A novel coding design is proposed to enhance information retrieval in a wireless network of users with partial access to the data, in the sense of observation, measurement, computation, or storage. Information exchange in the network is assisted by a multi-antenna base station (BS), with no direct access to the data. Accordingly, the missing parts of data are exchanged among users through an uplink (UL) step followed by a downlink (DL) step. In this paper, new coding strategies, inspired by coded caching (CC) techniques, are devised to enhance both UL and DL steps. In the UL step, users transmit encoded and properly combined parts of their accessible data to the BS. Then, during the DL step, the BS carries out the required processing on its received signals and forwards a proper combination of the resulting signal terms back to the users, enabling each user to retrieve the desired information. Using the devised coded data retrieval strategy, the data exchange in both UL and DL steps requires the same communication delay, measured by normalized delivery time (NDT). Furthermore, the NDT of the UL/DL step is shown to coincide with the optimal NDT of the original DL multi-input single-output CC scheme, in which the BS is connected to a centralized data library.

Content caching is perceived as a promising approach to offload traffic from shared medium networks by pre-fetching and placing contents in caches during off-peak hours, and taking advantage of multicasting in the delivery times. While most existing efforts on caching are directed towards reducing the traffic rate over the shared medium, little attention is given to user preferences. Though placement based on the heterogeneity of content popularity improves the caching performance, it is understood to be a non-trivial combinatorial optimization problem. In this paper, we investigate the content caching problem under non-uniform and user-dependent demands and propose several heuristic methods by leveraging hybrid coded-uncoded caching, clustering, and the trade-off between local and global popularity of contents. Simulation results validate our analysis and show the out-performance of the proposed schemes with respect to existing methods.

Multi-antenna coded caching is known to combine a global caching gain that is proportional to the cumulative cache size found across the network, with an additional spatial multiplexing gain that stems from using multiple transmitting antennas. However, a closer look reveals two severe bottlenecks; the well-known exponential subpacketization bottleneck that dramatically reduces performance when the communicated file sizes are finite, and the considerable optimization complexity of beamforming multicast messages when the SNR is finite. We here present an entirely novel caching scheme, termedcyclic multi-antennacoded caching, whose unique structure allows for the resolution of the above bottlenecks in the crucial regime of many transmit antennas. For this regime, where the multiplexing gain can exceed the coding gain, our new algorithm is the first to achieve the exact one-shot linear optimal DoF with a subpacketization complexity that scales only linearly with the number of users, and the first to benefit from a multicasting structure that allows for exploiting uplink-downlink duality in order to yield optimized beamformers ultra-fast. In the end, our novel solution provides excellent performance for networks with finite SNR, finite file sizes, and many users.

We consider the problem of private information retrieval (PIR), where a single user with private side information (PSI) aims to retrieve multiple files from a library stored at some servers. We assume that the side information (SI) at the user includes a subset of files stored privately. Moreover, the identity of requests and side information at the user are not revealed to any of the servers. The problem involves finding the minimum load transmitted from the servers to the user such that the requested files can be decoded with the help of received data and side information. By providing matching lower and upper bounds for certain regimes, we characterize the minimum load imposed on all the servers. Our result shows that the capacity is the same as the capacity of a multi-message PIR problem without PSI, but with a library of reduced size, i.e., the library is equal to the original library size minus the size of SI. Finally, we extend our setup to the case where instead of storing complete files as SI, the user can store a fraction of files. For this scenario, we propose an achievability scheme based on which we discuss the best storing strategies.

Exponentially growing subpacketization is known to be a major issue for practical implementation of coded caching, specially in networks with multi-antenna communication setups. We provide a new coded caching scheme for such networks, which requires linear subpacketization and is applicable to any set of network parameters, as long as the multi-antenna gain L is larger than or equal to the global caching gain t. Our scheme includes carefully designed cache placement and delivery algorithms; which are based on circular shift of two generator arrays in perpendicular directions. It also achieves the maximum possible degrees of freedom of t+L, during any transmission interval.

