Channel state information (CSI) feedback enhancement based on artificial intelligence (AI)/machine learning (ML) has been widely studied in the recent years, and has been selected as one of three physical layer AI/ML use cases in 3GPP Release 18 [1]. Despite their success of achieving a better trade-off between feedback accuracy and feedback payload size, most of the current solutions lack the flexibility to adjust to feedback payload size. For different feedback payload sizes, separate ML models are trained and utilized, resulting in a linear increase of the number of ML models with respect to the number of feedback payload sizes. It can be problematic for real-world deployment, since one ML model usually has hundreds of thousands or even millions of parameters. In this paper, we build an ML model where the majority of model parameters are shared, while the normalization layer is switched according to feedback payload size. The feasibility and effectiveness of switchable normalization layer is verified through numerical simulations, where an autoencoder (AE) is leveraged for CSI feedback and both convolutional neural network (CNN) and transformer based AE are considered. Results show that switchable normalization layer can adapt to various quantization bit-widths as well as various encoder output widths, achieving similar or sometimes even better performance than having separate AEs. Furthermore, by re-using most of the model parameters, the increase in model size is negligible.

Lower THz frequency in the range 100–300 GHz is an attractive candidate for the 6G communication system thanks to the large available bandwidth. To conduct system design from early on, there is a need to have a channel model for this frequency range. This paper presents a comprehensive channel parameters set for the 3GPP channel model in the frequency range 100–300 GHz. The channel parameters have been extracted from the measurement and ray tracing simulation data available in the literature. Insights into the specific behavior of the parameters have been provided as well. Additionally, a link budget analysis is provided to show the impact of the channel parameters on the 6G system design. The results show that 10–100 Gbps rates are achievable in the indoor scenario with the available bandwidth in the lower THz frequency.

The abundant spectrum in millimeter wave (mmWave) bands provides an opportunity for fifth generation (5G) cellular communication systems to enhance their mobile broadband services. mmWave communication is therefore considered as one of the key features of 5G cellular radio access network (RAN). However, the deployment of mmWave cellular RAN faces challenges due to mmWave radio propagation characteristics such as pathloss, blockage and penetration loss. In this paper, we investigate the performance of mmWave cellular RAN using system level simulations based on the 3GPP evaluation methodology and applying techniques such as cell densification, wireless backhaul, and sub-6 GHz and mmWave dual access.

Analog/digital/hybrid beamformer/receiver designs for mmWave communication have attracted great research attentions including directional of arrival (DOA) estimation. Traditional investigation of smart antennas for wireless communications has primarily focused on uniform linear array (ULA) antennas and there are little attention and literature on other smart antennas array topologies. Those DOA estimation algorithms designed for ULA (with received signal as a vector) can not immediately be applied for uniform planar array (UPA) structure (with received signal as a matrix). In this work, start with UPA DOA estimation system model, we process the received matrix through a simple vectorization process to construct a received vector. With theoretical proof of the vectorization process equivalence, conventional DOA estimation based on ULA can easily be applied to UPA structure. We apply several DOA estimation algorithms to UPA for one DOA arriving signal or multiple DOA arriving signals, with both perfect known autocorrelation matrix and estimated autocorrelation matrix through sample averaging, and demonstrate the effectiveness of our proposed DOA estimation process for UPA.

In millimeter wave (mmWave) communications with possible gigabit-per-second data rate, the severe path loss can effectively be alleviated by adaptive beamforming using antenna arrays. However, this complicates the initial access (IA), by which a mobile user equipment (UE) establishes a physical link connection with a mmWave base station (BS). The total duration of IA directional search can be very long since multiple preambles should be repeatedly transmitted for all transmit and receive beam pairs. In this work, we focus on IA techniques based on analog beamforming with uniform planar array antennas without context information from microwave BSs. We revisit current techniques of exhaustive search and iterative search based on BS training, and propose a novel hybrid training method, where in the first stage BS performs wide beam search, and in the second stage, the UE will perform reverse training according to the best wide beam decided in the first stage. For the three IA techniques, we derive the total consumed time slots and the received SNR expressions in each stage. Through simulations and comparisons, we demonstrate that the proposed hybrid training method shortens the searching delay and gives the same access error probability as iterative search.

