This paper proposes a novel communication scheme utilizing Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) and Index Modulation (IM) for Industrial Internet of Things (IIoT) to enhance Spectral Efficiency (SE). In this scheme, information bits are conveyed through the active antennas combination index of the two sensors at receiver, as well as the Pattern Index (PI) of designed subsurfaces on STAR-RIS. To enable reliable detection at the IIoT Control Center (CC), a joint Maximum Likelihood (ML) detector is introduced, and an Efficient ML Approximation (EMAL) detector is developed to lower computational complexity while retaining comparable Bit Error Rate (BER). In the theoretical analysis, closed-form expressions for the Average BER (ABER) under ML detection and computational complexity are provided, and the ABER analysis is validated by Monte Carlo simulations. Theoretical analysis and simulation results confirm that the proposed scheme significantly improves SE and ABER performance. Moreover, through simulation results, the scheme’s flexibility in configuring the number of antennas of the two sensors to meet diverse system requirements is also confirmed.

With the advent of extreme massive multiple-input multiple-output (X-MIMO) systems and the emerging Frequency Range 3 (FR3, 7.125–24.25 GHz) for 6G networks, the dimensionality of channel state information (CSI) has increased significantly. However, to ensure scalable operation and avoid an excessive increase in overhead, the feedback size is expected to increase only marginally. This constraint necessitates an extremely high compression ratio during CSI feedback, which in turn severely degrades the reconstruction performance of standardized codebooks. Moreover, even when employing AI methods, training models from scratch under such severe compression conditions leads to vanishing or exploding gradients, resulting in unstable training and diminished performance. In this paper, we propose a novel hierarchical transfer learning with progressive compression (HTL-PC) method to address these challenges. Our approach leverages a pretrained autoencoder extraction block from a large-feedback model and progressively transfers it to models with smaller latent spaces, thereby enabling stable training under severe compression conditions. Extensive system-level simulations demonstrate that the proposed HTL-PC method achieves remarkable improvements in squared generalized cosine similarity and downlink cell throughput over benchmark techniques.

To mitigate the growing overhead resulting from the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, various autoencoder-based schemes employing two-sided artificial intelligence (AI) models for channel state information (CSI) feedback-specifically, feedback of the precoding matrix-have been proposed. In these twosided AI models, the encoder and decoder are separately deployed at the user equipment (UE) and the base station (BS), posing significant challenges in maintaining synchronization between them in real-world scenarios with multiple UEs and BSs. In this paper, we propose a novel transformer-based temporaldomain multi-length optimized (TMO) decoder that effectively leverages temporal correlations in MIMO channels to enhance CSI reconstruction. Unlike existing schemes that require different models or additional signaling overhead for re-synchronization between the encoder and decoder under varying conditions, the transformer-based TMO decoder can robustly recover CSI by utilizing feedback of the precoding matrix with temporal information using a single fixed model for inputs of varying sequential time steps. Performance evaluations demonstrate that the proposed transformer-based TMO decoder achieves significantly higher squared generalized cosine similarity and average downlink throughput compared to state-of-the-art techniques.

The L1/L2-triggered mobility (LTM) technique, which supports beam and cell-level mobility and can significantly reduce handover (HO) interruption time, is expected to be defined as a baseline mobility technique for 5G-Advanced and 6G. However, as the HO decision criteria in LTM changes to an instantaneous value-based L1 measurement, it is expected that the problem of HO interruption due to frequent occurrence of HO will increase. Even if LTM is introduced, there is still a weakness in commercial systems where the data rate temporarily decreases due to conservative link adaptation behavior caused by the absence of initial channel state information (CSI) immediately after HO. In this paper, we propose an improved mobility management method that can respond to various signal degradation situations by simultaneously utilizing L1 measurements and L2 filtered measurements. Additionally, we propose an early CSI acquisition scheme that can acquire the CSI of the target cell before HO execution and reports the early acquired CSI to the target cell without any delay immediately after the HO. The result of the system-level simulation shows that proposed scheme reduces HO failure ratio by about 31%, and prevents a temporary low data rate due to the absence of initial CSI.

