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.

As the pace of global 5G network deployments accelerates, the telecommunications industry strives to move from a conventional vertical stack, closed, hardware-based ecosystem to an open, interoperable, modular, cloud-based ecosystem that leverages software-based implementations of various network entities – including core network functions and base stations. Such an open ecosystem could facilitate the implementation of AI techniques and could be a critical advancement in realizing the vision of “zero-touch” wireless networks that support end-to-end automation– stretching from the core network to end-user devices. In this paper, we provide an overview of ongoing discussions along these lines in the context of the O-RAN Alliance along with a comprehensive discussion on various challenges. We then briefly present our vision of the evolution of intelligent networks beyond current 4G/5G networks.

Current trends in spectrum regulation show that more and more unlicensed and shared spectrum bands are poised to be opened up for mobile communication. However, the question remains how to best utilize this spectrum and build efficient networks, and if the time has come for newer approaches to be considered for the next generation system. In this work, we propose a coordinated shared spectrum framework that can be considered for next generation cellular standardization. In designing the framework, we aim to improve on the current unlicensed access schemes toward increasing spectral efficiency in highly- dense networks. To this end, we demonstrate that with the proposed framework both throughput and access delay can be significantly improved over the state-of-the-art LAA system. We also show that large statistical multiplexing gains are possible through dynamic sharing instead of static, hard splitting of shared spectrum, as in the current CBRS system.

In this work, we consider the problem of distributed link scheduling for D2D communications without a centralized controller. Our design goal is to maximize a chosen global objective function. For example, maximizing the long-term proportional fair throughput amongst distributed links can be such a goal. In principle, each link evaluates whether its rate increase by raising its transmit power is sufficient enough to compensate others' rate decrease due to increased interference power towards the objective function maximization. To this end, an iterative distributed power control algorithm, called PowerD2D, and supporting frame structure and signaling method are proposed. As a result of link scheduling via PowerD2D, some links are completely turned off by setting their transmit power to zero and some scheduled links are assigned non-negative transmit power, which are all set for optimality. In addition to its superior performance, PowerD2D algorithm is also flexible enough to enforce any level of fairness amongst links in a distributed manner.

In this work, we consider the device-to-device (D2D) communications underlaying cellular networks to support local communication needs. In particular, we focus our attention on the design of an optimal resource allocation and mode selection algorithm for both cellular and D2D users. In the design, communication mode selection for D2D users is also taken into account so that a D2D source-destination pair has an option to either directly communicate or indirectly communicate through the base station (BS). On the other hand, it is necessary and important to provide a certain level of Quality of Service (QoS) to users. The users can be further differentiated by assigning different weighting factors and QoS requirements. To this end, we formulate a problem of maximizing the weighed sum rate of all the users constrained by their power and QoS requirements. The tool that we use to handle this problem is the primal-dual technique which transforms the original problem into the equivalent problem showing lower computational complexity. The simulation results verify that our proposed scheme outperforms the previous heuristic scheme by jointly optimizing the power and resource allocation along with the communication mode selection for the D2D communication pairs.

We consider the problem of resource sharing in Device-to-Device (D2D) communication underlaying cellular networks. The problem is formulated as a non-cooperative game in which mobile users, either legacy cellular users or D2D users, decide their respective transmission power over available resource blocks (RBs) with the goal of maximizing their own utility function. The key factor that distinguishes our work from the existing literature is the design of the utility function; the utility function of each user is defined as the achievable rate normalized by the power consumption, which is in [bits/sec/Joule]. Such a utility function well reflects the users' satisfaction in reality when users are mobile and subject to the availability of energy due to the finite battery capacity and limited recharging facility. The scenario where the cellular and the D2D connections share the same resources is considered, in which the interference management between cellular and D2D communications is of great importance to guarantee the performance of high-priority cellular users. The most energy efficient strategy turns out that a DUE allocates the least amount of power on the channel with the best channel gain-to-interference-plus-noise-ratio (CINR) yet still achieves the highest data rate on that channel while a CUE allocates the optimal power on its assigned channel to reach the maximum energy efficiency.

