Cell search is the process for a user to detect its neighboring base stations (BSs) and make a cell selection decision. Due to the importance of beamforming in 5G cellular networks including both the millimeter wave and sub-6 GHz networks, there is a need for a better understanding of the directional cell search delay performance. A cellular network with fixed BS and user locations is considered, so as to take into account the strong temporal correlations that exist for the SINR experienced by each BS and user in this context. For Poisson cellular networks with Rayleigh fading channels, a closed-form expression for the spatially averaged mean cell search delay of all users is derived. This mean cell search delay for a noise-limited network is proved to be infinite whenever the non-line-of-sight path loss exponent is larger than two. For interference-limited networks, a phase transition for the mean cell search delay is shown to exist in terms of the number of BS beams M: the mean cell search delay is infinite when M is smaller than a threshold and finite otherwise. Beam-sweeping is also demonstrated to be effective in decreasing the cell search delay, especially for cell edge users.

Initial access is the process which allows a mobile user to first connect to a cellular network. It consists of two main steps: cell search (CS) on the downlink and random access (RA) on the uplink. Millimeter wave (mm-wave) cellular systems typically must rely on directional beamforming (BF) in order to create a viable connection. The BF direction must, therefore, be learned-as well as used-in the initial access process for mm-wave cellular networks. This paper considers four simple but representative initial access protocols that use various combinations of directional BF and omnidirectional transmission and reception at the mobile and the BS, during the CS and RA phases. We provide a system-level analysis of the success probability for CS and RA for each one, as well as of the initial access delay and user-perceived downlink throughput (UPT). For a baseline exhaustive search protocol, we find the optimal BS beamwidth and observe that in terms of initial access delay it is decreasing as blockage becomes more severe, but is relatively constant (about π/12) for UPT. Of the considered protocols, the best tradeoff between initial access delay and UPT is achieved under a fast CS protocol.

We leverage stochastic geometry to characterize key performance metrics for neighboring Wi-Fi and LTE networks in unlicensed spectrum. Our analysis focuses on a single unlicensed frequency band, where the locations for the Wi-Fi access points and LTE eNodeBs are modeled as two independent homogeneous Poisson point processes. Three LTE coexistence mechanisms are investigated: 1) LTE with continuous transmission and no protocol modifications; 2) LTE with discontinuous transmission; and 3) LTE with listen-before-talk and random back-off. For each scenario, we derive the medium access probability, the signal-to-interference-plus-noise ratio coverage probability, the density of successful transmissions (DST), and the rate coverage probability for both Wi-Fi and LTE. Compared with the baseline scenario where one Wi-Fi network coexists with an additional Wi-Fi network, our results show that Wi-Fi performance is severely degraded when LTE transmits continuously. However, LTE is able to improve the DST and rate coverage probability of Wi-Fi while maintaining acceptable data rate performance when it adopts one or more of the following coexistence features: a shorter transmission duty cycle, lower channel access priority, or more sensitive clear channel assessment thresholds.

Although the Poisson point process (PPP) has been widely used to model base station (BS) locations in cellular networks, it is an idealized model that neglects the spatial correlation among BSs. This paper proposes the use of the determinantal point process (DPP) to take into account these correlations, in particular the repulsiveness among macro BS locations. DPPs are demonstrated to be analytically tractable by leveraging several unique computational properties. Specifically, we show that the empty space function, the nearest neighbor function, the mean interference, and the signal-to-interference ratio (SIR) distribution have explicit analytical representations and can be numerically evaluated for cellular networks with DPP-configured BSs. In addition, the modeling accuracy of DPPs is investigated by fitting three DPP models to real BS location data sets from two major U.S. cities. Using hypothesis testing for various performance metrics of interest, we show that these fitted DPPs are significantly more accurate than popular choices such as the PPP and the perturbed hexagonal grid model.

In this paper, we study the throughput and delay scaling laws for cognitive radio network with static primary users and heterogeneous mobile secondary users coexist in the unit planar region for both without base-station case and with base-station case. The primary network consists of $n$ randomly and uniformly distributed static primary users with higher priority to access the spectrum. The secondary network consists of $m=(h+1)n^{1+\epsilon}$ heterogeneous mobile secondary users with $h=O(\log n)$ We use standard asymptotic notations in our paper. Consider two nonnegative function $f(\cdot)$ and $g(\cdot)$ : (1) $f(n)=o(g(n))$ means $\lim_{n\rightarrow\infty}f(n)/\break g(n)= 0$ . (2) $f(n)=O(g(n))$ means $\lim_{n\rightarrow\infty}f(n)/g(n) . (3) $f(n)=\omega(g(n))$ means $\lim_{n\rightarrow\infty}f(n)/g(n)=\infty$ . (4) $f(n)=\Omega(g(n))$ means $\lim_{n\rightarrow\infty}f(n)/g(n) > 0$ . (5) $f(n)=\Theta(g(n))$ means $f(n)=O(g(n))$ and $g(n)=O(f(n))$ . (6) $f(n)=\mathtilde{\Theta}(g(n))$ means that $f(n)=\Theta(g(n))$ when poly-logarithmic factors are ignored.