In this paper, we propose a novel polarized reconfigurable intelligent surface (PRIS) -assisted polarized spatial scattering modulation (PSSM) for millimeter wave (mmWave) multiple input multiple output (MIMO) systems. In the PRIS-PSSM system, the PRIS is employed between the transmitter and receiver to provide a supplementary link to enhance spectrum efficiency. A strong line-of-light (LoS) path is considered in the transmitter-PRIS channel to reduce transmission power and non-line-of-light (NLoS) paths are considered in the PRIS-receiver channel to utilize scatters to convey information bits. At the receiver, an optimal maximum likelihood detector (MLD), a sub-optimal MLD, and a low-complexity detector based on minimum mean square error (MMSE) algorithm are proposed and applied to detect the received signals. Furthermore, two union upper bounds (UUBs) based on the optimal MLD and sub-optimal MLD are respectively derived in a closed-form. And the tightness of the proposed two closed-form UUBs are validated via link level simulations. In addition, the complexity of the proposed three detection algorithms is compared. Numerical results demonstrate that the proposed PRIS-PSSM system outperforms the conventional PSSM system in terms of the average bit error probability (ABEP). And the performance of the PRIS-PSSM system can be improved significantly in proportion to the number of PRIS elements.

The application of internet of things (IoT) may suffer from serious security issue, such as the attack and wiretap from jammers and eavesdroppers, which results in the degradation of reception of useful signals at the IoT devices (users), affecting the secrecy performance for the IoT application. In this work, we propose to introduce an active simultaneously transmitting and reflecting reconfigurable intelligent surface (ASTAR-RIS) to resist jamming and eavesdropping caused by multiple jammers and eavesdroppers, respectively. For the security purpose, we formulate a sum rate maximization problem subject to the imperfect channel state information and maximum tolerable leakage rate at the eavesdroppers. By jointly optimizing beamformers at the base station and that at the ASTAR-RIS including phase shifts and amplification factors, simulation results show that the proposed robust scheme is able to provide significant improvement as compared with other baselines.

The integration of the Sixth-Generation (6G) communication technology with the Internet of Things (IoT) is one of the directions in achieving a digitalized world, aiming to provide ultra-high-speed communication services that exhibit higher energy-efficiency, lower latency, and heightened reliability and availability. In this paper, we investigate the use of the Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS), one of the candidate technologies for 6G communication, along with the Index Modulation (IM) in multi-antennas Ambient Backscatter Communication System (ABCS) to form the STAR-RIS-assisted ABCS with Spatial Modulation (STAR-RIS-ABCS-SM). In particular, through the utilization of STAR-RIS and backscatter communication, we meet the demand for low-power wireless communication devices in the green communication, which is also a crucial characteristic of the IoT. Specifically, we introduce STAR-RIS into ABCS, which not only significantly boost the signal strength but also achieve full communication coverage. Meanwhile, we apply the SM technology in the multi-antennas Backscatter Tags (BTs), located on both sides of the STAR-RIS, and use joint detection at the reader to enhance the system’s Spectral Efficiency (SE) as well as its Bit Error Rate (BER) performance. Furthermore, we divide the STAR-RIS into various subsurfaces to form patterns that further enhance SE, which is termed STAR-RIS-assisted ABCS with Pattern Index and SM (STAR-RIS-ABCS-PISM) scheme. Finally, theoretical BER analytical expressions for both schemes are derived and presented. Simulation and theoretical results demonstrate the enhanced performance of the proposed schemes as well as the validity of the system model.