In this paper, we consider random access by nodes that have energy harvesting capability. Each node is equipped with both a queue for storing the arriving packets and a battery for storing the harvested energy chunks, where the packet arrival and the energy harvesting events are all modeled as discrete-time stochastic processes. In each time slot, each node attempts to transmit the head-of-the-line packet in the queue with some probability if its battery is non-empty, and each transmission consumes one chunk of energy. Therefore, the transmission by one node is not just limited by the availability of packets in the queue but also by the availability of energy chunks in the battery. In most of related previous work, it was implicitly assumed that there exists unlimited energy for transmission, which is impractical in many distributed systems. In this work, we characterize the exact stability region when a pair of bursty nodes, which are harvesting energy from the environment, are randomly accessing a common receiver. The analysis takes into account the compound effects of multi-packet reception capability at the receiver. The contributions in the paper are twofold. First, we accurately assess the effect of limited, but renewable, energy availability due to harvesting on the stability region by comparing against the case of having unlimited energy. Second, the impact of the finite capacity batteries on the achieved stability region is also quantified.

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.

In this paper, we study the stability property of a cognitive radio system comprised of a set of source-destination pairs having different priorities. In particular, we focus attention on the effect of imperfect sensing on the stability region of the system, which has been overlooked in most of related previous work. The adopted cognitive access protocol allows the secondary user not only to exploit the idle slots of the primary user but also to transmit along with the primary user with some probability. This is aimed at achieving the full utilization of the shared channel with capture, i.e., a transmission can be correctly decoded at the destination, even in the presence of other transmissions, if the received signal-to-interference-plus-noise ratio (SINR) exceeds a certain threshold for successful decoding. The abolition of strong primacy, however, requires the secondary user to properly regulate its multi-access probability in order not to impede the primary user's stability guarantee. To this end, the maximum stability region of the system is characterized which describes the theoretical limit on rates that can be pushed into the system while maintaining the queues stable. Interestingly, we found that even with non-zero sensing error rates, there exists a condition for which we can achieve the identical stability region that is achieved with perfect sensing. This is when the destinations enjoy fairly strong capture, and if then sensing errors do not affect the stability region for the queueing system. For the case when the specified condition does not hold, we precisely quantify the loss due to the imperfect sensing in terms of the size of the stability region. Finally, we study the problem of controlling the operating point of the sensing device over its receiver operating characteristic (ROC) and summarize some key aspects observed in the control.

In this work, we consider a hybrid of interweave and underlay modes of operation for cognitive radio systems with random connectivity and bursty packet arrivals. Under the designed hybrid access policy, the secondary communication system is allowed to operate in the interweave mode only when its transmission has no harm on the primary communication. This is when the primary communication system is idle or the interference link from the secondary source to the primary destination is disconnected. The secondary communication system can optionally operate in the underlay mode, although when it is inevitable to interfere with the primary communication. The underlay mode is activated with some probability, called the hybrid rate. We analyze the stability of the hybrid access policy and show that it is not always beneficial when compared against the interweave-only mode. Thus, the condition for which the hybrid access policy can outperform is specified.

In this work, we consider a system with time-varying channels and random access that exploits the channel state information (CSI). The CSI is not directly available to each node but estimated with some errors. An exact stability analysis is carried out for the considered model when a pair of bursty sources are competing for a shared channel and the receiver has multipacket reception capability. The contributions in the paper are twofold: first, we identify the effect of channel estimation errors on the achievable stability region of the channel-aware random access protocol. Secondly, we make a comparison with the class of stationary scheduling policies.

In this paper, we evaluate the benefits of using one user of a two-user random access system to relay traffic of the other user.

