This paper presents a grazing angle dependent outdoor-to-indoor (O2I) path loss model at 10.1 GHz for a glass and a concrete wall. The COST 231 O2I path loss model is used as a baseline in model creation. The parameters for the model are derived from radio channel measurements performed with a vector network analyzer and a single-input single-output antenna configuration at 500 MHz bandwidth. The results indicate that attenuation through the concrete wall is heavily dependent on the wall material whereas the attenuation through the window is on the same level as in the lower frequencies.
The parallel interference cancellation (PIC) principle is a conceptually simple and yet effective method of parameter estimation and data detection in the presence of multiple-access and multipath interference. It unifies some of the known methods of data detection, complex channel coefficient estimation, as well as delay tracking in DS-CDMA receivers. The PIC method will be derived and some numerical results for data detection, channel coefficient estimation and delay tracking will be presented.
Effective capacity (EC) determines the maximum communication rate subject to a particular delay constraint. In this paper, we analyze the EC of ultra reliable machine type communication networks operating in the finite blocklength regime. First, we present a closed form approximation for EC in quasi-static Rayleigh fading channels. Our analysis determines the upper bounds for EC and delay constraint when varying transmission power. Finally, we characterize the power-delay tradeoff for fixed EC and propose an optimum power allocation scheme which exploits the asymptotic behavior of EC in the high SNR regime. The results illustrate that the proposed scheme provides significant power saving with a negligible loss in EC.
The 3rd generation cellular communications standard will be based on wideband CDMA (WCDMA). To obtain adequate performance multiuser receivers, such as LMMSE receivers, can be used. Unfortunately, previously suggested LMMSE receivers cannot be applied in WCDMA systems employing long scrambling codes. In this paper, linear receivers suitable also for downlink with long scrambling codes are studied. These receivers equalize the channel prior to the despreading, thus restoring the orthogonality of users and suppressing multiple access interference (MAI). The numerical results show that chip equalizer based receivers can offer significant performance improvement in comparison to the conventional RAKE receiver.
Unmanned aerial vehicles (UAVs) are becoming increasingly attractive for the ambitious expectations for 5G and beyond networks due to their several benefits. Indeed, UAV-assisted communications introduce a new range of challenges and opportunities regarding the security of these networks. Thus, in this paper we explore the opportunities that UAVs can provide for physical layer security solutions. Particularly, we analyse the secrecy performance of a ground wireless communication network assisted by N friendly UAV jammers in the presence of an eavesdropper. To tackle the secrecy performance of this system, we introduce a new area-based metric, the weighted secrecy coverage (WSC), that measures the improvement on the secrecy performance of a system over a certain physical area given by the introduction of friendly jamming. Herein, the optimal 3D positioning of the UAVs and the power allocation is addressed in order to maximise the WSC. For that purpose, we provide a reinforcement learning-based solution by modelling the positioning problem as a multi-armed bandit problem over three positioning variables for the UAVs: angle, height and orbit radius. Our results show that the proposed algorithm improves the secrecy of the system over time in terms of the WSC, and it converges into a stable state close to the exhaustive search solution for discretised actions, where there is a trade-off between expediency of the positioning of the UAVs to positions of better secrecy outcome and energy consumption.
While multiuser receivers for code-division multiple-access (CDMA) systems have been extensively developed in the past, there performance in fading channels with practical delay and channel estimation has gained very little attention. Thus, the performance of the hard-decision parallel interference cancellation (HD-PIC) multiuser receiver in frequency selective fading channels is studied in this paper. A practical complex channel gain and delay estimation are applied. The results show that the performance of the PIC receiver is robust to the delay estimation. The performance of the PIC receiver in channel coded CDMA systems is also studied. A singleuser as well as a simple multiuser joint decoding (JD) are compared. Partial interference cancellation (PC) in conjunction with joint decoding is also studied. The results show that the PIC clearly outperforms the RAKE receiver both in terms of receiver performance and system capacity. The joint decoding in conjunction with a PIC receiver ca...
In virtualized radio access network (vRAN), the base station (BS) functions are decomposed into virtualized components that can be hosted at the centralized unit or distributed units through functional splits. Such flexibility has many benefits; however, it also requires solving the problem of finding the optimal splits of functions of the BSs in such a way that minimizes the total network cost. The underlying vRAN system is complex and precise modelling of it is not trivial. Formulating the functional split problem to minimize the cost results in a combinatorial problem that is provably NP-hard, and solving it is computationally expensive. In this paper, a constrained deep reinforcement learning (RL) approach is proposed to solve the problem with minimal assumptions about the underlying system. Since in deep RL, the action selection is the outcome of inference of a neural network, it can be done in real-time while training to update the neural networks can be done in the background. However, since the problem is combinatorial, even for a small number of functions, the action space of the RL problem becomes large. Therefore, to deal with such a large action space, a chain rule-based stochastic policy is exploited in which a long short-term memory (LSTM) network-based sequence-to-sequence model is applied to estimate the policy that is selecting the functional split actions. However, the utilized policy is still limited to an unconstrained problem, and each split decision is bounded by vRAN's constraint requirements. Hence, a constrained policy gradient method is leveraged to train and guide the policy toward constraint satisfaction. Further, a search strategy by greedy decoding or temperature sampling is utilized to improve the optimality performance at the test time. Simulations are performed to evaluate the performance of the proposed solution using synthetic and real network datasets.
5G emerges with ultra-dense deployments of small cell networks to address the location specific service demand of various vertical sectors. While the development of technical solutions for network densification is progressing, less attention has been paid to local operator models and location specific service offerings. Efficient local service delivery promoting innovation and competition calls for opening of the mobile market for new entrants to operate local radio access networks (RAN) and 3rd parties to integrate their services into the networks. This paper applies the recently proposed micro operator concept to local ultra-dense networks where different stakeholders can become micro operators and deploy their small cell RAN for tailored service delivery. We depict the resulting high-level architecture and enabling techniques focusing on network slicing and spectrum micro licensing. While network slicing is well addressed in 5G research from the mobile network operator (MNO) view for providing an end-to-end connection for 3rd parties, there is little work on how the ultra-dense small cell RAN could be operated by another stakeholder. Micro operators could offer the RAN or end-to-end network slice that comprises of network elements belonging to different stakeholders with the help of local spectrum micro licensing with quality guarantees.
Carrier frequency, carrier phase, multipath profile, delay values as well as fading characteristics are important for coherent detection. Several DS-CDMA receivers have been investigated, but mainly with the assumption of perfect estimation of those parameters. This paper deals with the impact of channel phase and path delay estimation errors to the performance of pre and post-combining blind adaptive linear minimum mean square error (LMMSE) receivers. Comparisons are made also with the conventional RAKE receiver. The results show that channel phase estimation errors degrade almost equally the performance of blind adaptive LMMSE and RAKE receivers. Delay estimation errors by over 20% of chip time cause the loss of advantages of LMMSE detection.