In this paper, a novel three-dimensional polarized spatial scattering modulation (3-D PSSM), which exploits the available degrees of freedom in the spatial scattering path domain and polarization domain to increase spectral efficiency, is proposed for uplink millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) system. At the receiver, considering the non-orthogonality of the array vectors, a whitening filter based on optimal maximum likelihood detection (MLD) is designed and applied to detect received signals. A tight union upper bound (UUB) on the average bit error probability (ABEP) is derived in a closed-form. Furthermore, a simplified UUB on the ABEP is derived for fast evaluation of the system. And the tightness of the derived UUBs is validated via Monte Carlo simulations. In addition, the 3-D PSSM system under imperfect channel state information (CSI) is investigated. Finally, the ABEP performance of the 3-D PSSM is analyzed in typical indoor propagation environments. Numerical results demonstrate that the proposed 3-D PSSM system outperforms the conventional three-dimensional spatial scattering modulation (3-D SSM) system and the two-dimensional (2-D) PSSM system, which is considerably degraded due to indiscernible scattering paths.

In the realm of mobile communications, the receiver often encounters undesired situations where it receives only noise, interference, or unintended signals. In such cases, it may incorrectly infer that the decoding result is valid, particularly when the error detection capability, mainly provided by a cyclic redundancy check (CR C) code, falls short. While bounded distance decoding techniques based on the employed error-correcting code have been introduced to address this issue, there is still room for improvement especially when dealing with unintended signals. In this paper, we present a formula to identify the situation of unintended signals and find it expressed in terms of a metric called discrepancy. Utilizing this discrepancy, we interpret the problem of determining the validity of decoding results as a binary classification task. Then, we propose suitable machine learning techniques to improve the accuracy of the binary classification process. Our experimental results, conducted for the 5G New Radio (NR) system, demonstrate significant performance improvement resulting from the application of the proposed methods.

The non-linear distortion caused by non-ideal radio frequency (RF) components especially the power amplifier (PA) limits the applications of higher order modulation and degrades power utilization efficiency. To improve the achievable rate in modern systems, it becomes critical to overcome the non-linear distortion so that we can maximize the opportunity of using higher order modulation such as 256QAM, 1024QAM and even 4096QAM at high transmission power. In this paper, we introduce an artificial intelligence (AI)-enabled non-linearity compensation scheme (AI-NC) to avoid the "model deficit" problem. The introduced AI-NC adapts the Echo State Network (ESN) to enable fast online training without additional training overhead. Furthermore, it is general enough to be used for any types of power amplifiers (PAs) with different non-linearity characteristics and different channel environments. It can also be used for the communication system using multiple antennas and supporting multiple users simultaneously. Simulation results and hardware-based tests show that the proposed AI-NC can drastically improve the link performance and/or coverage of higher order modulations in practice.

Unmanned aerial vehicles (UAVs) could acquire strong line-of-sight (LoS) channels for terrestrial nodes, which means UAV communications are more vulnerable to jammers and eavesdroppers. Thanks to the reconfigurable intelligent surface (RIS), it is capable of reconfiguring the propagation environment and has good prospects for forthcoming secure transmission in combination with UAV wireless network. In this paper, we facilitate RIS to aid the uplink communication between the ground user and the UAV in the existence of a malevolent jammer and an eavesdropper by maximizing the average secrecy rate (ASR) of the proposed scheme. In order to achieve this goal, we jointly optimize the transmission power of the ground user, the RIS phase shift, and the trajectory of the UAV. Nevertheless, the proposed problem cannot be solved directly because of the coupled optimization variables and the non-convexity. Consequently, we tackle it by decomposing the original problem into three achievable sub-problems, in which formulated problem could be handled by using alternative optimization, the successive convex approximation, and semidefinite relaxation. Finally, we continuously optimize three variables and iterate over three sub-problems until the ASR converges to a stationary value. Simulation results show that the proposed scheme effectively boost the ASR compared with other baselines.

Since the start of 5G New Radio (NR) work in the 3rd Generation Partnership Project (3GPP) in early 2016, tremendous progress has been made in both standardization and commercial deployments. The first 5G NR release (Release 15) laid out a solid foundation in accommodating a diverse set of services, a wide range of spectra, and a variety of deployment scenarios, while being forward compatible. Expansion to vertical domain services [e.g., vehicle to everything (V2X), non-terrestrial networks (NTN)] was introduced in Release 16. Such an expansion was further accelerated in Release 17, with the standardization work being completed despite the extreme challenges due to COVID-19.

