Multi-user Multiple-input And Multiple-output Research Articles

A Desired PAR-Achieving Precoder Design for Multiuser MIMO OFDM Based on Concentration of Measure

For multi-user multiple-input and multiple-output (MIMO) wireless communications in orthogonal frequency di- vision multiplexing systems, we propose a MIMO precoding scheme providing a desired peak-to-average power ratio (PAR) at the minimum cost that is defined as received SNR degradation. By taking advantage of the concentration of measure, we formulate a convex problem with constraint on the desired PAR. Consequently, the proposed scheme almost exactly achieves the desired PAR on average, and asymptotically attains the desired PAR at the 0.001 point of its complementary cumulative distribution function, as the number of subcarriers increases.

Sencar Based Load Balanced Clustering With Mobile Data Gathering In Wireless Sensor Networks

The wireless sensor networks consist of static sensors, which can be deployed in a wide environment for monitoring applications. While transmitting the data from source to static sink, the amount of energy consumption of the sensor node is high. This results in reduced lifetime of the network. Some of the WSN architectures have been proposed based on Mobile Elements such as three-layer framework is for mobile data collection, which includes the sensor layer, cluster head layer, and mobile collector layer (called SenCar layer). This framework employs distributed load balanced clustering and dual data uploading, it is referred to as LBC-DDU.In the sensor layer a distributed load balanced clustering algorithm is used for sensors to self-organize themselves into clusters. The cluster head layer use inter-cluster transmission range it is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-saving in the inter-cluster communications. Through this transmissions cluster head information is send to the SenCar for its moving trajectory planning.This is done by utilizing multi-user multiple-input and multiple-output (MU-MIMO) technique. Then the results show each cluster has at most two cluster heads. LBC-DDU achieves higher energy saving per node and energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sinks.

Multiuser MIMO User Selection Based on L 2-Hausdorff Distance with Block Diagonalization

Block diagonalization (BD) is an important precoding method for multiuser multiple-input and multiple-output (MU-MIMO) broadcast channel (BC) systems. When the number of users is large, user selection (scheduling) should be performed so as to make full use of BD precoding. In this paper, based on $$L_{2}$$L2-Hausdorff distance, we propose two novel user selection algorithms, namely GUS-$$\hbox {D}_{{L_{2}}}$$DL2 and US-$$\hbox {S}_{{L_{2}}}$$SL2, for MU-MIMO BC systems with BD precoding to maximize the throughput. Both of the proposed algorithms select users iteratively and perform power allocation using the waterfilling method. In GUS-$$\hbox {D}_{{L_{2}}}$$DL2, $$L_{2}$$L2-Hausdorff distance is used as a crucial factor for the user selection criterion. In US-$$\hbox {S}_{{L_{2}}}$$SL2, besides the criterion in GUS-$$\hbox {D}_{{L_{2}}}$$DL2, a similarity criterion based on $$L_{2}$$L2-hausdorff distance is employed to reduce the cardinality of the candidate user set effectively. The complexities of the proposed algorithms are analyzed and compared with those of typical existing algorithms. Simulations have been carried out to verify the performance of the proposed algorithms. Numerical results suggest that the proposed algorithms outperform most of their rivals in terms of complexity and show competitive performance in throughput.

Green MU-MIMO/SIMO Switching for Heterogeneous Delay-Aware Services With Constellation Optimization

In this paper, we propose adaptive techniques for multiuser multiple-input and multiple-output (MU-MIMO) cellular communication systems, to solve the problem of energy efficient communications with heterogeneous delay-aware traffic. In order to minimize the total transmission power of the MU-MIMO, we investigate the relationship between the transmission power and the M-ary quadrature amplitude modulation (MQAM) constellation size and get the energy efficient modulation for each transmission stream based on the minimum mean square error (MMSE) receiver. Since the total power consumption is different for MU-MIMO and multiuser single input and multiple output (MU-SIMO), by exploiting the intrinsic relationship among the total power consumption model, and heterogeneous delay-aware services, we propose an adaptive transmission strategy, which is a switching between MU-MIMO and MU-SIMO. Simulations show that in order to maximize the energy efficiency and consider different Quality of Service (QoS) of delay for the users simultaneously, the users should adaptively choose the constellation size for each stream as well as the transmission mode.

Efficient Beamforming by SLNR Maximization for Dual-Hop Relay Assisted MIMO Network

Relay beamforming is a key signal processing technique to mitigate interference in single and multiuser multiple input and multiple output (MIMO) wireless communication networks. In MIMO relay netw...

Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading in Wireless Sensor Networks

In this paper, a three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called SenCar) layer. The framework employs distributed load balanced clustering and dual data uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long network lifetime and low data collection latency. At the sensor layer, a distributed load balanced clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In contrast to existing clustering methods, our scheme generates multiple cluster heads in each cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the inter-cluster transmission range is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-saving inter-cluster communications. Through inter-cluster transmissions, cluster head information is forwarded to SenCar for its moving trajectory planning. At the mobile collector layer, SenCar is equipped with two antennas, which enables two cluster heads to simultaneously upload data to SenCar in each time by utilizing multi-user multiple-input and multiple-output (MU-MIMO) technique. The trajectory planning for SenCar is optimized to fully utilize dual data uploading capability by properly selecting polling points in each cluster. By visiting each selected polling point, SenCar can efficiently gather data from cluster heads and transport the data to the static data sink. Extensive simulations are conducted to evaluate the effectiveness of the proposed LBC-DDU scheme. The results show that when each cluster has at most two cluster heads, LBC-DDU achieves over 50 percent energy saving per node and 60 percent energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sink, and 20 percent shorter data collection time compared to traditional mobile data gathering.