In this paper, we consider the random access of nodes having energy harvesting capability and a battery to store the harvested energy. Each node attempts to transmit the head-of-line packet in the queue if its battery is nonempty. The packet and energy arrivals into the queue and the battery are all modeled as a discrete-time stochastic process. The main contribution of this paper is the exact characterization of the stability region of the packet queues given energy harvesting rates for the two-node slotted ALOHA system. By stability, we refer the ability of a system to keep the queues in a bounded region, or more precisely, the existence of the limiting distribution for the joint queue length process. The analysis is non-trivial even for the two-node case because it involves the interaction between nodes of having both the packet queue and the battery. The result is obtained for both scenarios in which the capacity of batteries is infinite and also finite.

This paper considers the scenario in which a set of nodes share a common channel. Some nodes have a rechargeable battery and the others are plugged to a reliable power supply and, thus, have no energy limitations. We consider two source-destination pairs and apply the concept of cognitive radio communication in sharing the common channel. Specifically, we give high-priority to the energy-constrained source-destination pair, i.e., primary pair, and low-priority to the pair which is free from such constraint, i.e., secondary pair. In contrast to the traditional notion of cognitive radio, in which the secondary transmitter is required to relinquish the channel as soon as the primary is detected, the secondary transmitter not only utilizes the idle slots of primary pair but also transmits along with the primary transmitter with probability p. This is possible because we consider the general multipacket reception model. Given the requirement on the primary pair's throughput, the probability p is chosen to maximize the secondary pair's throughput. To this end, we obtain two-dimensional maximum stable throughput region which describes the theoretical limit on rates that we can push into the network while maintaining the queues in the network to be stable. The result is obtained for both cases in which the capacity of the battery at the primary node is infinite and also finite.

In this paper, we consider the backpressure-based control for wireless multihop networks with time-correlated arrivals. The arrival process considered in this work is fairly general in the sense that it may exhibit long-range dependence depending on the asymptotic shape of the autocorrelation function. We first show that the original backpressure policy is still throughput-optimal even with correlated arrivals if the autocorrelation functions are monotonically decreasing. The resulting upper bound on average network delay is expressed in terms of the autocorrelation parameters. After that, we extend our model to include the case where the arrival rate vector is possibly outside the stability region and take the method of joint flow control and backpressure policy that is known to perform arbitrarily close to the utility-optimal throughput point with a corresponding tradeoff in average network delay. The effect of correlated arrivals appears again in the tradeoff in terms of the autocorrelation parameters.

The introduction of relays into legacy cellular networks is gaining more of an interest in the 4th generation (4G) wireless systems. In the presence of relays, simultaneous transmission of both base stations (BS) and relay stations (RS) on the same resources is possible, and consequently much higher throughput can be achieved. However, determining the set of links which will be turned on at the same time is usually considered a NP-complete combinatorial problem. Moreover, it requires cooperation between BSs and RSs of independent cells. In such context, we briefly address the difficulties of spatial resource reuse from the graph-theoretical perspective. Next, our focus shifts to developing a simple but efficient radio resource management algorithm which enables the spatial resource reuse, the pricing- based radio resource management (PRRM) strategy. The PRRM performs spatial reuse for interference-free users operating in the high signal-to-interference-and-noise ratio (SINR) region, while guaranteeing the signal quality of interference-susceptible users usually located near the coverage boundary. By applying the PRRM, we evaluate the potential benefits of the spatial resource reuse.

Most of up-to-date wireless data systems are based on the OFDM technology and employ the opportunistic scheduling to exploit channel itself fully. Thus, feedback reduction in multiuser multi-carrier systems becomes more of an issue due to the large amount of feedback required to pass to the base station. In this paper, we propose a novel feedback reduction scheme preserving the essential of multi-user diversity. In our proposed scheme, active users determine their feedback amount based on the feedback efficiency factor in a distributed manner. The objective is to reduce the feedback load remarkably while achieving almost the same performance to the full feedback condition. Our proposed scheme offers several advantages over existing ones. First, it does not distort the property of the scheduling policies. Second, total feedback load can be explicitly controlled to a target level regardless of the number of users in a system by adjusting each user's feedback load adaptively.