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Register a new userCooperative 3D Beamforming for Small-Cell and Cell-Free 6G Systems
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Added by
Sarath Gopi
Publication date
2021
fields
Electronic Engineering
and research's language is
English
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Three dimensional (3D) resource reuse is an important design requirement for the prospective 6G wireless communication systems. Hence, we propose a cooperative 3D beamformer for use in 3D space. Explicitly, we harness multiple base station antennas for joint zero forcing transmit pre-coding for beaming the transmit signals in specific 3D directions. The technique advocated is judiciously configured for use in both cell-based and cell-free wireless architectures. We evaluated the performance of the proposed scheme using the novel metric of Volumetric Spectral Efficiency (VSE). We also characterized the performance of the scheme in terms of its spectral efficiency (SE) and Bit Error Rate (BER) through extensive simulation studies.
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The support for aerial users has become the focus of recent 3GPP standardizations of 5G, due to their high maneuverability and flexibility for on-demand deployment. In this paper, probabilistic caching is studied for ultra-dense small-cell networks with terrestrial and aerial users, where a dynamic on-off architecture is adopted under a sophisticated path loss model incorporating both line-of-sight and non-line-of-sight transmissions. Generally, this paper focuses on the successful download probability (SDP) of user equipments (UEs) from small-cell base stations (SBSs) that cache the requested files under various caching strategies. To be more specific, the SDP is first analyzed using stochastic geometry theory, by considering the distribution of such two-tier UEs and SBSs as Homogeneous Poisson Point Processes. Second, an optimized caching strategy (OCS) is proposed to maximize the average SDP. Third, the performance limits of the average SDP are developed for the popular caching strategy (PCS) and the uniform caching strategy (UCS). Finally, the impacts of the key parameters, such as the SBS density, the cache size, the exponent of Zipf distribution and the height of aerial user, are investigated on the average SDP. The analytical results indicate that the UCS outperforms the PCS if the SBSs are sufficiently dense, while the PCS is better than the UCS if the exponent of Zipf distribution is large enough. Furthermore, the proposed OCS is superior to both the UCS and PCS.
In this work, we investigate hybrid analog-digital beamforming (HBF) architectures for uplink cell-free (CF) millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. {We first propose two HBF schemes, namely, decentralized HBF (D-HBF) and semi-centralized HBF (SC-HBF). In the former, both the digital and analog beamformers are generated independently at each AP based on the local channel state information (CSI). In contrast, in the latter, only the digital beamformer is obtained locally at the AP, whereas the analog beamforming matrix is generated at the central processing unit (CPU) based on the global CSI received from all APs. We show that the analog beamformers generated in these two HBF schemes provide approximately the same achievable rates despite the lower complexity of D-HBF and its lack of CSI requirement.} Furthermore, to reduce the power consumption, we propose a novel adaptive radio frequency (RF) chain-activation (ARFA) scheme, which dynamically activates/deactivates RF chains and their connected analog-to-digital converters (ADCs) and phase shifters (PSs) at the APs based on the CSI. For the activation of RF chains, low-complexity algorithms are proposed, which can achieve significant improvement in energy efficiency (EE) with only a marginal loss in the total achievable rate.
A silicon 3D detector with a single cell of 50x50 um2 was produced and evaluated for timing applications. The measurements of time resolution were performed for 90Sr electrons with dedicated electronics used also for determining time resolution of Low Gain Avalanche Detectors (LGADs). The measurements were compared to those with LGADs and also simulations. The studies showed that the dominant contribution to the timing resolution comes from the time walk originating from different induced current shapes for hits over the cell area. This contribution decreases with higher bias voltages, lower temperatures and smaller cell sizes. It is around 30 ps for a 3D detector of 50x50 um2 cell at 150 V and -20C, which is comparable to the time walk due to Landau fluctuations in LGADs. It even improves for inclined tracks and larger pads composed of multiple cells. A good agreement between measurements and simulations was obtained, thus validating the simulation results.
Recent achievement in self-interference cancellation algorithms enables potential application of full-duplex (FD) in 5G radio access systems. The exponential growth of data traffic in 5G can be supported by having more spectrum and higher spectral efficiency. FD communication promises to double the spectral efficiency by enabling simultaneous uplink and downlink transmissions in the same frequency band. Yet for cellular access network with FD base stations (BS) serving multiple users (UE), additional BS-to-BS and UE-to-UE interferences due to FD operation could diminish the performance gain if not tackled properly. In this article, we address the practical system design aspects to exploit FD gain at network scale. We propose efficient reference signal design, low-overhead channel state information feedback and signalling mechanisms to enable FD operation, and develop low-complexity power control and scheduling algorithms to effectively mitigate new interference introduced by FD operation. We extensively evaluate FD network-wide performance in various deployment scenarios and traffic environment with detailed LTE PHY/MAC modelling. We demonstrate that FD can achieve not only appreciable throughput gains (1.9x), but also significant transmission latency reduction~(5-8x) compared with the half-duplex system.
We consider Internet of Things (IoT) organized on the principles of cell-free massive MIMO. Since the number of things is very large, orthogonal pilots cannot be assigned to all of them even if the things are stationary. This results in an unavoidable pilot contamination problem, worsened by the fact that, for IoT, since the things are operating at very low transmit power. To mitigate this problem and achieve a high throughput, we use cell-free systems with optimal linear minimum mean squared error (LMMSE) channel estimation, while traditionally simple suboptimal estimators have been used in such systems. We further derive the analytical uplink and downlink signal-to-interference-plus-noise ratio (SINR) expressions for this scenario, which depends only on large scale fading coefficients. This allows us to design new power control algorithms that require only infrequent transmit power adaptation. Simulation results show a 40% improvement in uplink and downlink throughputs and 95% in energy efficiency over existing cell-free wireless systems and at least a three-fold uplink improvement over known IoT systems based on small-cell systems.
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