The macro base station (BS) deployments in modern cellular networks are neither regular nor completely random. We use determinantal point process (DPP) models to study the repulsiveness among macro base stations observed in cellular networks. Three DPP models are fitted to base station location data sets from two major US cities. Hypothesis testing is used to validate the goodness-of-fit for these DPP models. Based on performance metrics including the K-function, the L-function and coverage probability, DPP models are shown to be accurate in modeling real BS deployments. On the contrary, the Poisson point process and perturbed hexagonal grid model are shown to be less realistic. Different DPP models are compared, and several computational properties of these models are also discussed.

We study the capacity and delay scaling laws for cognitive radio network (CRN) with static primary users and heterogeneous mobile secondary users coexisting in the unit planar area. The primary network consists of n randomly and uniformly distributed static primary users (PUs) with higher priority to access the spectrum. The secondary network consists of m = (h + 1)n1+∈heterogeneous mobile secondary users (SUs) which should access the spectrum opportunistically, here h = O(log n) and ∈ > 0. Each secondary user moves within a circular area centered at its initial position with a restricted speed. The moving area of each mobile SU is n−α, where a is a random variable which follows the discrete uniform distribution with h + 1 different values, ranging from 0 to α0(α0> 0). α0and h together determine the mobility heterogeneity of secondary users. By allowing the secondary users to relay the packets for primary users, we have proposed a joint routing and scheduling scheme to fully utilize the mobility heterogeneity of secondary users. We show that the primary network and secondary network can achieve optimal capacity and delay scalings if we increase the mobility heterogeneity of secondary users, i.e., the value of h and α0, until h = Θ(log n) and α0≥ 1 + ∈. In this optimal condition, both the primary network and part of the secondary network can achieve almost constant capacity and delay scalings except for poly-logarithmic factor.

Automated configuration of neighbor cell lists, the so-called Automatic Neighbor Relation (ANR) function, is one of the first SON features being deployed in commercial networks. From the operators' point of view, it is beneficial to know how many ANR enabled UEs should be activated to help the full ANR list configuration. In other words, it is important to predict, given a fixed percentage of ANR enabled UEs, how much time is needed to finish the establishment of neighbor relation list. In this work, we defined an ANR penetration probability prediction method and use this method to, calculate the probability of UE detecting a neighbor relationship based on the number of ANR capable UE number and other related network parameters which can be obtained from the network operators. Two prediction cases using this method are discussed and we use simulation to validate the prediction results.

In this paper, we focus on capacity-delay tradeoffs for multicast traffic pattern. Under the assumption that n nodes move in a unit square according to an i.i.d. mobility model, with each serving as a source that sends identical packets to k destinations, we propose four schemes of which the achievable capacity λ and delay D are analyzed: (1) 2-hop noncooperative non-redundancy scheme, (2) 2-hop noncooperative redundancy scheme, (3) 2-hop cooperative non-redundancy scheme, (4) 2-hop cooperative redundancy scheme. Compared with non-cooperative scheme with capacity delay tradeoff λ = O( E[D]/nk log k) first developed in [5], cooperation among destination nodes achieves optimal capacity delay tradeoff λ = O(E[D]/n log k) in cell partitioned network. With intelligent cooperation, each destination acts equivalently as relay and helps other destinations get more opportunities of receiving packets with capacity sacrificed to a addition, our redundancy schemes also allow delay under Θ(√n) log k factor compared with unicast in [3] under the same delay. In achievable, which is the minimum delay under the schemes of [3],[5].

In this paper, we study the capacity and delay scaling laws for cognitive radio networks (CRN). The primary network consists of n static, randomly and evenly distributed primary users (PUs), which require high throughput with low delay. The secondary network consists of m = O(n1+δ) randomly and evenly distributed cognitive secondary users (SUs) with δ >; 0, which move in different area according to the hierarchical i.i.d. mobility model. The secondary network is carefully designed to support the primary network, so that PUs may achieve near-optimal performance in both capacity and delay aspects. Then by utilizing hierarchical cooperation among SUs with different mobility, a new hierarchical relay algorithm is proposed to improve the delay performance extensively. Under optimal condition, this algorithm may provide Ω(n-δ') per-node throughput and O(nδ") average delay for PU with δ', δ" >; 0, and significantly improve the performance of SU at the same time.

The paper studies the multipath characteristics of the wideband channels at 3.5 GHz in a typical outdoor urban environment. A channel measurement system for this frequency band was developed; Based on the measurement data, the channel modeling parameters including the tapped delay line models, the multipath distribution, the excess delay and the Ricean K-factor were extracted. Then by using the measured channel models, we analyze the BER performance of OFDM system in different data rate and the comparison of the measured channels is made.