In mobile millimeter wave (mmWave) systems, energy is a scarce resource due to the large losses in the channel and high energy usage by analog-to-digital converters (ADC), which scales with bandwidth. In this paper, we consider a communication architecture that integrates the sub-6 GHz and mmWave technologies in 5G cellular systems. In order to mitigate the energy scarcity in mmWave systems, we investigate the rate-optimal and energy-efficient physical layer resource allocation jointly across the sub-6 GHz and mmWave interfaces. First, we formulate an optimization problem in which the objective is to maximize the achievable sum rate under power constraints at the transmitter and receiver. Our formulation explicitly takes into account the energy consumption in integrated-circuit components, and assigns the optimal power and bandwidth across the interfaces. We consider the settings with no channel state information and partial channel state information at the transmitter and under high and low SNR scenarios. Second, we investigate the energy efficiency (EE) defined as the ratio between the amount of data transmitted and the corresponding incurred cost in terms of power. We use fractional programming and Dinkelbach's algorithm to solve the EE optimization problem. Our results prove that despite the availability of huge bandwidths at the mmWave interface, it may be optimal (in terms of achievable sum rate and energy efficiency) to utilize it partially. Moreover, depending on the sub-6 GHz and mmWave channel conditions and total power budget, it may be optimal to activate only one of the interfaces.
Beyond the classical mmWave communications and beamforming methods @cite_8 @cite_16 @cite_25 @cite_29 , recently, there have been proposals on leveraging out-of-band information in order to enhance the mmWave performance. The authors in @cite_9 propose a transform method to translate the spatial correlation matrix at the sub-6 GHz band into the correlation matrix of the mmWave channel. The authors in @cite_26 consider the @math GHz indoor WiFi network, and investigate the correlation between the estimated angle-of-arrival (AoA) at the sub-6 GHz band with the mmWave AoA in order to reduce the beam-steering overhead. The authors in @cite_24 propose a compressed beam selection method which is based on out-of-band spatial information obtained at sub-6 GHz band. Our work is distinguished from the above cited works as we investigate the optimal physical layer resource allocation across the sub-6 GHz and mmWave interfaces. In our proposed hybrid sub-6 GHz mmWave architecture, both interfaces can be simultaneously used for data transfer. In @cite_19 , we investigated the problem of optimal load devision and scheduling across the sub-6 GHz and mmWave interfaces.
@cite_26 @cite_8 @cite_9 @cite_29 @cite_24 @cite_19 @cite_16 @cite_25
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We propose a hybrid architecture that integrates RF (i.e., sub-6 GHz) and millimeter wave (mmWave) technologies for 5G cellular systems. In particular, communications in the mmWave band faces significant challenges due to variable channels, intermittent connectivity, and high energy usage. On the other hand, speeds for electronic processing of data is of the same order as typical rates for mmWave interfaces which makes the use of complex algorithms for tracking channel variations and adjusting resources accordingly impractical. Our proposed architecture integrates the RF and mmWave interfaces for beamforming and data transfer, and exploits the spatio-temporal correlations between the interfaces. Based on extensive experimentation in indoor and outdoor settings, we demonstrate that an integrated RF mmWave signaling and channel estimation scheme can remedy the problem of high energy usage and delay associated with mmWave beamforming. In addition, cooperation between two interfaces at the higher layers effectively addresses the high delays caused by highly intermittent mmWave connectivity. We design a scheduler that fully exploits the mmWave bandwidth, while the RF link acts as a fallback mechanism to prevent high delay. To this end, we formulate an optimal scheduling problem over the RF and mmWave interfaces where the goal is to maximize the delay-constrained throughput of the mmWave interface. We prove using subadditivity analysis that the optimal scheduling policy is based on a single threshold that can be easily adopted despite high link variations. Millimeter wave (mmWave) communication is one feasible solution for high data-rate applications like vehicular-to-everything communication and next generation cellular communication. Configuring mmWave links, which can be done through