Multicell base station cooperation can improve sum-rates and reduce outage in cellular system by sharing user channel state information (CSI). On the basis of inter-cell interference nulling (ICES) at the transmitter sides of cooperative base stations, we propose an adaptive feedback bit allocation scheme to minimize the rate loss due to limited feedback. Furthermore, we investigate the scaling law of the total number of bits per user to maintain a constant rate loss. Simulation results show that the proposed feedback bits allocation strategy provides significant gain compared to equal bits allocation.
Intelligent reflecting surface (IRS) has emerged as a cost-effective solution to enhance wireless communication performance via passive signal reflection. Existing works on IRS have mainly focused on investigating IRS's passive beamforming/reflection design to boost the communication rate for users assuming that their channel state information (CSI) is fully or partially known. However, how to exploit IRS to improve the wireless transmission reliability without any CSI, which is typical in high-mobility/delay-sensitive communication scenarios, remains largely open. In this paper, we study a new IRS-aided communication system with the IRS integrated to its aided access point (AP) to achieve both functions of transmit diversity and passive beamforming simultaneously. Specifically, we first show an interesting result that the IRS's passive beamforming gain in any channel direction is invariant to the common phase-shift applied to all of its reflecting elements. Accordingly, we design the common phase-shift of IRS elements to achieve transmit diversity at the AP side without the need of any CSI of the users. In addition, we propose a practical method for the users to estimate the CSI at the receiver side for information decoding. Meanwhile, we show that the conventional passive beamforming gain of IRS can be retained for the other users with their CSI known at the AP. Furthermore, we derive the asymptotic performance of both IRS-aided transmit diversity and passive beamforming in closed-form, by considering the large-scale IRS with an infinite number of elements. Numerical results validate our analysis and show the performance gains of the proposed IRS-aided simultaneous transmit diversity and passive beamforming scheme over other benchmark schemes.
The main disadvantage of multicarrier system is the high peak-to-average power ratio which can easily result in significant cut-the-top distortion of power amplifier. However, the power efficiency of power amplifier will be reduced by power back-off technology. Therefore, crest factor reduction is important in reducing the peak-to-average power ratio of multicarrier system and improving the efficiency of power amplifier. The peak-to-average power ratio can be effectively reduced with small distortion by the algorithm of crest factor reduction based on peak cancellation. And the performance of peak-to-average power ratio is better with the same error vector magnitude.
No abstract is provided for this article.
Aerial-ground interference mitigation is a challenging issue in the emerging cellular-connected unmanned aerial vehicle (UAV) communications. Due to the strong line-of-sight (LoS) air-to-ground (A2G) channels, the UAV may impose/suffer more severe uplink/downlink interference to/from the cellular base stations (BSs) as compared to the ground users. To tackle this challenge, we propose in this paper to apply the non-orthogonal multiple access (NOMA) technique to the uplink communication from a UAV to cellular BSs, under spectrum sharing with the existing ground users. However, for our considered system, traditional NOMA with only local interference cancellation (IC) at individual BSs, termed non-cooperative NOMA, may provide very limited gain compared to the orthogonal multiple access (OMA). This is because there are a large number of co-channel BSs due to the LoS A2G channels, and thus, the rate performance of the UAV is severely limited by the BS with the worst channel condition with the UAV. To mitigate the UAV's uplink interference without significantly compromising its achievable rate, a new cooperative NOMA scheme is proposed in this paper by exploiting the existing backhaul links among BSs. Specifically, some BSs with better channel conditions are selected to decode the UAV's signals first, and then forward the decoded signals to their backhaul-connected BSs for IC. To investigate the optimal design of cooperative NOMA and air-ground performance tradeoff, we maximize the weighted sum-rate of the UAV and ground users by jointly optimizing the UAV's rate and power allocations over multiple resource blocks as well as their associated BSs. However, this problem is difficult to be solved optimally. To obtain useful insights, we first consider two special cases with egoistic and altruistic transmission strategies of the UAV, respectively, and solve their corresponding problems optimally. Next, we consider the general case and propose an efficient suboptimal solution by applying the alternating optimization and successive convex approximation techniques. Numerical results show that the proposed cooperative NOMA scheme yields significant throughput gains than those by the traditional OMA as well as the non-cooperative NOMA benchmark.