Device-to-device (D2D) aided beamforming for coded caching is considered in a finite signal-to-noise ratio regime. A novel beamforming and resource allocation scheme is proposed where the local cache content exchange among nearby users is exploited. The transmission is split into two phases: local D2D content exchange and downlink transmission. In the D2D phase, users can autonomously share content with the adjacent users. The downlink phase utilizes multicast beamforming to simultaneously serve all users to fulfill the remaining content requests. A low complexity D2D-multicast mode selection algorithm is proposed with comparable performance to the optimal exhaustive search. We first explain the main procedure via one simple example and then present the general formulation. Furthermore, D2D transmission scenarios and conditions useful for minimizing the overall delivery time are identified. By exploiting the direct D2D exchange of file fragments, the common multicasting rate for delivering the remaining file fragments in the downlink phase is increased, providing greatly enhanced overall content delivery performance.

Content caching is a technique aimed to reduce the network load imposed by data transmission during peak time while ensuring users' quality of experience. Studies have shown that content delivery via coded caching can significantly improve beyond the performance limits of conventional caching schemes when caches and the server share a common link. Finding the optimal cache content placement however, becomes challenging under arbitrary distributions of content popularity. While existing works show that partitioning contents into three popularity levels performs better when multiple requests are received at each time slot, they neither delve into the problem analysis nor derive closed-form expressions for the optimum partitioning problem. In this paper, we analyze the coded caching scheme for a system with arbitrary content popularity, where we derive explicit closed-forms for the server load in the delivery phase and formulate the near-optimum partitioning problem. Simulation results are presented to corroborate our mathematical analysis.

We consider load balancing problem in a cache network consisting of storage-enabled servers forming a distributed content delivery scenario. Previously proposed load balancing solutions cannot perfectly balance out requests among servers, which is a critical issue in practical networks. Therefore, in this paper, we investigate a coded cache content placement where coded chunks of original files are stored in servers based on the files popularity distribution. In our scheme, upon each request arrival at the delivery phase, by dispatching enough coded chunks to the request origin from the nearest servers, the requested file can be decoded. Here, we show that if n requests arrive randomly at n servers, the proposed scheme results in the maximum load of O(1) in the network. This result is shown to be valid under various assumptions for the underlying network topology. Our results should be compared to the maximum load of two baseline schemes, namely, nearest replica and power of two choices strategies, which are O(log n) and O(log log n), respectively. This finding shows that using coding, results in a considerable load balancing performance improvement, without compromising communications cost performance. This is confirmed by performing extensive simulation results, in non-asymptotic regimes as well.

A multi-antenna broadcast channel scenario is considered where a base station delivers contents to cache-enabled user terminals. A joint design of coded caching (CC) and multigroup multicast beamforming is proposed to benefit from spatial multiplexing gain, improved interference management and the global CC gain, simultaneously. The developed general content delivery strategies utilize the multiantenna multicasting opportunities provided by the CC technique while optimally balancing the detrimental impact of both noise and inter-stream interference from coded messages transmitted in parallel. Flexible resource allocation schemes for CC are introduced where the multicast beamformer design and the receiver complexity are controlled by varying the size of the subset of users served during a given time interval, and the overlap among the multicast messages transmitted in parallel, indicated by parameters α and β, respectively. Degrees of freedom (DoF) analysis is provided showing that the DoF only depends on α while it is independent of β. The proposed schemes are shown to provide the same degreesof-freedom at high signal-to-noise ratio (SNR) as the state-of-art methods and, in general, to perform significantly better, especially in the finite SNR regime, than several baseline schemes.

Coded caching can be applied in wireless multi- antenna communications by multicast beamforming coded data chunks to carefully selected user groups and using the existing file fragments in user caches to decode the desired files at each user. However, the number of packets a file should be split into, known as subpacketization, grows exponentially with the network size. We provide a new scheme, which enables the level of subpacketization to be selected freely among a set of predefined values depending on basic network parameters such as antenna and user count. A simple efficiency index is also proposed as a performance indicator at various subpacketization levels. The numerical examples demonstrate that larger subpacketization generally results in better efficiency index and higher symmetric rate, while smaller subpacketization incurs significant loss in the achievable rate. This enables more efficient caching schemes, tailored to the available computational and power resources.