channel estimation or beam-selection, however, is a source of significant overhead. In this paper, we propose to use spatial information extracted at sub-6 GHz to help establish the mmWave link. First, we review the prior work on frequency dependent channel behavior and outline a simulation strategy to generate multi-band frequency dependent channels. Second, assuming: (i) narrowband channels and a fully digital architecture at sub-6 GHz; and (ii) wideband frequency selective channels, OFDM signaling, and an analog architecture at mmWave, we outline strategies to incorporate sub-6 GHz spatial information in mmWave compressed beam selection. We formulate compressed beam-selection as a weighted sparse signal recovery problem, and obtain the weighting information from sub-6 GHz channels. In addition, we outline a structured precoder combiner design to tailor the training to out-of-band information. We also extend the proposed out-of-band aided compressed beam-selection approach to leverage information from all active OFDM subcarriers. The simulation results for achievable rate show that out-of-band aided beam-selection can reduce the training overhead of in-band only beam-selection by 4x. Deploying sub-6-GHz network together with millimeter wave (mm-wave) is a promising solution to simultaneously achieve sufficient coverage and high data rate. In heterogeneous networks, the traditional coupled access, i.e., users are constrained to be associated with the same base station in both downlink and uplink, is no longer optimal, and the concept of downlink and uplink decoupling (DUDe) has recently been proposed. In this paper, we analyze the coverage probability and area throughput for both the downlink and uplink of sub-6-GHz mm-wave cellular networks with decoupled access. Compared with the existing works, we take uplink power control and mm-wave interference into account. Using the tools from stochastic geometry, the expressions of signal-to-interference-plus-noise ratio coverage probability, user-perceived rate coverage probability and the area throughput are derived. The impact of decoupled access and different small cells (SCells) is investigated. In particular, analytical results reveal that with decoupled access, UEs are more likely to be associated with SCells in uplink when the network is sparse, and the uplink traffic will be offloaded from sub-6-GHz SCells to mm-wave SCells when the network is dense. Moreover, the dense deployment of mm-wave SCells rather than sub-6-GHz SCells is more reasonable, and the DUDe is a key factor in improving the performance of dense cellular networks with multi-band. Millimeter-wave (mm-wave) frequency bands provide an opportunity for much wider channel bandwidth compared with the traditional sub-6-GHz band. Communication at mm-waves is, however, quite challenging due to the severe propagation pathloss incurred by conventional isotropic antennas. To cope with this problem, directional beamforming both at the base station (BS) side and at the user equipment (UE) side is necessary in order to establish a strong path conveying enough signal power. Finding such beamforming directions is referred to as beam alignment (BA). This paper presents a new scheme for efficient BA. Our scheme finds a strong propagation path identified by an angle-of-arrival (AoA) and angle-of-departure (AoD) pair, by exploring the AoA–AoD domain through pseudo-random multi-finger beam patterns and constructing an estimate of the resulting second-order statistics (namely, the average received power for each pseudo-random beam configuration). The resulting under-determined system of equations is efficiently solved using non-negative constrained least-squares, yielding naturally a sparse non-negative vector solution whose maximum component identifies the optimal path. As a result, our scheme is highly robust to variations of the channel time dynamics compared with alternative concurrent approaches based on the estimation of the instantaneous channel coefficients, rather than of their second-order statistics. In the proposed scheme, the BS probes the channel in the downlink and trains simultaneously an arbitrarily large number of UEs. Thus, “beam refinement,” with multiple interactive rounds of downlink uplink transmissions, is not needed. This results in a scalable BA protocol, where the protocol overhead is virtually independent of the number of UEs, since all the UEs run the BA procedure at the same time. Extensive simulation results illustrate that our approach is superior to the state-of-the-art BA schemes proposed in the literature in terms of training overhead in multi-user scenarios and robustness to variations in the channel dynamics.