Next-generation wireless communications systems are expected to exploit frequency bands above 6 GHz. An important transition towards such bands will be design of channel models capable of supporting the design of efficient air-interface and networks. In this paper, we describe a geometry-based statistical channel model and apply ray-tracing simulation for its validation. Focusing on path loss and root-mean-square (RMS) delay spread as metrics, we show that the proposed modeling approach is flexible and realistic.

ABSTRACT Because of the inevitable trend of green networking, energy efficiency (EE) is quickly becoming one of the key performance metrics to evaluate wireless communication systems, together with spectrum efficiency (SE) and quality of service (QoS) that have been traditionally used. This paper studies the fundamental tradeoff between EE and SE in the presence of statistical QoS requirements in wireless transmission systems. Earlier studies have shown that the performance with QoS requirements in the wireless transmission can be measured through effective capacity, which can capture the physical layer fading channel characteristics in the link layer QoS requirements, such as delay and data rate. Under this context, SE is defined as effective capacity per unit frequency bandwidth, and EE is defined as energy consumed per effective capacity bit. Both circuit power and transmission power are considered in the energy model, based on which we derive the quasi‐convex generalized EE formulation. To exploit the tradeoff between EE and SE with QoS considerations, we propose a generic close‐form approximation for EE–SE formulation by employing a curve fitting approach. The impacts of QoS and circuit power consumption on EE–SE tradeoff are respectively analyzed. QoS requirement and circuit power consumption affect the EE–SE tradeoff differently. In the low‐SNR regime, circuit power shows more impact on the EE–SE tradeoff, whereas QoS impacts EE–SE tradeoff more in the high‐SNR regime. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, we consider the operation of the Long Term Evolution (LTE) systems in the unlicensed spectrum. Given the lack of the exclusive use of the spectrum, the operation in the unlicensed band is fundamentally limited by interference from other technologies using the same frequency band. By noting that the unlicensed spectrum is heavily used by Wireless Local Area Networks (WLAN), here we focus on the mutual effect between LTE and WLAN when they coexist. For this, we developed a novel inter-system interference analysis technique based on the continuum field approximation and spiral representation, which improves the accuracy of the previous approaches and is applicable to both large-scale and small-scale networks. To this end, we quantify the effect of inter-system interference when the LTE and WLAN systems operate in the same unlicensed spectrum.

Device-to-device (D2D) communication underlaying a cellular network is a promising technology in the future wireless networks to improve network capacity and user experience. In current works, D2D communications are considered as two user equipments (UEs) communicating directly without going through the central base station (BS). In fact, D2D communications can be further broadened to multi-hop D2D communications in which a UE may help other UEs communicate with each other, or assist other UEs to communicate with BS. In this paper, we investigate a scenario of multi-hop D2D communications where one UE may help other two UEs to exchange information, by utilizing analog network coding technique. We analyze the energy-efficiency of this multi-hop D2D communication, derive the average energy-efficiency under Rayleigh fading channels, and compare with direct one-hop D2D communication and traditional cellular communication through BSs.

As radio interface approaches its practical capacity limit given limited spectrum resource, network architecture innovation/revolution would play a key role in boosting wireless communication system capacity and improving user experience. Deploying dense small cell networks overlaying the conventional macro cell networks is widely regarded as a key step towards network architecture revolution for improved spectrum and energy efficiency. In this paper, we analytically investigate the spectrum efficiency of densely deployed small cell networks in the downlink using tools from stochastic geometry. Unlike the conventional user-centric link-level spectrum efficiency analysis, we analyze network spectrum efficiency, defined as the average aggregate spectrum efficiency per cell. As the portion of cell-edge users, who would consume more spectrum resource in achieving a target rate, usually outweighs that of the cell-center users, network spectrum efficiency evaluation should count user distribution to portray the network performance as a whole. Based on the network spectrum efficiency results, we are able to find the optimal cell density and the corresponding optimal base station transmit power for achieving a high spectrum efficiency and/or energy efficiency.