This paper considers a cloud-RAN architecture with cache-enabled multi-antenna Edge Nodes (ENs) that deliver content to cache-enabled end-users. The ENs are connected to a central server via limited-capacity fronthaul links, and, based on the information received from the central server and the cached contents, they transmit on the shared wireless medium to satisfy users' requests. By leveraging cooperative transmission as enabled by ENs' caches and fronthaul links, as well as multicasting opportunities provided by users' caches, a close-to-optimal caching and delivery scheme is proposed. As a result, the minimum Normalized Delivery Time (NDT), a high-SNR measure of delivery latency, is characterized to within a multiplicative constant gap of 3/2 under the assumption of uncoded caching and fronthaul transmission, and of one-shot linear precoding. This result demonstrates the interplay among fronthaul links capacity, ENs' caches, and end-users' caches in minimizing the content delivery time.

Content caching has emerged as a promising technique to reduce the backhaul multimedia traffic rising due to the proliferation of mobile devices. To address the bottleneck issue arising as a result of sparse wireless resources, the current literature is mainly focused on designing centralized or decentralized coded caching schemes. In this paper, we present a hybrid coded caching approach in a cellular network considering mobile users, where both downlink transmission from the base-station (BS) and device-to-device (D2D) communications are permitted. The proposed method comprises of two phases in content delivery. In the first phase, coded packets are delivered using decentralized coded caching which provides concurrent transmissions through spatial reuse. The BS broadcasts the remaining files using the centralized coded caching paradigm in the second phase in order to compensate for the diminishing returns in D2D communications as time progresses. We analytically derive and analyze the optimal switching point for which the network performance improves in terms of throughput and response time delay under two random user mobility models. Validated by simulation results, our hybrid strategy significantly reduces the finishing time as compared to existing schemes.

We investigate the potentials of applying the coded caching paradigm in wireless networks. In order to do this, we investigate physical layer schemes for downlink transmission from a multiantenna transmitter to several cache-enabled users. As the baseline scheme, we consider employing coded caching on the top of max-min fair multicasting, which is shown to be far from optimal at high-SNR values. Our first proposed scheme, which is near-optimal in terms of DoF, is the natural extension of multiserver coded caching to Gaussian channels. As we demonstrate, its finite SNR performance is not satisfactory, and thus we propose a new scheme in which the linear combination of messages is implemented in the finite field domain, and the one-shot precoding for the MISO downlink is implemented in the complex field. While this modification results in the same near-optimal DoF performance, we show that this leads to significant performance improvement at finite SNR. Finally, we extend our scheme to the previously considered cache-enabled interference channels, and moreover we provide an ergodic rate analysis of our scheme. Our results convey the important message that although directly translating schemes from the network coding ideas to wireless networks may work well at high-SNR values, careful modifications need to be considered for acceptable finite SNR performance.

A single cell downlink scenario is considered where a multiple-antenna base station delivers contents to cache-enabled user terminals. Using the ideas from multi-server coded caching (CC) scheme developed for wired networks, a joint design of CC and general multicast beamforming is considered to benefit from spatial multiplexing gain, improved interference management and the global CC gain, simultaneously. The proposed multicast beamforming strategies utilize the multiantenna multicasting opportunities provided by the CC technique and optimally balance the detrimental impact of both noise and inter-stream interference from coded messages transmitted in parallel. The proposed scheme is shown to provide the same degrees-of-freedom at high SNR as the state-of-art methods and, in general, to perform significantly better than several baseline schemes including, the joint zero forcing and CC, max-min fair multicasting with CC, and basic unicasting with multiuser beamforming.

We consider the problem of private information retrieval (PIR) where a single user with private side information aims to retrieve multiple files from a library stored (uncoded) at a number of servers. We assume the side information at the user includes a subset of files stored privately (i.e., the server does not know the indices of these files). In addition, we require that the identity of requests and side information at the user are not revealed to any of the servers. The problem involves finding the minimum load to be transmitted from the servers to the user such that the requested files can be decoded with the help of received and side information. By providing matching lower and upper bounds, for certain regimes, we characterize the minimum load imposed to all the servers (i.e., the capacity of this PIR problem). Our result shows that the capacity is the same as the capacity of a multi-message PIR problem without private side information, but with a library of reduced size. The effective size of the library is equal to the original library size minus the size of side information.