Three-dimensional fading channel models: A survey of elevation angle research

The explosive increase of mobile traffic demands higher spectrum efficiency for future wireless communications. By properly configuring a 2-dimensional (2D) antenna array at the basestation, the system capacity can be improved with 3 dimensional (3D) multiuser Multiple Input and Multiple Output (MIMO) techniques without modifying the terminal antennas. Therefore, the signal will propagate in a 3D space with angle dispersion in both horizontal and vertical planes. Due to its role in facilitating research and development of 3D MIMO technology, the 3D fading channel model is receiving increasing attention. However, existing fading channel models mostly focus on the azimuth angle characteristics, while neglecting the elevation angle impact. This article provides a state of the art review on 3D fading channel models, emphasizing research related to the elevation angle. We also report some recent field measurements for 3D MIMO and investigate the comprehensive propagation characteristics of the elevation angle.

A Study State Analysis of Mu Mimo Using Adaptive Algorithm

In conventional cellular systems, each base station (BS) transmits signals intended for a single user in a particular resource allocation. As bandwidth is a scarce resource, effective utilization of the available bandwidth in the system is essential in modern wireless systems especially for applications such as video streaming and voice over internet protocol (VoIP) which demands high data rate. Fortunately since the user's feedback the channel state information to the network, there is an opportunity for the BS to schedule more than one user's data in a single resource allocation by designing pre-coders which beam form the data to the intended user. This technique which is called multi-user multiple-input and multiple-output (MU-MIMO) is adopted to investigate an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme. We develop a analogous fast iterative truncation algorithm (FITRA) and display statistical results to exhibit tremendous PAR-reduction capabilities. The significantly condensed linearity necessities ultimately empower the routine of low-cost RF components for the large-scale MU-MIMO-OFDM downlink. We show that there is a strong preference for obtaining high-quality feedback, and that obtaining near-perfect channel information from as many receivers as possible provides a significantly larger sum rate than collecting a few feedback bits from a large number of users.

Energy Efficient Pilot and Link Adaptation for Mobile Users in TDD Multi-User MIMO Systems

In this paper, we develop an uplink pilot and downlink link adaptation approach to improve the energy efficiency (EE) of mobile users in time division duplexing (TDD) multi-user multiple input and multiple output (MU-MIMO) systems. Assuming reciprocity between uplink and downlink channels, the downlink transmission is based on uplink channel estimation. While more uplink pilot power ensures more accurate channel estimation and better downlink performance, it incurs higher energy consumption of mobile users. This paper reveals the relationship and tradeoff among pilot power, channel estimation, and downlink link adaptation that achieves the highest energy efficiency for mobile users. We show that the energy efficiency of different users can be decoupled because the downlink average throughput of each user is independent of the pilot powers of other users and energy-efficient design can be done on a per-user basis. Based on the analysis, we propose an uplink pilot and downlink link adaptation algorithm to improve the EE of mobile users. Simulation results are finally provided to demonstrate the significant gain in energy efficiency for mobile users.

Average Mutual Information Analysis of Multiple Input and Multiple Output System with Multihop Relaying in Wireless Communication System

Problem statement: Multiple Input and Multiple Output (MIMO) system with Multihop relaying techhnique is significant and active areas of wireless communication. In a rich scattering environment MIMO antenna system provides better channel capacity and data rates than single antenna systems. To provide high throughput, reliable transmission and broad coverage, wireless relaying techniques are essential in a variety of applications. In a cellular environment a relay can be used to overcome shadowing effect due to obstacles and multihop relaying can improve the throughput for mobiles suffering from poor signal to interference, noise ratio at the edge of a cell and reduce cell size to increase spectral efficiency. Approach: This study analyzes average mutual information of the Ricean channel for single hop Multiple Input Multiple Output (MIMO) system for different antenna configuation and dependence of capacity on the Rice factor for cellular system. The asymptotic capacity of multiuser two-hop MIMO system with Regularization Block Diagonalization (RBD) precoding techniques for Indepenent Identically Distributed (IID) channal and realistic Mobile to Mobile fading channel model was examined. In this realistic model, Non-Line-Sight (NLOS) propagation conditions are assumed from source mobile station to mobile relay and also from mobile relay to destination station. A non regenerative Amplify and Forward (AF) relay is used to optimize the capacity between the source and destination and also the evaluation was made for multiuser multi-hop relay system with correlated fading channel model using RBD precoding matrix. Results: The simulation results for average mutual information of single hop MIMO relay system for different antenna configuration with ricean channel model, ergodic sum mutual information for two hop relay system with RBD precoding technique and mutual information results for multiuser multihop relay system with correlated channel model was presented. Conclusion/Recommendations: Cellular systems generally operated at a fairly low SINR which can be increased on each hop by adding relays. Multiuser two hop relay system with RBD precoding for realistic mobile to mobile fading channel model is simulated and compared with IID channel model. Multiuser Multi-hop relay with optimal precoding and RBD precoding technique results were analyzed for correlated fading channel and found that capacity offered by RBD precoding scheme is better than other relaying systems.

