical maximum was used as a baseline to which the results of all the proposed algorithms are compared. The obtained results showed that the proposed algorithms could solve efficiently the target coverage problem.     

A new technique for multi-cell joint channel estimation in time division code division multiple access based on reduced rank singular value decomposition

A new technique for multi-cell joint channel estimation (MCJCE) in time division code division multiple access based on singular value decomposition (SVD) reduced rank technique is proposed in this paper. MCJCE is one of the effective solutions to improve the mobile system performance throughout mitigate the inter-cell interference form the neighboring cells. The increasing complexity of multi-cell system model due to the additional processing of the interferer users will be solved by using SVD reduced rank technique, where a limited number of parameter that really need it to describe the channel matrix will be estimated. Two models of multi-cell approaches are discussed, the first one depended on reconstruct the convolutional midamble matrix of inactive users in serving cell by the strongest interferer users from the neighboring cells. The second one will be more inclusive to user traffic scenarios in mobile systems and will be expanding to contain all detected users. The simulation results prove the validity of the proposed reduced rank technique for precision channel estimation (6.4 and 5 dB) and (9 and 7 dB) for case 1 and 2 respectively; BER performance improvements over the conventional estimators.     

Novel Tight Closed-Form Bounds for the Symbol Error Rate of EGC and MRC Diversity Receivers Employing Linear Modulations Over \alpha -\mu Fading

In this paper, we propose novel lower and upper bounds on the average symbol error rate (SER) of the dual-branch maximal-ratio combining and equal-gain combining diversity receivers assuming independent branches. \(M\) -ary pulse amplitude modulation and \(M\) -ary phase shift keying schemes are employed and operation over the \(\alpha -\mu \) fading channel is assumed. The proposed bounds are given in closed form and are very simple to calculate as they are composed of a double finite summation of basic functions that are readily available in the commercial software packages. Furthermore, the proposed bounds are valid for any combination of the parameters \(\alpha \) and \(\mu \) as well as \(M\) . Numerical results presented show that the proposed bounds are very tight when compared to the exact SER obtained via performing the exact integrations numerically making them an attractive much simpler alternative for SER evaluation studies.     

A CMOS RF front-end for a multistandard WLAN receiver

This letter describes the design and performance of a dual band tri-mode receiver front-end compliant with the IEEE 802.11a, b, and g standards. The receiver front-end was built in a 0.18-/spl mu/m CMOS process and achieves a noise figure of 4.7 dB/5.1 dB for the 2.4-GHz/5-GHz bands, respectively. The receiver front-end provides a dual gain mode of 5 dB/30 dB with an IIP3 of -1dBm for the low gain mode. The front-end draws 25 mA/27 mA from a 1.8-V supply for the 2.4-GHz/5-GHz bands, respectively.     

A behavioral-based multi-agent optimization algorithm for system level radio design

This paper introduces a multi-agent behavioral-based optimization algorithm for system level radio design. Making multi-standard wireless communication receivers that meet their specs while keeping the requirements of the individual blocks as relaxed as possible is the goal of this algorithm. In order to achieve this goal a “divide and conquer” approach is proposed. Different agents focus on different objectives that are pursued in parallel. Agents adopt different behaviors depending on the status of the environment and their interaction with other agents. Agents are cooperative by default as they try to meet their spec without making changes that affect other agents. However, more aggressive behaviors that lead to global changes can be adopted when needed. The interaction between these simple entities yields an emergent behavior able to deal smoothly with the complexity of the problem at hand.     

Understanding and Predicting Data Hotspots in Cellular Networks

The unprecedented growth in mobile data usage is posing significant challenges to cellular operators. One key challenge is how to provide quality of service to subscribers when their residing cell is experiencing a significant amount of traffic, i.e. becoming a traffic hotspot. In this paper, we perform an empirical study on data hotspots in today’s cellular networks using a 9-week cellular dataset with 734K+ users and 5327 cell sites. Our analysis examines in details static and dynamic characteristics, predictability, and causes of data hotspots, and their correlation with call hotspots. We show that using standard machine learning methods, future hotspots can be accurately predicted from past observations. We believe the understanding of these key issues will lead to more efficient and responsive resource management and thus better QoS provision in cellular networks. To the best of our knowledge, our work is the first to empirically characterize traffic hotspots in today’s cellular networks.     

A High-Quality Rectifier Based on Sheppard–Taylor Converter Operating in Discontinuous Capacitor Voltage Mode

This paper presents a single-phase soft-switched high power factor (PF) Sheppard-Taylor rectifier suitable for applications requiring low-voltage and high-current output. The proposed rectifier is designed to operate at discontinuous capacitor voltage mode. The Sheppard-Taylor converter in this mode of operation provides zero-voltage turnoff switching, as well as natural input PF correction over a wide range of input voltage, which makes the converter suitable for universal input applications. Due to its simplified control circuitry and reduced switch current stress, this converter presents better efficiency and higher reliability. In addition, the presented converter features continuous input-output currents, which result in low electromagnetic interference emission. Principle of operation, theoretical analysis, and experimental results from a laboratory prototype rated at 45 W/10 Vdc output voltage are presented. The measured efficiency and total harmonic distortion of the input line current were 85% and 3.2%, respectively. The input current harmonics meet the EN61000-3-2 Class D requirements.     

Integrated high-quality rectifier-regulators

A new family of AC-DC converters is derived which integrate the functions of low-harmonic rectification, low-frequency energy storage, and wide-bandwidth output voltage control into a single converter containing one, two, or four active switches. These converters utilize a discontinuous conduction mode input inductor, an internal energy storage capacitor, and transformer secondary circuits which resemble the bridge, forward, flyback, or Cuk DC-DC converters. A large-signal equivalent circuit model for this family is presented, which uses the “loss-free resistor” concept. Design strategies and experimental results are given. High-performance regulation with satisfactory line-current harmonics is demonstrated with conventional duty-ratio control. Further improvements in line current are possible by simultaneous duty-ratio and switching-frequency control