This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system, where a UAV-mounted energy transmitter (ET) broadcasts wireless energy to charge distributed energy receivers (ERs) on the ground. In particular, we consider a basic two-user scenario, and investigate how the UAV can optimally exploit its mobility to maximize the amount of energy transferred to the two ERs during a given charging period. We characterize the achievable energy region of the two ERs, by optimizing the UAV's trajectory subject to a maximum speed constraint. We show that when the distance between the two ERs is smaller than a certain threshold, the boundary of the energy region is achieved when the UAV hovers above a fixed location between them for all time; while when their distance is larger than the threshold, to achieve the boundary of the energy region, the UAV in general needs to hover and fly between two different locations above the line connecting them. Numerical results show that the optimized UAV trajectory can significantly improve the WPT efficiency and fairness of the two ERs, especially when the UAV's maximum speed is large and/or the charging duration is long.
No abstract is provided for this article.
This paper studies an unmanned aerial vehicle (UAV)-enabled multicasting system, where a UAV is dispatched to disseminate a common file to a number of geographically distributed ground terminals (GTs). Our objective is to design the UAV trajectory to minimize its mission completion time, while ensuring that each GT is able to successfully recover the file with a high probability required. We consider the use of practical random linear network coding (RLNC) for UAV multicasting, so that each GT is able to recover the file as long as it receives a sufficiently large number of coded packets. However, the formulated UAV trajectory optimization problem is non-convex and difficult to be directly solved. To tackle this issue, we first derive an analytical lower bound for the success probability of each GT's file recovery. Based on this result, we then reformulate the problem into a more tractable form, where the UAV trajectory only needs to be designed to meet a set of constraints each on the minimum connection time with a GT, during which their distance is below a designed threshold. We show that the optimal UAV trajectory only needs to constitute connected line segments, thus it can be obtained by determining first the optimal set of waypoints and then UAV speed along the lines connecting the waypoints. We propose practical schemes for the waypoints design based on a novel concept of virtual base station (VBS) placement and by applying convex optimization techniques. Furthermore, for given set of waypoints, we obtain the optimal UAV speed over the resulting path efficiently by solving a linear programming (LP) problem. Numerical results show that the proposed UAV-enabled multicasting with optimized trajectory design achieves significant performance gains as compared to benchmark schemes.
This paper considers spectrum sharing for wireless communication between a cognitive radio (CR) link and a primary radio (PR) link. It is assumed that the CR protects the PR transmission by applying the so-called interference-temperature constraint, whereby the CR is allowed to transmit regardless of the PR's on/off status provided that the resultant interference power level at the PR receiver is kept below some predefined threshold. For the fading PR and CR channels, the interference-power constraint at the PR receiver is usually one of the following two types: One is to regulate the average interference power (AIP) over all the fading states, while the other is to limit the peak interference power (PIP) at each fading state. From the CR's perspective, given the same average and peak power threshold, the AIP constraint is more favorable than the PIP counterpart because of its more flexibility for dynamically allocating transmit powers over the fading states. On the contrary, from the perspective of protecting the PR, the more restrictive PIP constraint appears at a first glance to be a better option than the AIP. Some surprisingly, this paper shows that in terms of various forms of capacity limits achievable for the PR fading channel, e.g., the ergodic and outage capacities, the AIP constraint is also superior over the PIP. This result is based upon an interesting interference diversity phenomenon, i.e., randomized interference powers over the fading states in the AIP case are more advantageous over deterministic ones in the PIP case for minimizing the resultant PR capacity losses. Therefore, the AIP constraint results in larger fading channel capacities than the PIP for both the CR and PR transmissions.