A Probabilistic Approach for Robust Leakage-Based MU-MIMO Downlink Beamforming with Imperfect Channel State Information

Multi-user multiple-input and multiple-output (MU-MIMO) wireless systems have the potential to increase system capacity significantly by separating multiple users in the space domain through appropriate signal processing. These techniques require accurate channel state information at transmitter (CSIT) for their proper operations. With inevitable channel imperfections in practice, robustness has become an important issue in the development of beamforming techniques. In this work, we propose a robust leakage-based transmit beamforming design for multi-user MIMO systems by introducing a probabilistic constraint. In a multi-user system, the main challenge for transmit beamforming is to suppress the co-channel interference (CCI) from other users. Our approach optimizes the average signal-to-interference-plus-noise ratio (SINR) performance implicitly by maximizing the average signal power subject to probabilistic leakage and noise power constraint. Moreover, both the single-stream-per-user and multiple-stream-per-user cases are considered.In the latter case, a hybrid scheme is suggested by incorporating Alamouti code into the proposed design. Simulation results show that under proper control of the probabilistic constraint, both beamformers achieve good bit-error-rate (BER) performances, reliability of SINR levels as well as robustness against channel uncertainties.

Cross-Layer Antenna Selection and Channel Allocation for MIMO Cognitive Radios

We propose algorithms to address the spectrum efficiency and fairness issues of multi band multiuser Multiple-Input and Multiple-Output (MIMO) cognitive ad-hoc networks. To improve the transmission efficiency of the MIMO system, a cross layer antenna selection algorithm is proposed. Using the transmission efficiency results, user data rate of the cognitive ad-hoc network is determined. Objective function for the average data rate of the multi band multiuser cognitive MIMO ad-hoc network is also defined. For the average data rate objective function, primary users interference is considered as performance constraint. Furthermore, using the user data rate results, a learning-based channel allocation algorithm is proposed. Finally, numerical results are presented for performance evaluation of the proposed antenna selection and channel allocation algorithms.

A Novel Spatially Correlated Multiuser MIMO Channel Modeling: Impact of Surface Roughness

A novel approach for modeling multiuser multiple-input and multiple-output (MIMO) channels is proposed. Here, the scatterers are modeled as random rough surfaces: Any point on rough surfaces scatters the incident wave into any given direction with certain probability. This leads to correlation across different spatially distributed users. The paper derives closed form expressions for the intra-user (point-to-point) and inter-user (multiuser) correlation of pair-wise channel coefficients. It is observed that the distance of users relative to the scatterer surfaces as well as the degree of roughness impact the correlation region. The technique is applied to both non-line-of-sight (NLOS) and line-of-sight (LOS) scenarios. It is observed that LOS signals drastically boost the correlation of the channel coefficients.

MU-MIMO Pairing Algorithm Using Received Power

In this letter, a new received power pairing scheduling (PPS) algorithm is proposed for Multi User Multiple Input and Multiple Output (MU-MIMO) systems. In contrast to existing algorithms that manage complex orthogonal factors, the PPS algorithm simply utilizes CINR to determine a MU-MIMO pair. Simulation results show that the PPS algorithm achieves up to 77% of MU-MIMO gain of determinant pairing scheduling (DPS) with low complexity.

Zero-Forcing Beamforming Multiuser-MIMO Systems with Finite Rate Feedback for Multiple Stream Transmission per User

We describe a channel-vector quantization scheme that is suitable for multiple stream transmission per user in zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple output (MU-MIMO) systems with finite rate feedback. Multiple subsets of a channel matrix are quantized to vectors from random vector codebooks for finite rate feedback. The quantization vectors with an angle difference that is closer to orthogonal are then selected and their indexes are fed back to the transmitter. Simulation results demonstrate that the proposed scheme achieves a better average throughput than that serving a single stream per user when the number of active users is smaller than the number of transmit antennas and that it provides an average throughput close to that serving a single stream per user when the number of users is equal to the number of transmit antennas.

Rate Control for Zero-Forcing Beamforming Multiuser MIMO Systems with QR-Decomposition MLD Receiver

A rate control scheme is described for zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple-output (MU-MIMO) systems with a QR-decomposition maximum likelihood detector (MLD) at the receiver. For selected users, a modulation-and-coding set is selected for each substream by estimating the per-substream post-MLD signal-to-interference-plus-noise ratio. Iterative modified QR-decomposition MLD is employed at the receiver to achieve the throughput expected from the transmitter. The simulation results demonstrated that the proposed rate-control scheme achieved the target packet error rate while increasing the throughout for ZFBF-MU-MIMO systems as the number of user candidates increases.