A wireless coded caching (CC) setup is considered, where a multi-antenna transmitter delivers contents to multiple cache-enabled users. Exploiting multicasting opportunities provided by the coded caching paradigm, novel interference management schemes are proposed by assigning carefully designed beamforming vectors to different multicast messages. Thereby, the proposed design benefits from spatial multiplexing gain, improved interference management and the global CC gain, simultaneously. In addition, a novel multicast mode selection scheme is proposed which determines the optimum multicast group sizes providing the best complexity-performance tradeoff for a given SNR range. While the proposed scheme exhibits the same near-optimal degrees-of-freedom (DoF) performance as previously proposed methods, it will surpass them at the practical finite SNR regimes. In addition to reducing the complexity, the proposed mode selection feature also provides significantly better rate than previously proposed schemes.

We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems. In this framework, we investigate the tension between storage resources, communication cost, and load balancing performance. To this end, we propose a randomized load balancing scheme which simultaneously considers cache size limitation and proximity in the server redirection process. In contrast to the classical power of two choices setup, since the memory limitation and the proximity constraint cause correlation in the server selection process, we may not benefit from the power of two choices. However, we prove that in certain regimes of problem parameters, our scheme results in the maximum load of order Q(loglogn) (here n is the network size). This is an exponential improvement compared to the scheme which assigns each request to the nearest available replica. Interestingly, the extra communication cost incurred by our proposed scheme, compared to the nearest replica strategy, is small. Furthermore, our extensive simulations show that the trade-off trend does not depend on the network topology and library popularity profile details.

We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems that reduces network imbalance. In this paper, we propose a randomized load balancing scheme which simultaneously considers cache size limitation and proximity in the server redirection process. Since the memory limitation and the proximity constraint cause correlation in the server selection process, we may not benefit from the power of two choices in general. However, we prove that in certain regimes, in terms of memory limitation and proximity constraint, our scheme results in the maximum load of order Θ(log log n) (here n is the number of servers and requests), and at the same time, leads to a low communication cost. This is an exponential improvement in the maximum load compared to the scheme which assigns each request to the nearest available replica. Finally, we investigate our scheme performance by extensive simulations.

It is well known that load balancing and low delivery communication cost are two critical issues in mapping requests to servers in Content Delivery Networks (CDNs). However, the trade-off between these two performance metrics has not been yet quantitatively investigated in designing efficient request mapping schemes. In this work, we formalize this trade-off through a stochastic optimization problem. While the solutions to the problem in the extreme cases of minimum communication cost and optimum load balancing can be derived in closed form, finding the general solution is hard to derive. Thus we propose three heuristic mapping schemes and compare the trade-off performance of them through extensive simulations. Our simulation results show that at the expense of high query cost, we can achieve a good trade-off curve. Moreover, by benefiting from the power of multiple choices phenomenon, we can achieve almost the same performance with much less query cost. Finally, we can handle requests with different delay requirements at the cost of degrading network performance.

We consider a K-user Interference Channel where each transmitter is interested in conveying a message to its corresponding receiver. In addition, we assume a fully connected noiseless backhaul network through which receivers can collaborate and help each other recover their desired messages. In this paper, we fully characterize the trade-off between the rate in wireless link (per user) in terms of degrees of freedom (DoF) versus backhaul load (per user) for large values of K. In particular, we characterize the optimal trade-off for all values of K, where K is an even number. For odd values of K, we characterize the trade-off within a gap of 2(k - 1)/k(k + 1), which goes to zero as K increases. For achievability we use time-sharing between two corner points: (i) using interference alignment for the case where backhaul load is zero, and (ii) collecting a quantized version of all the received signals at one of the receivers to jointly decode the messages, for the case where DoF of one per user is desired. For the converse, we develop a new outer-bound based on the results from two-user multiple antenna interference channel with limited backhaul cooperation. Recently, it was shown that for the case of three-user interference channel, the optimal trade-off is achieved by some sort of alignment in the backhaul messaging, known as Cooperation Alignment. Our result shows that unlike the gain of interference alignment, the gain of cooperation alignment does not scale with the number of users K.

In this paper we consider a single-cell downlink scenario where a multiple-antenna base station delivers contents to multiple cache-enabled user terminals. Based on the multicasting opportunities provided by the so-called Coded Caching technique, we investigate three delivery approaches. Our baseline scheme employs the coded caching technique on top of max-min fair multicasting. The second one consists of a joint design of Zero-Forcing (ZF) and coded caching, where the coded chunks are formed in the signal domain (complex field). The third scheme is similar to the second one with the difference that the coded chunks are formed in the data domain (finite field). We derive closed-form rate expressions where our results suggest that the latter two schemes surpass the first one in terms of Degrees of Freedom (DoF). However, at the intermediate SNR regime forming coded chunks in the signal domain results in power loss, and will deteriorate throughput of the second scheme. The main message of our paper is that the schemes performing well in terms of DoF may not be directly appropriate for intermediate SNR regimes, and modified schemes should be employed.