Summary With the changes of the times and the rapid development of the mobile Internet and the Internet of Things, network communications are facing increasingly severe challenges. Due to the user exclusivity of the orthogonal resources of the existing orthogonal multiple access technology, it is difficult for the number of accessible users and the spectral efficiency to meet the application requirements of network communications. 5G technology will meet the diverse business needs of people in various scenarios such as life, work, leisure, and transportation. This paper analyzes the 5G‐oriented non‐orthogonal multiple access (NOMA) technology and designs and implements a NOMA technology simulation platform laboratory based on 5G technology. The entire simulation experiment adopts a modular design concept so that it can be modified and extended in the future network communication. In this paper, the user pairing scheme and power allocation algorithm of NOMA technology are studied in depth. For the user pairing scheme, this paper adopts two schemes: traversal search pairing scheme and grouping pairing scheme. For the same algorithm for power allocation, this paper studies two suboptimal power allocation algorithms including fixed power allocation and partial transmission power allocation. Simulation experiments show that the average cell throughput and cell edge user throughput of NOMA are slightly lower than when the traversal search pairing scheme is adopted: the average cell throughput has decreased by approximately 4%, and the cell edge user throughput has decreased by approximately 1.6%. The packet pairing scheme is a compromise between complexity and throughput performance. For different power allocation factor values, the overall throughput performance of some transmission power allocation algorithms is better than the flower pollination algorithm (FPA).
In this letter, the achievable rate maximization problem is considered for intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems in an underlay spectrum sharing scenario, subject to interference power constraints at the primary users. The formulated non-convex optimization problem is challenging to solve due to its non-convexity as well as coupling design variables in the constraints. Different from existing works that are mostly based on alternating optimization (AO), we propose a penalty dual decomposition based gradient projection (PDDGP) algorithm to solve this problem. We also provide a convergence proof and a complexity analysis for the proposed algorithm. We benchmark the proposed algorithm against two known solutions, namely a minimum mean-square error based AO algorithm and an inner approximation method with block coordinate descent. Specifically, the complexity of the proposed algorithm grows <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linearly</i> with respect to the number of reflecting elements at the IRS, while that of the two benchmark methods grows with the third power of the number of IRS elements. Moreover, numerical results show that the proposed PDDGP algorithm yields considerably higher achievable rate than the benchmark solutions.
Bit-interleaved coded modulation (BICM) was first proposed by Zehavi to increase the time diversity of coded modulation over Rayleigh fading channels. In order to make up for the deficiency of BICM over Gaussian channel, BICM with iterative demapping and decoding (BICM-ID) was suggested by Li. Recent research on BICM-ID found that LDPC codes with BICM-ID could get better performance than traditional turbo codes. Since the information processed in BILCM-ID system contains both modulation information and decoding information, we show that the joint optimization for constellation mapping and degree distribution of LDPC codes is necessary. Moreover, we valued the effect of iteration on the bit error performance with different mapping schemes in this paper.
In a recent paper, the authors introduced the save-then-transmit (ST) protocol, designed for a wireless link with an energy harvesting transmitter. The outage minimizing ST protocol computes the fraction of each frame to reserve for energy harvesting by the main energy storage device (ESD); the rest of the frame is used concurrently for message transmission and for charging of the secondary ESD. In this paper, we study the performance loss due to the randomness of energy availability at the transmitter, compared to a conventional system with a deterministic supply of power, through a derivation of the outage probability expression under certain special conditions. It will be shown that this performance loss is dependent on the distribution assumed for the energy harvesting rate, X. Different parameter settings for a Gamma-distributed X lead to performance gaps ranging from 1 to 10 dB. These results confirm that the performance loss incurred by using an unreliable energy source is heavily dependent on the variability of the source.
