Search

As wireless communication evolves toward 5G, both fixed broadband and mobile broadband will play a crucial part in providing the gigabit-per-second infrastructure for a connected society. This article proposes an MGB system as the solution to two critical problems in this evolution: last-mile access for fixed broadband and small cell backhaul for mobile broadband. The key idea is to use spectrum that is already available in the millimeter-wave bands for fixed wireless access with optimized dynamic beamforming and massive MIMO infrastructure to achieve high capacity with wide area coverage. This article explains the MGB concept and describes potential array architectures for realizing the system. Simulations demonstrate that with 500 MHz of bandwidth (at 39 GHz band) and 28 dBm transmission power (55 dBm EIRP), it is possible to provide more than 11 Gb/s backhaul capacity for 96 small cells within a 1 km radius.

Almost all mobile communication systems today use spectrum in the range of 300 MHz-3 GHz. In this article, we reason why the wireless community should start looking at the 3-300 GHz spectrum for mobile broadband applications. We discuss propagation and device technology challenges associated with this band as well as its unique advantages for mobile communication. We introduce a millimeter-wave mobile broadband (MMB) system as a candidate next generation mobile communication system. We demonstrate the feasibility for MMB to achieve gigabit-per-second data rates at a distance up to 1 km in an urban mobile environment. A few key concepts in MMB network architecture such as the MMB base station grid, MMB interBS backhaul link, and a hybrid MMB + 4G system are described. We also discuss beamforming techniques and the frame structure of the MMB air interface.

Practical application of superposition coding in multiplexing broadcast and unicast for OFDM-based mobile cellular systems is discussed. Superposition coding, whose gain is increased as the superposed signals have larger difference in signal-to interference-plus-noise ratio, is well matched for unicast and broadcast in a single-frequency network configuration. Combined with interference cancellation technique, broadcast signals from multiple base stations can be cancelled in a single step, minimizing the interference from broadcast to unicast. Issues related with scheduling and strategy for time, frequency and power resource sharing between broadcast and unicast are discussed. The application of superposed broadcast and unicast is then extended to MIMO systems. Simulation results in a practical mobile cellular environment are also provided, showing significant throughput gain of superposed broadcast and unicast.

The rapid growth of Internet-based applications calls for design of a high-speed wireless packet data communication system. This anticipated increase in future mobile wireless packet data services has challenged the current 3G standardization bodies to respond with evolved 3G system specifications capable of providing increased data throughput. In response to such a need, 3GPP2 recently completed the enhanced reverse link standardization effort of the CDMA technology flagship, cdma2000/spl reg/ by completing the definition of the 1/spl times/EV-DV 1/spl times/ system. 1/spl times/EV-DV achieves higher data throughput while simultaneously providing coexisting and backward-compatible voice services within the same spectrum. This feature of 1/spl times/EV-DV allows wireless operators to manage the voice and data loading in their system more efficiently. This article describes the physical layer reverse link enhancements in cdma2000 revision D that are necessary to support 1/spl times/EV-DV.

Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression procedure. However, most CS algorithms have difficulty in data recovery due to non-sparsity characteristic of many physiological signals. Block sparse Bayesian learning (BSBL) is an effective approach to recover such signals with satisfactory recovery quality. However, it is time-consuming in recovering multichannel signals, since its computational load almost linearly increases with the number of channels. This work proposes a spatiotemporal sparse Bayesian learning algorithm to recover multichannel signals simultaneously. It not only exploits temporal correlation within each channel signal, but also exploits inter-channel correlation among different channel signals. Furthermore, its computational load is not significantly affected by the number of channels. The proposed algorithm was applied to brain computer interface (BCI) and EEG-based driver's drowsiness estimation. Results showed that the algorithm had both better recovery performance and much higher speed than BSBL. Particularly, the proposed algorithm ensured that the BCI classification and the drowsiness estimation had little degradation even when data were compressed by 80%, making it very suitable for continuous wireless telemonitoring of multichannel signals., Comment: Codes are available at: https://sites.google.com/site/researchbyzhang/stsbl

We develop a new tractable model for K-tier cellular networks, where each base station (BS) is solely powered by a self-contained energy harvesting module instead of a conventional power-line source. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deployment density. Since a BS may not always have enough energy, it may need to be kept OFF and allowed to recharge while its load is served by the neighboring BSs that are ON. Using tools from random walk theory and stochastic geometry, we characterize the fraction of time each type of BS can be kept ON, termed availability, for general uncoordinated strategies, where each BS toggles its ON/OFF state independently of the others. As a part of our analysis, we model the temporal dynamics of the energy level at each BS as a birth-death process, derive energy utilization rate for each BS class, and use hitting/stopping time analysis to study availabilities. We prove that there is a fundamental limit on the availabilities, which cannot be surpassed by any uncoordinated strategy. As a part of the proof, we construct the strategy that achieves this limit.

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered., 30 pages, 7 figures, submitted to IEEE Transactions on Wireless Communications

We develop a new tractable model for K-tier heterogeneous cellular networks (HetNets), where each base station (BS) is powered solely by a self-contained energy harvesting module. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deployment density. Since a BS may not always have enough energy, it may need to be kept OFF and allowed to recharge while nearby users are served by neighboring BSs that are ON. We show that the fraction of time a k^{th} tier BS can be kept ON, termed availability \rho_k, is a fundamental metric of interest. Using tools from random walk theory, fixed point analysis and stochastic geometry, we characterize the set of K-tuples (\rho_1, \rho_2, ... \rho_K), termed the availability region, that is achievable by general uncoordinated operational strategies, where the decision to toggle the current ON/OFF state of a BS is taken independently of the other BSs. If the availability vector corresponding to the optimal system performance, e.g., in terms of rate, lies in this availability region, there is no performance loss due to the presence of unreliable energy sources. As a part of our analysis, we model the temporal dynamics of the energy level at each BS as a birth-death process, derive the energy utilization rate, and use hitting/stopping time analysis to prove that there exists a fundamental limit on \rho_k that cannot be surpassed by any uncoordinated strategy., Comment: submitted to IEEE Transactions on Wireless Communications, July 2013

Millimeter wave (mmWave) systems must overcome heavy signal attenuation to support high-throughput wireless communication links. The small wavelength in mmWave systems enables beamforming using large antenna arrays to combat path loss with directional transmission. Beamforming with multiple data streams, known as precoding, can be used to achieve even higher performance. Both beamforming and precoding are done at baseband in traditional microwave systems. In mmWave systems, however, the high cost of mixed-signal and radio frequency chains (RF) makes operating in the passband and analog domains attractive. This hardware limitation places additional constraints on precoder design. In this paper, we consider single user beamforming and precoding in mmWave systems with large arrays. We exploit the structure of mmWave channels to formulate the precoder design problem as a sparsity constrained least squares problem. Using the principle of basis pursuit, we develop a precoding algorithm that approximates the optimal unconstrained precoder using a low dimensional basis representation that can be efficiently implemented in RF hardware. We present numerical results on the performance of the proposed algorithm and show that it allows mmWave systems to approach waterfilling capacity.