The demand for multimedia services in modern networks has experienced exponential growth in recent years and it is expected to dominate the mobile traffic in near future. On the other hand, the link capacity of mobile networks is limited due to the scarce wireless resources. Caching is a popular technique that uses available storage capability of the mobile devices to relieve this traffic tension in high peak hours of network operation. In this paper, we investigate the effect of mobility on a wireless device-to-device (D2D) coded caching architecture. Coded caching is a technique in which library files are split into sub-files and any combination of sub-files can be cached at devices and exchanged between them later. We consider two mobility models for our network architecture and study the effect of mobility on the throughput of the network. We show that, in contrast to the static scenario, by exploiting the mobility in a D2D coded caching network, the coded multi-casting gain and the spatial reuse gain can be attained simultaneously, in terms of the throughput scaling law.

We consider a cellular wireless system including several interfering multi-user multi-antenna uplink channels, where the base station of each cell has to locally recover the messages of its corresponding users. We use a linear Wyner model, where each base station experiences interference only from the users in the two neighboring cells. Each base station is connected to the two nearby base stations through a backhaul link. The objective is to achieve the maximum degrees of freedom per cell, with minimum aggregated load in the backhaul. We propose a successive cooperative alignment scheme, in which each base station forms backhaul messages by combining the previous received backhaul messages with the received signals at its wireless terminal. By some alignment schemes in signaling over wireless links as well as developing proper messages over backhaul links, each base station can help the neighboring base stations to peel off the aggregated interference with minimum help. This is done without propagating interference throughout the network. In this conference paper, we focus on linear one shot schemes and prove the optimality of the proposed scheme, in a robust set-up for a system with two antennas per base station and two users per cell, where each user is equipped with two antennas.

Recent studies reveal that an adversary might trace the apparently insignificant traffic rate of source nodes over the net and turn such data to invaluable information so as to breach the privacy of the victim sources. Inhibiting the adversary of being able to extract information from the traffic rate of source nodes is a complicated task unless taking into consideration the flow conservation law effect of the transmitter queue. A reliable method of preserving the rate privacy that copes with the flow conservation law is to transmit original packets augmented with probabilistically dummy ones so as to change the observable aggregated traffic rate. Augmenting dummy packets, however, bears redundancy, and hence, requires extra resources in terms of bandwidth and buffer requirements, and more importantly suggests higher transmitting energy consumption. Grounded on the queueing and information theories, in this paper, we present an efficient method that minimally augments dummy packets to preserve the source rate privacy at a given degree while preserving the delay distribution of the original packets intact, and thus does not affect the quality of service parameters of the transmitted data in terms of delay and jitter. The presented method models the original packets and dummy ones with a preemptive resume 2-priority queueing system and then using information theory attempts to maximize the Fano lower bound of the best estimation of the adversary's speculation. All of the theoretically obtained results have been validated by conducting simulation experiments.

In this paper, we consider multiple cache-enabled clients connected to multiple servers through an intermediate network. We design several topology-aware coding strategies for such networks. Based on the topology richness of the intermediate network, and types of coding operations at internal nodes, we define three classes of networks, namely, dedicated, flexible, and linear networks. For each class, we propose an achievable coding scheme, analyze its coding delay, and also compare it with an information theoretic lower bound. For flexible networks, we show that our scheme is order-optimal in terms of coding delay and, interestingly, the optimal memory-delay curve is achieved in certain regimes. In general, our results suggest that, in the case of networks with multiple servers, type of network topology can be exploited to reduce service delay.

The authors consider the effect of caching in interference‐limited wireless networks where fading is the dominant channel effect. First, the authors propose a one‐hop transmission strategy for cache‐enabled wireless networks, which is based on exploiting multi‐user diversity gain. Then, they derive a closed‐form result for throughput scaling of the proposed scheme in large networks, which reveals the inherent trade‐off between cache memory size and network throughput. Their results show that substantial throughput improvements are achievable in networks with sources equipped with large cache size, compared with previous works where each transmitter could just store one file. Also, the authors provide extensive simulations through which they analyse network throughput and verify their analytical results. Their simulations suggest that the scaling results also hold true even by introducing correlation between channels, making the results more general.