Since the start of 5G work in 3GPP in early 2016, tremendous progress has been made in both standardization and commercial deployments. 3GPP is now entering the second phase of 5G standardization, known as5G-Advanced, built on the 5G baseline in 3GPP Releases 15, 16, and 17. 3GPP Release 18, the start of 5G-Advanced, includes a diverse set of features that cover both device and network evolutions, providing balanced mobile broadband evolution and further vertical domain expansion and accommodating both immediate and long-term commercial needs. 5G-Advanced will significantly expand 5G capabilities, address many new use cases, transform connectivity experiences, and serve as an essential step in developing mobile communications towards 6G. This paper provides a comprehensive overview of the 3GPP 5G-Advanced development, introducing the prominent state-of-the-art technologies investigated in 3GPP and identifying key evolution directions for future research and standardization.

Full duplex (FD) communication is considered as a promising technology in the development of 5G-advanced and 6G systems as it theoretically doubles the capability of channel. However, this improvement relying on a simultaneously bidirectional manner of communication induces intrinsic self-interference (SI) demanding to be fully cancelled, which is generally intractable. This challenge is minimized in the scenario of integrated access and backhaul (IAB) networks operated in millimeter wave (mmW) band, as its transceivers are stationary and the complexity of SI is greatly reduced by beamforming technique. As a matter of fact, FD can be a pioneering technique to unlock the full potential mmW-based IAB network by releasing its suffering of the half-duplex inefficiency. This article presents the design principle and validation of a practical SI cancellation (SIC) technique in the case of high transmission power class in mmW-based IAB networks. The proposed technique sequentially eliminates SI from the spatial, RF, and digital domains that reduces the SI down to the noise floor. To validate the technique, a prototype system is developed in accordance with 5G IAB specifications and field tests are conducted. Results suggest that the designed mmW SIC transceiver significantly reduces residual-interference to noise ratio (R-INR) to 2.1 dB or less. Additionally, a system-level simulation is conducted in line with 5G IAB evaluation methodology, which explores the potential performance gain of the proposed technique in presence of cross-link interference (CLI). Results indicate that the method could yield a cell throughput gain of about 84%, compared to the current time division duplex deployment.

In this paper, we propose a new user-plane (UP) network architecture for 6G cellular networks, where there is no distinction between radio access network (RAN) and core network (CN). We define a new network function (NF), called merged-UP (M-UP), where the UP functions of both RAN and CN sides are merged, thus enabling efficient protocol operations. We also propose an IP flow-based radio quality-of-service (QoS) control scheme to support 6G services with diverse QoS requirements. Based on our network testbed system, we show that the proposed architecture improves the system performance in terms of packet processing load and maximum throughput.

Network virtualization and cloudification are being actively introduced into mobile networks, but the current control-plane (CP) architecture, which distinguishes radio access network (RAN) from core network (CN), is inefficient in fully utilizing the flexibility provided by such technologies. In this paper, we propose a novel CP architecture, which is based on service-based interface (SBI) throughout the network without distinction between RAN and CN, thus reducing the delay and overhead of control signaling. The proposed architecture not only reduces the completion time and amount of signaling of the control procedures by up to 27% and 45%, respectively, but also provides a cloud-friendly environment in which slices and sub-networks with various characteristics can be easily operated by configuring the CP at will.

The ever-increasing roll-out of 5G integrated access and backhaul (IAB) networks in millimeter wave (mmW) band and its current hard-constraint of half duplex operation motivate the study of full duplex (FD) communication in a high power beamforming system. In an mmW IAB network using FD, the intrinsic self-interference inherits the nature of mmW high attenuation and cross link interference can be quite manageable via sharp beamforming between fixed nodes. As a matter of fact, mmW IAB could be a pioneering use case of FD in near future. In this article, a practical self-interference cancellation (SIC) transceiver design is presented targeting for “down to noise floor” SIC in the case of high transmission power class. We developed an mmW prototype testbed system in accordance with 5G IAB specifications. Our experimental results via prototype verifies the feasibility of the designed mmW SIC transceiver and confirms the potential of 2 times throughput gain from FD compared with conventional half duplex in an IAB scenario.

