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This paper provides the signal-to-interference-plus-noise ratio (SINR) complimentary cumulative distribution function (CCDF) and average data rate of the normalized SNR-based scheduling in an uplink cellular network using stochastic geometry. The uplink analysis is essentially different from the downlink analysis in that the per-user transmit power control is performed and that the interferers are composed of at most one transmitting user in each cell other than the target cell. In addition, as the effect of multi-user diversity varies from cell to cell depending on the number of users involved in the scheduling, the distribution of the number of users is required to obtain the averaged performance of the scheduling. This paper derives the SINR CCDF relative to the typical scheduled user by focusing on two incompatible cases, where the scheduler selects a user from all the users in the corresponding Voronoi cell or does not select users near cell edges. In each case, the SINR CCDF is marginalized over the distribution of the number of users involved in the scheduling, which is asymptotically correct if the BS density is sufficiently large or small. Through the simulations, the accuracies of the analytical results are validated for both cases, and the scheduling gains are evaluated to confirm the multi-user diversity gain.
We propose to use channel inversion power control (CIPC) to achieve one-way ultra-reliable and low-latency communications (URLLC), where only the transmission in one direction requires ultra reliability and low latency. Based on channel reciprocity, our proposed CIPC schemes guarantee the power of received signals to be a constant value $Q$, by varying the transmit signals and power, which relaxes the assumption of knowing channel state information (CSI) at the receiver. Thus, the CIPC schemes eliminate the overhead of CSI feedback, reduce communication latency, and explore the benefits of multiple antennas to significantly improve transmission reliability. We derive analytical expressions for the packet loss probability of the proposed CIPC schemes, based on which we determine a closed interval and a convex set for optimizing $Q$ in CIPC with imperfect and perfect channel reciprocities. Our results show that CIPC is an effective means to achieve one-way URLLC. For example, increasing the number of transmit antennas continuously improves reliability and reduces latency, which is a different conclusion from the system using traditional channel estimation and feedback mechanisms. The tradeoff among reliability, latency, and required resources (e.g., transmit antennas) is further revealed, which provides novel principles for designing one-way URLLC systems.
Decoupling uplink (UL) and downlink (DL) is a new architectural paradigm where DL and UL are not constrained to be associated to the same base station (BS). Building upon this paradigm, the goal of the present paper is to provide lower, albeit tight bounds for the ergodic UL capacity of a decoupled cellular network. The analysis is performed for a scenario consisting of a macro BS and a set of small cells (SCs) whose positions are selected randomly according to a Poisson point process of a given spatial density. Based on this analysis simple bounds in closed form expressions are defined. The devised bounds are employed to compare the performance of the decoupled case versus a set of benchmark cases, namely the coupled case, and the situations of having either a single macro BS or only SCs. This comparison provides valuable insights regarding the behavior and performance of such networks, providing simpler expressions for the ergodic UL capacity as a function of the distances to the macro BS and the density of SCs. These expressions constitute a simple guide to the minimum degree of densification that guarantees the Quality of Service (QoS) objectives of the network, thus, providing a valuable tool to the network operator of significant practical and commercial value.
Cellular connected unmanned aerial vehicle (UAV) has been identified as a promising paradigm and attracted a surge of research interest recently. Although the nearly line-of-sight (LoS) channels are favorable to receive higher powers, UAV can in turn cause severe interference to each other and to any other users in the same frequency band. In this contribution, we focus on the uplink communications of cellular-connected UAV. To cope with the severe interference among UAV-UEs, several different scheduling and power control algorithms are proposed to optimize the spectrum efficiency (SE) based on the geometrical programming (GP) principle together with the successive convex approximation (SCA) technique. The proposed schemes include maximizing the sum SE of UAVs, maximizing the minimum SE of UAVs, etc., applied in the frequency domain and/or the time domain. Moreover, the quality of service (QoS) constraint and the uplink single-carrier (SC) constraint are also considered. The performances of these power and resource allocation algorithms are evaluated via extensive simulations in both full buffer transmission mode and bursty traffic mode. Numerical results show that the proposed algorithms can effectively enhance the uplink SEs of cellular-connected UAVs.
In this paper, using the stochastic geometry, we develop a tractable uplink modeling framework for the outage probability of both the single and multi-tier millimeter wave (mmWave) cellular networks. Each tiers mmWave base stations (BSs) are randomly located and they have particular spatial density, antenna gain, receiver sensitivity, blockage parameter and pathloss exponents. Our model takes account of the maximum power limitation and the per-user power control. More specifically, each user, which could be in line-of-sight (LOS) or non-LOS to its serving mmWave BS, controls its transmit power such that the received signal power at its serving BS is equal to a predefined threshold. Hence, a truncated channel inversion power control scheme is implemented for the uplink of mmWave cellular networks. We derive closed-form expressions for the signal-to-interference-and-noise-ratio (SINR) outage probability for the uplink of both the single and multi-tier mmWave cellular networks. Furthermore, we analyze the case with a dense network by utilizing the simplified model, where the LOS region is approximated as a fixed LOS disc. The results show that imposing a maximum power constraint on the user significantly affects the SINR outage probability in the uplink of mmWave cellular networks.
In this study, we propose two schemes for uplink control channels based on non-contiguous complementary sequences (CSs) where the peak-to-average-power ratio (PAPR) of the resulting orthogonal frequency division multiplexing (OFDM) signal is always less than or equal to 3 dB. To obtain the proposed schemes, we extend Golays concatenation and interleaving methods by considering extra upsampling and shifting parameters. The proposed schemes enable a flexible non-contiguous resource allocation in frequency, e.g., an arbitrary number of null symbols between the occupied resource blocks (RBs). The first scheme separates the PAPR minimization and the inter-cell interference minimization problems. While the former is solved by spreading the sequences in a Golay complementary pair (GCP) with the sequences in another GCP, the latter is managed by designing a set of GCPs with low cross-correlation. The second scheme generates reference symbols (RSs) and data symbols on each RB as parts of an encoded CS. Therefore, it enables coherent detection at the receiver side. The numerical results show that the proposed schemes offer significantly improved PAPR and cubic metric (CM) results in case of non-contiguous resource allocation as compared to the sequences defined in 3GPP New Radio (NR) and Zadoff-Chu (ZC) sequences.