Many applications in wireless networks impose locally distributed traffic on the network. We consider the effect of traffic localization on throughput of large wireless networks in the scaling sense. We show that by careful exploitation of traffic localization, one can enhance the throughput of various schemes in wireless networks. Also, the important case of Small World traffic distribution in wireless networks is addressed. In this type of traffic, in addition to the local traffic, a non-negligible amount of global traffic should be handled by the network. It is shown that a non-negligible amount of network-wide traffic can be tolerated by network without any performance degradation in the scaling sense.

We consider the effect of caching in wireless networks where fading is the dominant channel effect. First, we propose a one-hop transmission strategy for cache-enabled wireless networks, which is based on exploiting multi-user diversity gain. Then, we derive a closed-form result for throughput scaling of the proposed scheme in large networks, which reveals the inherent trade-off between cache memory size and network throughput. Our results show that substantial throughput improvements are achievable in networks with sources equipped with large cache size. We also verify our analytical result through simulations.

In this study, the authors propose a novel power allocation scheme in time division multiple access (TDMA)‐based distributed multiple‐input multiple‐output (MIMO) channels. By modelling the problem with a TDMA MIMO interference channel, the authors have derived closed‐form expressions for power and time slot assigned to each MIMO transmission. Although our scheme is sub‐optimal, with the aid of Jensen's inequality, it is shown to be superior to solutions based on channel inversion. In addition, the proposed scheme is compared with the optimal solution, and also with the scheme proposed by Dohler. By applying our proposed power allocation to the hierarchical cooperation strategy, the authors have shown that this scheme significantly improves the overall network throughput compared with the channel inversion solution. However, the improvement gain (which is at high‐signal‐to‐noise ratio values) reduces when the method is compared with Dohler's solution.

In this paper, we derive the rate of route discovery process for finding a randomly chosen destination in large wireless networks. The well-known protocol for route discovery is flooding in which each node simply rebroadcasts the route request packet once. Rate of route discovery process is defined as the inverse of time between transmitting two successive route request packets which shows how fast a node can request a route to its destination. Discovery time is another parameter of interest. For a single node discovering routes to its destination, at most the rate of È (1/3√n) is feasible when n identical nodes are optimally placed in network area and the discovery time is of order È(3√n). Achievability of such rate is obtained through optimal placement and hierarchical scheduling of nodes transmissions.

In this paper, we analyze the role of the number of quantization bits on the third phase of the hierarchical cooperation scheme proposed by Ozgur et al. in 2007. The hierarchical cooperation scheme has a digital architecture and requires quantization of MIMO (Multiple-Input Multiple-Output) observations in the third phase. The choice of the number of quantization bits Q has direct effect on the pre-constant factor of the network throughput. By increasing the number of quantization bits, the MIMO capacity in the second phase increases at the expense of higher computational complexity of the third phase. We investigate such trade-off and show that there is an optimum number of quantization bits which maximizes the throughput. In addition, it will be shown that due to quantization noise, it is not possible to increase throughput pre-constant factor as large as desired by increasing transmit power. As a result, there is a saturation value for the pre-constant value. Finally, we will demonstrate that by proper scaling of Q as Q = β log(SNR) for any β independent of SNR, an increasing pre-constant factor of order √(log (SNR)) can be achieved.

There are two types of scatterers in a multipath propagation environment: fixed and non-fixed scatterers. Fixed scatterers like buildings, mountains and tree stems do not move, while non-fixed (moving) scatterers like cars, people and tree leaves move from their initial positions. In addition to different movements of the mobile station (MS) that cause different kinds of Doppler fading, movements of non-fixed scatterers are also anticipated to generate other kinds of fading/correlation. This fading changes depend on the type of the propagation environment and the type of movements of local surrounding scatterers. In this paper we characterize these effects in terms of temporal correlations. In this study we assume constant speed for the MS and random displacements for scatterers based on stationary-increment Wiener vector process. As it will be verified, these random movements have direct effect on the channel process power spectral density (PSD).