This paper emphasize the importance of the inter-sector self-interference (SI) cancellation to realize the full duplex (FD) for the practical three-sectored cell deployment scenario. We measure the inter-sector SI, the interference coming from the neighboring sector in the same site, using our FD enabled prototype testbed, and then we conduct the system-level simulation to validate the the impact of the inter-sector SI along with the intra-sector SI and cross link interference (CLI) in mmWave integrated access and backhaul (IAB) networks. From our extensive simulation results, the FD operation compared with the half duplex (HD) operation achieves throughput gain of 70% with inter-sector SI cancellation (SIC), while the FD operation achieves throughput gain of 20% without inter-sector SIC. Conclusively, the inter-sector SI should be effectively cancelled out to guarantee the meaningful FD gain over HD.

In multiple-input multiple-output (MIMO) systems, the high-resolution channel information (CSI) is required at the base station (BS) to ensure optimal performance, especially in the case of multi-user MIMO (MU-MIMO) systems. In the absence of channel reciprocity in frequency division duplex (FDD) systems, the user needs to send the CSI to the BS. Often the large overhead associated with this CSI feedback in FDD systems becomes the bottleneck in improving the system performance. In this paper, we propose an AI-based CSI feedback based on an auto-encoder architecture that encodes the CSI at UE into a low-dimensional latent space and decodes it back at the BS by effectively reducing the feedback overhead while minimizing the loss during recovery. Our simulation results show that the AI-based proposed architecture outperforms the state-of-the-art high-resolution linear combination codebook using the DFT basis adopted in the 5G New Radio (NR) system.

Full duplex (FD) communication is an enabling technology with simultaneous uplink and downlink transmission over the same spectrum, which could not only virtually double the spectrum but also shorten the latency of bi-directional communications. One of the key challenges to bring full duplex into reality is how to design a practically implementable self-interference cancellation (SIC). This paper promotes a practical joint-design of SIC capable of >120dB SIC gain to make in-band FD practically viable. It consists of novel integrated SIC antenna, multi-tap tunable RF SIC and non-linear digital SIC. Further, a prototype system implemented using in-band FD with 5G NR commercial level hardware components is presented, which not only verifies in-band FD is practically implementable with the proposed joint SIC, but also achieves highest SIC results, i.e. 122.5dB SIC capability with 32dBm transmit power, to our best knowledge. This result confirms the appealing potential of in-band FD and conclusively, the in-band FD communication with the developed effective SIC turns out to be a promising enabler for future business thriving.

To realize wireless communications in tera-hertz (THz) spectrum, the design of transmit signal with low peak-to-average power ratio (PAPR) is essential due to poor power amplifier (PA) efficiency in this extremely high frequency band. Although the discrete Fourier transform (DFT) spread orthogonal frequency-division multiplexing (DFT-s-OFDM) is a viable solution to reduce the PAPR than the conventional orthogonal frequency-division multiple access (OFDMA), the choice between these two schemes in the downlink reveals a fundamental tradeoff between PAPR and multiuser diversity. In this paper, to facilitate the optimal balancing of this trade-off, we propose a new downlink transmission scheme suitable for THz communications, namely DFT-precoded OFDMA with variable number of DFT-precoding chunks, where a base station (BS) is able to opportunistically vary the number of chunks to generate a multiuser downlink transmit signal. For the proposed scheme, we provide solid analysis on the PAPR of BS transmit signal with respect to the number of chunks, which enables the optimal design of various downlink transmission scenarios by opportunistic control of the number of chunks according to the required level of PAPR and multiuser diversity. The proposed scheme and analysis provide useful insights in the optimal design of future wireless systems, especially in THz bands with limited PA efficiency.