This paper investigates the energy efficiency in a wireless channel with delay requirement. We address the energy efficiency transmission by considering both transmission power and circuit power consumptions based on the effective capacity approach. Effective capacity has been widely used to incorporate QoS requirements in the wireless communication and is an effective approach to modeling the physical layer wireless fading channel with the link layer parameters. We first derive the quasi-convex generalized form of energy efficiency formulation based on effective capacity under delay constraints. The general expression can be applied to various fading scenarios. We further develop a two-step binary search algorithm to find the best energy efficiency and the corresponding optimal transmission signal-to-noise ratio (SNR). The numerical results show that both the circuit power and queuing delay requirement have a big impact on the overall wireless channel energy efficiency.

Wireless heterogeneous networks have emerged as a new paradigm to meet the fast increasing wireless capacity and coverage demands. Coordinated Multipoint Processing (CoMP) and Precoding are two promising techniques to further improve the network capacity and spectral efficiency. This paper presents an optimal intra-cell CoMP resource allocation scheme in a wireless heterogeneous network and explores the Tomlinson-Harashima Precoding (THP) in the physical layer to reduce the inter-user interference. The objective is to maximize the aggregate proportional rates in the system. We derive an asymptotically optimal solution for resource allocation by using a gradient descent based scheduling and KKT conditions for optimality. Simulation results demonstrate the system proportional fairness capacity gain of proposed resource allocation scheme and this resource management framework provides a guideline for future radio resource management in wireless heterogeneous networks.

Heterogeneous wireless networks have emerged as a new paradigm to meet the fast growing wireless network capacity and coverage demands. Due to the co-deployment of high power and low power nodes in the same network using the same spectrum, more advanced interference coordination and radio resource management schemes are required than in the traditional cellular network in order to achieve a high network capacity and good user experience. In this paper, we propose an optimal fractional frequency reuse and power control scheme that can effectively coordinate the interference among high power and low power nodes. The scheme can be optimized to maximize the sum of the long term log-scale throughput among all the user equipments (UEs). Towards that end, the Lagrange dual function is first derived for the proposed optimization problem. Gradient descent method is then used to search the optimal solution for the convex dual problem. Due to the strong duality condition, the optimal solution for the dual problem is also the optimal solution for the primal problem. Simulation results show that the proposed scheme can greatly improve the wireless heterogeneous network performance on system capacity and user experience.

As a key technology in 4G-LTE, heterogeneous networks can effectively extend the coverage and capacity of wireless networks by deploying multiple micro-nodes on top of the conventional macro base stations (BS). The deployed micro-nodes differ in transmission power and processing capabilities, leading to new challenges in interference management, mobile association, and radio resource management (RRM). In this paper, we consider RRM for heterogeneous networks with relays (RN) where the RNs have full RRM capabilities and can be viewed as micro BSs. A radio resource allocation framework is proposed with the objective to ensure proportional fairness among the UEs. An asymptotically optimal solution is derived by applying the gradient-based scheduling scheme and the Karush-Kuhn-Tucker (KKT) conditions for optimality. To implement RRM in networks with RNs, the resource consumption in the backhaul links, which depends on the demand of the UEs associated with the RN, should be counted at both the BS and the RN. The derived resource allocation scheme gives insight on the optimal radio resource allocation for heterogeneous networks with RNs.

