In this paper, a novel single layer Multiple Input–Multiple Output (MIMO) antenna for Fifth-Generation (5G) 28 GHz frequency band applications is proposed and investigated. The proposed MIMO antenna operates in the Ka-band, which is the most desirable frequency band for 5G mm-wave communication. The dielectric material is a Rogers-5880 with a relative permittivity, thickness and loss tangent of 2.2, 0.787 mm and 0.0009, respectively, in the proposed antenna design. The proposed MIMO configuration antenna element consists of triplet circular shaped rings surrounded by an infinity-shaped shell. The simulated gain achieved by the proposed design is 6.1 dBi, while the measured gain is 5.5 dBi. Furthermore, the measured and simulated antenna efficiency is $90\%$ and $92\%$, respectively. One of the MIMO performance metrics—i.e., the Envelope Correlation Coefficient (ECC)—is also analyzed and found to be less than 0.16 for the entire operating bandwidth. The proposed MIMO design operates efficiently with a low ECC, better efficiency and a satisfactory gain, showing that the proposed design is a potential candidate for mm-wave communication.

This paper presents an S-shape four-port Multiple Input Multiple Output (MIMO) wideband mmWave antenna with bandwidth of 25 GHz to 39 GHz. The antenna is designed on 0.254 mm ultra-thin RO5880 with permittivity of 2.3. The dimensions of proposed S-shape antenna are 10 × 12 mm for single element and 24 × 24 mm for four-port MIMO configuration. A decoupling network is introduced to further compress mutual coupling among MIMO elements. The peak gain achieved is 7.1 dBi and MIMO assembly delivers diversity scheme. The proposed MIMO antenna is fabricated, and simulated results are found to be in excellent agreement with simulations. Through the results obtained, the proposed MIMO antenna system can be considered as a potential candidate for future mmWave devices.

This article presents the design of a uni-planar MIMO antenna system for sub-6 GHz 5G-enabled smartphones. The MIMO antenna designed comprises four loop-shaped radiators placed at each corner of the mobile phone board, which follows the principle of pattern diversity. The single-antenna element resonates at 3.5 GHz, its impedance bandwidth is noted to be 1.28 GHz (3–4.28 GHz) for S${}_{11}\le$ −6 dB, and it is equal to 720 MHz (3.18–3.9 GHz) for S${}_{11}\le$ −10 dB. For a single-antenna element, a peak gain of 3.64 dBi is observed with an antenna efficiency of >90%. The isolation of >10 dB between antenna elements is achieved for the MIMO configuration. Furthermore, the MIMO antenna designed provides enough radiation coverage to support different sides of the mobile phone board, which is an important feature for future 5G-enabled handsets. In addition, the impacts of human hands and heads on MIMO antenna performance are investigated, and acceptable performance in the data and conversation modes is observed.

Data caching has emerged as a promising technique to handle growing data traffic and backhaul congestion of wireless networks. However, there is a concern regarding how and where to place contents to optimize data access by the users. Data caching can be exploited close to users by deploying cache entities at Small Base Stations (SBSs). In this approach, SBSs cache contents through the core network during off-peak traffic hours. Then, SBSs provide cached contents to content-demanding users during peak traffic hours with low latency. In this paper, we exploit the potential of data caching at the SBS level to minimize data access delay. We propose an intelligence-based data caching mechanism inspired by an artificial intelligence approach known as Reinforcement Learning (RL). Our proposed RL-based data caching mechanism is adaptive to dynamic learning and tracks network states to capture users’ diverse and varying data demands. Our proposed approach optimizes data caching at the SBS level by observing users’ data demands and locations to efficiently utilize the limited cache resources of SBS. Extensive simulations are performed to evaluate the performance of proposed caching mechanism based on various factors such as caching capacity, data library size, etc. The obtained results demonstrate that our proposed caching mechanism achieves 4% performance gain in terms of delay vs. contents, 3.5% performance gain in terms of delay vs. users, 2.6% performance gain in terms of delay vs. cache capacity, 18% performance gain in terms of percentage traffic offloading vs. popularity skewness ($\gamma$), and 6% performance gain in terms of backhaul saving vs. cache capacity.

User Equipment (UE) is equipped with limited cache resources that can be utilized to offload data traffic through device-to-device (D2D) communications. Data caching at a UE level has the potential to significantly alleviate data traffic burden from the backhaul link. Moreover, in wireless networks, users exhibit mobility that poses serious challenges to successful data transmission via D2D communications due to intermittent connectivity among users. Users’ mobility can be exploited to efficiently cache contents by observing connectivity patterns among users. Therefore, it is crucial to develop an efficient data caching mechanism for UE while taking into account users’ mobility patterns. In this work, we propose a mobility-aware data caching approach to enhance data offloading via D2D communication. First, we model users’ connectivity patterns. Then, contents are cached in UE’ cache resources based on users’ data preferences. In addition, we also take into account signal-to-interference and noise ratio (SINR) requirements of the users. Hence, our proposed caching mechanism exploits connectivity patterns of users to perform data placement based on users’ own demands and neighboring users to enhance data offloading via cache resources. We performed extensive simulations to investigate the performance of our proposed mobility-aware data caching mechanism. The performance of our proposed caching mechanism is compared to most deployed data caching mechanisms, while taking into account the dynamic nature of the wireless channel and the interference experienced by the users. From the obtained results, it is evident that our proposed approach achieves 14%, 16%, and 11% higher data offloading gain than the least frequently used, the Zipf-based probabilistic, and the random caching schemes in case of an increasing number of users, cache capacity, and number of contents, respectively. Moreover, we also analyzed cache hit rates, and our proposed scheme achieves 8% and 5% higher cache hit rate than the least frequently used, the Zipf-based probabilistic, and the random caching schemes in case of an increasing number of contents and cache capacity, respectively. Hence, our proposed caching mechanism brings significant improvement in data sharing via D2D communications.