Faster-Than-Nyquist (FTN) is a technique that can improve the spectral efficiency of communication systems by making better use of available spectrum resources at the cost of inter-symbol interference (ISI) and inter-carrier interference (ICI). In this paper, we propose a hybrid signaling scheme for a practical application of FTN for MIMO transmission. We propose a new slot structure optimized for the hybrid signaling supporting both FTN signaling and orthogonal frequency division multiplexing (OFDM) signaling. Specifically, in the proposed slot structure, data transmission is based on the FTN signaling and the pilot transmission is based on the OFDM signaling. Numerical results confirm that the proposed signaling scheme has clear benefit over the systems employing only OFDM or FTN signaling.

In this paper, a compressed sensing based channel acquisition is proposed for beyond 5G systems where the single carrier waveform is used over the millimeter wave spectrum. The key idea of the proposed technique, 2-dimensional compressed channel recovery (2D-CCR), is to estimate channel impulse response based on randomly selected time-domain pilot samples transmitted in a localized portion of the bandwidth. As a result of 2D-CCR, channel information of full bandwidth can be acquired from compressed sensing without having to take the measurement on the entire bandwidth. From the numerical evaluations, it is observed that the proposed scheme outperforms conventional channel estimation schemes in terms of estimation accuracy.

This paper studies a hybrid automatic repeat and request (HARQ) mechanism for multicast/broadcast services in 5G New Radio (NR) systems. HARQ is widely used in unicast transmission to improve reliability and resource efficiency under the fading channel. However, for multicast/broadcast, it is difficult to apply conventional HARQ technology because the probability of retransmission becomes high as the number of receiver increases. In this paper, we propose a novel and efficient retransmission scheme, called outer code- based HARQ. After the initial transmission of a given data packet for multicast/broadcast, each receiver sends feedback information on how many code blocks (CBs) are broken instead of which CBs are broken. Then, for retransmission of the data, the transmitter generates parity CBs by using outer code such as Reed- Solomon (RS) or Raptor code and transmits the parity CBs after applying inner code such as low density parity check (LDPC) code. Numerical results show that the proposed scheme outperforms the conventional HARQ schemes, reducing more than 50% of retransmissions.

Multidimensional characterization of outdoor urban macrocellular propagation channels is essential for the analysis and design of next-generation (5G and beyond) cellular massive MIMO (multiple-input-multiple-output) systems. Since most massive MIMO arrays will extend in two or three dimensions, an understanding of 3-D parameters (i.e., azimuth and elevation) of the multipath components (MPCs) is required. This paper presents an extensive measurement campaign for 3-D outdoor propagation channels in an urban macrocellular environment. Measurements were performed with a 20 MHz wideband polarimetric MIMO channel sounder centered at 2.53 GHz and MPCs were extracted using RIMAX-an iterative maximum likelihood algorithm. The physical propagation mechanisms of the observed discrete MPCs are explained in terms of waveguiding, over-the-rooftop propagation, and scattering by far-away objects. MPCs exhibit clustering in the temporal and spatial domains; both intra- and inter-cluster parameters and their relevant statistics are provided. We also extract diffuse MPCs, show that they can comprise a moderate portion of the overall energy, and provide a statistical characterization.

The 3-D multiple-input multiple-output (3-D MIMO) systems have received great interest recently because of the spatial diversity advantage and capability for full-dimensional beamforming, making them promising candidates for practical realization of massive MIMO. In this paper, we present a low-cost test equipment (channel sounder) and post-processing algorithms suitable for investigating the 3-D MIMO channels as well as the results from a measurement campaign for obtaining elevation and azimuth characteristics in an outdoor-to-indoor (O2I) environment. Due to limitations in available antenna switches, our channel sounder consists of a hybrid switched/virtual cylindrical array with effectively 480 antenna elements at the base station. The virtual setup increased the overall MIMO measurement duration, thereby introducing phase drift errors in the measurements. Using reference antenna measurements, we estimate and correct for the phase errors during post-processing. We provide the elevation and azimuth angular spreads for the measurements done in an urban macro-cellular and urban micro-cellular environments, and study their dependence on the user equipment (UE) height. Based on the measurements done with UE placed on different floors, we study the feasibility of separating users in the elevation domain. The measured channel impulse responses are also used to study the channel hardening aspects of the massive MIMO and the optimality of the maximum ratio combining receiver.