Heterogeneous networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low-power nodes on top of the conventional network nodes. In this paper, we consider a heterogeneous cellular network with multiple low-power relay nodes (RN) deployed in each cell using in-band wireless backhaul between the RN and the base stations (BS). The RNs work cooperatively with the BSs on the downlink communication towards the user equipments (UE). Due to the disparity between the transmit powers of the BSs and the RNs, mobile association schemes developed for the conventional homogeneous networks may lead to a highly unbalanced traffic loading with most of the traffic being concentrated on the BSs. In this paper, we propose a new mobile association framework for the heterogeneous wireless networks with intra-cell node cooperations. The proposed framework aims to maximize the network capacity and balance the traffic load among the network nodes. Furthermore, we introduce a pricing mechanism to enable the distributed implementation of the proposed scheme. Numerical results show that a prominent improvement in network capacity can be achieved by the proposed pricing-based mobile association scheme.

This paper considers a cellular network with multiple low-power relay nodes (RN) deployed in each cell, helping the downlink transmission between the base stations (BS) and the user equipments (UE). The difference in transmission power between the BSs and the RNs makes this network heterogeneous. With conventional mobile association schemes, traffic load may concentrate on the BSs due to their high transmit power, leading to a highly unbalanced traffic load distribution and inefficient utilization of the RNs. To improve the capacity and the overall spectrum efficiency of the network, it is beneficial to let the RNs share a larger amount of the traffic burden. Towards this end, in associating the UEs to the RNs, the spectrum consumption on both UE to RN and RN to BS links should be cautiously considered. Also the interference from the high power BSs to the low power RNs need to be carefully mitigated. A systematic mobile association scheme considering load-balancing and overall spectrum efficiency is essential to ensure a fair and efficient usage of network resources. In this paper, we propose a load-balancing based mobile association framework under both full frequency reuse and partial frequency reuse and find the pseudo-optimal solutions using gradient descent method. By comparing with other mobile association schemes, a significant improvement in overall network capacity and RN utilization can be observed for the proposed mobile association framework. To enable dynamic and timely mobile association for the incoming UEs, we also develop an online mobile association algorithm based on the gradient descent method. Simulation results show that the proposed online algorithm achieves a good tradeoff between association delay and network capacity.

Interference forwarding in an interference channel makes the interference stronger which in turn enables the usage of simple detectors like the successive interference canceler (SIC) at the destinations. In this paper, detect and forward (DF), amplify and forward (AF) based interference forwarding protocols (also called as AF-SIC and DF-SIC protocols) are analyzed. Symbol error rate (SER) performance of the SIC, AF-SIC and DF-SIC protocols using M-PAM modulation is studied. Also the relay channel gains required to restore full diversity for the AF-SIC and the DF-SIC protocols are obtained. Impact of the relay power and relay location on the SER performance is also studied. The proposed protocols are proved to provide the same SER performance as the orthogonal transmission scheme while improving the spectral efficiency.

In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of a multiple-input-multiple-output (MIMO) full-duplex single-user multihop relay channel, where a pair of source and destination communicates via multiple layers of relays. All communication terminals could be equipped with multiple antennas. The relays operate in a full-duplex mode. By incorporating time-domain linear transformation into amplify-and-forward (AF) based relaying, we propose an AF-based space-time relay scheme and show that the DMT upper bound of the channel can be achieved by properly designing space-time (ST) codes at the source.

In this paper, diversity-multiplexing tradeoff (DMT) of the delay-limited symmetric two-user single-antenna fading interference channel (IFC) with source cooperation is evaluated under both full-duplex and half-duplex cooperation constraints. The interference signal and the desired signal received by each destination node are assumed to be of comparable strength. Under each cooperation constraint, DMT upper and lower bounds are derived and shown to be tight, i.e., the lower bound meets the upper bound. A full characterization of the DMT of the channel is thus established. The upper bounds are evaluated using the capacity upper bounds and the lower bounds are obtained based on our proposed transmission schemes. The proposed transmission schemes only require partial channel state information at transmitter side (CSIT), making them suitable for practical applications. Specifically, for the transmission scheme designed under the full-duplex constraint, the partial CSIT is obtained by letting each destination represent the fading magnitude of each of its incoming links using 1 bit of information and feed back this information to the sources. In the half-duplex case, the proposed transmission scheme requires no more than 3 bits of feedback information to represent the fading magnitude of each link. Our DMT results show that source cooperation can notably improve the system diversity performance over the whole multiplexing gain region even under the half-duplex constraint.

