MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications

The UFMC modulation is among the most considered solutions for the realization of beyond-OFDM air interfaces for future wireless networks. This paper focuses on the design and analysis of an UFMC transceiver equipped with multiple antennas and operating at millimeter wave carrier frequencies. The paper provides the full mathematical model of a MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission, and for the case of multiple-packet continuous transmission. In the latter situation, the paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, the several considered detection structures and transmission schemes are compared in terms of bit-error-rate, root-mean-square-error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear MMSE data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10 - 13 $\%$. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance

Probabilistic Rateless Multiple Access for Machine-to-Machine Communication

Future machine to machine (M2M) communications need to support a massive number of devices communicating with each other with little or no human intervention. Random access techniques were originally proposed to enable M2M multiple access, but suffer from severe congestion and access delay in an M2M system with a large number of devices. In this paper, we propose a novel multiple access scheme for M2M communications based on the capacity-approaching analog fountain code to efficiently minimize the access delay and satisfy the delay requirement for each device. This is achieved by allowing M2M devices to transmit at the same time on the same channel in an optimal probabilistic manner based on their individual delay requirements. Simulation results show that the proposed scheme achieves a near optimal rate performance and at the same time guarantees the delay requirements of the devices. We further propose a simple random access strategy and characterized the required overhead. Simulation results show the proposed approach significantly outperforms the existing random access schemes currently used in long term evolution advanced (LTE-A) standard in terms of the access delay.Comment: Accepted to Publish in IEEE Transactions on Wireless Communication

Performance analysis of a polling model with BMAP and across-queue state-dependent service discipline

As various video services become popular, video streaming will dominate the mobile data traffic. The H.264 standard has been widely used for video compression. As the successor to H.264, H.265 can compress video streaming better, hence it is gradually gaining market share. However, in the short term H.264 will not be completely replaced, and will co-exist with H.265. Using H.264 and H.265 standards, three types of frames are generated, and among different types of frames exist dependencies. Since the radio resources are limited, using dependencies and quantities of frames in buffers, an appropriate time division transmission policy can be applied to transmit different types of frames sequentially, in order to avoid the occurrence of video carton or decoding failure. Polling models with batch Markovian arrival process (BMAP) and across-queue state-dependent service discipline are considered to be effective means in the design and optimization of appropriate time division transmission policies. However, the BMAP and across-queue state-dependent service discipline of the polling models lead to the large state space and several coupled state transition processes, which complicate the performance analysis. There have been very few researches in this regard. In this paper, a polling model of this type is analyzed. By constructing a supplementary embedded Markov chain and applying the matrix-analytic method based on the semi-regenerative process, the expressions of important performance measures including the joint queue length distribution, the customer blocking probability and the customer mean waiting time are obtained. The analysis will provide inspiration for analyzing the polling models with BMAP and across-queue state-dependent service discipline, to guide the design and optimization of time division transmission policies for transmitting the video compressed by H.264 and H.265

Undersampled-Based Modulation Schemes for Optical Camera Communications

Widespread use of white light-emitting diodes and ubiquitous smart devices offer the opportunity to establish VLC, which has become a hot research topic based on the growing number of publications over the last decade. Camera-based VLC, namely OCC, provides many unique features when compared to a single-photodiode-based system, such as the ability to separate incident light in the spatial and color domains. OCC technology represents a promising approach to utilize the benefits of VLC in beyond-5G scenarios and is one of the key technologies of the Internet of Things. Establishing a long communication channel in OCC, as well as non-flickering illumination by using low-frame-rate camera detectors, requires special modulation schemes. This article provides an overview of the principles of three categories of modulation schemes for OCC systems using a low-frame-rate camera detector. In addition, a series of undersampled modulation schemes are proposed and discussed to achieve flicker-free OCC with higher spectral efficiency. In addition, framing structures are designed to solve problems occurring in OCC systems using particular modulation schemes. To evaluate the performance of these modulation schemes, measured bit error rate values are shown. Finally, challenges in the implementation of OCC systems are also outlined

Study on the thermal degradation of palm olein and the effects of trace metals

Palm olein is used for the study of thermal degradation of edible oil during frying. The free fatty acids, peroxide value, total polar contents, uv/vis absorption coefficient, viscosity and percentage linoleic acid content are investigated for two sets of experiments to mimic batch and continuous frying.Master of Scienc

Using milk somatic cells to study stearoyl-CoA desaturase enzyme activity in dairy cows

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On the efficient channel state information compression and feedback for downlink MIMO-OFDM systems

This paper is concerned with the efficient compression and feedback of channel state information (CSI) in downlink multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Inspired by video coding, we propose a novel CSI compression and feedback scheme, referred to as hybrid transform coding (HTC). HTC consists of two coding types, i.e., selective time-domain coding (STDC) and differential time-domain coding (DTDC), which are adopted to exploit the correlation of CSI in both the frequency and time domains. We first develop closed-form expressions for the overhead-distortion performance of these two coding types in HTC. The parameters involved in HTC are then optimized based on the analytical results. Finally, the system-level performance of HTC is evaluated in both maximum eigenmode beamforming (MEB)-based single-user MIMO (SU-MIMO) and zero-forcing beamforming (ZFBF)-based multiuser MIMO (MU-MIMO) under Long Term Evolution Advanced (LTE-A) Release 10-based cellular networks. Simulation results show that HTC can significantly outperform the available alternative

Performance analysis of generalized block diagonal structured random matrices in compressive sensing

In compressive sensing practice, the choice of compression matrix reflects the important tradeoffs between the reconstruction performance and the implementation cost. Motivated by practical signal processing applications, this paper advocates a family of generalized block diagonal (GBD) structured random matrices for the implementation simplicity and reduced memory requirements. The restricted isometry property of such structured matrices is established to reveal the minimum number of measurements required for the perfect reconstruction of a sparse signal with high probability. The reconstruction performance of GBD random matrices is compared with that of conventional dense random matrices via both the theoretical derivation and the empirical simulations. For moderate-size sparse signals, the GBD random matrices are shown to enjoy several nice structural benefits in practical implementations, at minimal extra cost in terms of the number of required measurements. © 2012 IEEE