Device to device (D2D) communication techniques is one of main themes for the next generation wireless communication techniques. Compared to traditional Wireless Wide Area Network (WAN) communication where all radio links are formed between a user equipment (UE) and a base station (eNB), D2D communication uses a direct link between two different UEs. In the standard organization, 3rd Generation Partnership Project (3GPP), there is an ongoing discussion to adopt the D2D communication in current Long Term Evolution Advanced (LTE-A) system. The main target use cases of the D2D in LTE system comprise public safety using direct communication and commercial services using proximal device discovery. Introduction of the D2D discovery inside LTE-A network bring some impacts to existing cellular operation by the in-bane emission property. This paper provides a promising way to support D2D discovery in LTE-A system and analyze the in-band emission impact of D2D discovery on current LTE-A operation. In order to minimize the impact, an eNB based open loop power control algorithm is proposed for D2D discovery. To see the performance of the proposed scheme, system-level simulation results are provided. Our results show that eNB based open loop power control algorithm alleviate the in-band emission impact significantly.

There has been an increasing interest in Full- Dimension (FD) MIMO, i.e., exploiting the elevation domain (in addition to the azimuth domain) for increasing the capacity of multi-antenna systems. A first prerequisite for designing FD MIMO is an understanding of the elevation characteristics of wireless propagation channels, in particular elevation at the base station. This paper utilizes a state-of-art ray-tracing simulation software to investigate and quantify these elevation characteristics in urban macro cellular (UMa) environments. We study in detail the height and distance dependency of these channel parameters such as mean elevation angle and elevation spread. More importantly we find that several of these parameters exhibit markedly different characteristics depending on whether the UEs are close to exterior walls or they are deeper inside the buildings. Thus, the traditional method of "factoring" the propagation into an outdoor part and an indoor part is not applicable, and we propose more accurate fitting equations.

In this paper, an asymptotic distribution for the sum rate capacity is derived in zero-forcing beamforming (ZF-BF) based multiuser MIMO systems with a large number of base station (BS)antennas. By utilizing the characteristics of a large number of antennas and the central limit theorem, we prove that the asymptotic distribution for the sum rate capacity follows Gaussian distribution. Also we derive the mean and variance values for the asymptotic Gaussian distribution. Based on the asymptotic Gaussian distribution, we also obtain the outage probability for the sum rate capacity as a closed form. Simulation results show that the asymptotic Gaussian distribution is well follows the actual sum rate capacity, and the both asymptotic mean and variance value are also very accurate.

This paper analyzes the pilot power ratio (PPR) in multiuser multiple-input multiple-output (MU-MIMO) systems with a large number of receive antennas (M) at the base station (BS). We consider zero-forcing based MU-MIMO orthogonal frequency division multiplexing (OFDM) systems. Based on the deterministic uplink sum-rate approximation for imperfect channel state information, we can formulate the optimization problems in terms of the PPR to maximize the ergodic uplink sum-rate subject to the per-slot or per-symbol power constraint. Under the per-slot power constraint, the optimal PPR can be obtained in a closed form while under the per-symbol power constraint, we propose an iterative algorithm which generates a suboptimal PPR. Simulation results show that the proposed PPRs perform close to the optimal performance in terms of the sum-rate. Also, it is shown that the proposed PPRs outperform the equal power allocation. In particular, in the ZF-R based MU-MIMO OFDM system with 8 users and M=32 under the per-slot power constraint, the proposed PPR can achieve about 8bps/Hz performance gain compared to the equal power allocation.