As one of the key technologies for future wireless communication systems, user cooperation has a great potential in improving the system performance. In this paper, the diversity benefit of user cooperation is evaluated using diversity-multiplexing tradeoff (DMT) as the performance metric. Ways of exploiting the diversity benefit are devised. We investigate two typical channel models, namely, the multiple-access channel (MAC) and the interference channel (IFC). For the MAC, all the terminals are equipped with multiple antennas and theK(K≥ 2) sources cooperate in a full-duplex mode. We determine the optimal DMT of the channel and propose a compressed-and-forward (CF) based cooperation scheme to achieve the optimal DMT. For the IFC, we consider a two-user channel with single-antenna terminals and full-duplex source cooperation. A DMT upper bound and two DMT lower bounds are derived. The upper bound is derived based on a channel capacity upper bound, and the lower bounds are derived using decode-and-forward (DF) based cooperation schemes. In most channel scenarios, the bounds are found to be tight. This implies that under certain channel scenarios, the optimal DMT of the channel can be achieved by DF-based cooperation schemes.

In this paper, we propose a transmission scheme for the two-user symmetric multiple antenna interference channel (IFC) and show that the proposed transmission scheme can achieve the optimal diversity-multiplexing tradeoff (DMT) of the channel. The proposed transmission scheme requires only limited channel state information at the transmitter (CSIT) and is suitable for practical implementation. The limited CSIT is obtained by letting the destinations quantize the required information and feed back to the sources. Rules for implementing the quantization are proposed and the number of bits needed to represent the quantization is calculated. It is shown that for the proposed transmission scheme to be DMT optimal, the number of feedback bits should increase in log scale with respect to signal-to-noise ratio.

In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of the delay-limited symmetric two-user fading interference channel (IFC) with full-duplex source cooperation. Upper and lower bounds on the channel DMT are derived and shown to be tight, i.e., the lower bound meets the upper bound. The DMT behavior of the channel is thus fully determined. The upper bound is derived based on a channel capacity upper bound. The lower bound is derived based on a proposed transmission scheme which requires only limited CSIT obtained from destination feedback. Specifically, the magnitude of each of the fading links is represented by the destinations using one bit of information and fed back to the sources. The DMT result shows that source cooperation can notably improve the system diversity performance over the whole multiplexing rate region.

In this paper, we propose a noncoherent space-frequency (SF) code for multiple-input-multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems for broadband wireless communications. The proposed noncoherent SF code matrix is constructed as a combination of a noncoherent SF code matrix and a differential modulation matrix. Comparing to noncoherent SF codes and differential SF codes in the literature, the advantages of our proposed code are higher spectrum efficiency, no error floor and more suitable for broadband communication systems. Taking advantage of the codeword structure of the proposed SF code, we devise a two-stage decoding scheme, in which the decoding process is implemented in two steps by decoding the component noncoherent codeword matrix and the component differential codeword matrix sequentially. Accordingly, the decoding scheme efficiently reduces decoding complexity. Simulation results show that our proposed scheme with two-stage decoding yields better performance than the noncoherent SF codes and frequency-domain differential codes proposed in the literature.

In this paper, we focus on noncoherent space-frequency (SF) coded multiple-input-multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) systems. Based on OFDM subcarrier grouping, a group-based unitary space- frequency code is proposed and the effect of grouping on system performance is studied. Comparing to the coding scheme without grouping, which implements SF coding among all the OFDM tones, the proposed group-based coding scheme can greatly reduce the decoding complexity, making the noncoherent SF codes more applicable to practical use. By relating the noncoherent SF codes with packings in Grassmann manifold, we propose an efficient decoding method by restricting the implementation of decoding within a subset of the codebook. Numerical results are presented to demonstrate and verify our proposals.