We study the downlink of a limited fronthaul capacity cloud-radio access networks (C-RANs). Three energy efficiency metrics, namely, global energy efficiency (GEE), weighted sum energy efficiency (WSEE), and energy efficiency fairness (EEF) are maximized by jointly designing transmit beamforming, remote radio head (RRH) selection, and RRH-user association. Furthermore, we incorporate a rate-dependent fronthaul power model, in which the fronthaul power consumption is proportional to the user sum rate. The formulated problems are difficult to solve. Our first contribution is to customize a branch and reduce and bound (BRB) method based on monotonic optimization to find globally optimal solutions for the three energy efficiency maximization problems. Subsequently, for a more practical approach, we propose a unified framework based on successive convex approximation (SCA) method that can be applied to all the considered problems. Our novelty lies in the equivalent transformations leading to more tractable problems that are amenable to the SCA. Specifically, appropriate continuous relaxation and convex approximation techniques are employed to arrive at a sequence of second-order cone programs (SOCPs) for which dedicated solvers are available. Then, a post-processing algorithm is devised to obtain a high-performance feasible solution from the continuous relaxation. The numerical results demonstrate that the proposed SCA-based algorithms converge rapidly and achieve near-optimal performance as well as outperform the known methods. They also highlight the importance of the rate dependent fronthaul power model in designing the energy efficient C-RANs.

We consider the downlink virtualized cloud-radio access networks (C-RANs) with limited capacity fronthaul. A novel virtual computing resource allocation (VCRA) which can dynamically split the users workload into smaller fragments to be served by virtual machines is presented. Under the proposed scheme, we aim at maximizing the network energy efficiency (EE) by a joint design of virtual computing resources, transmit beamforming, remote radio head (RRH) selection, and RRH-user association, considering rate dependent fronthaul power consumption model. The formulated problem is generally combinatorial and NP-hard. For an appealing solution approach, we resort to the difference of convex algorithm (DCA) to solve the continuous relaxed problem. In particular, Lipschitz continuity is derived for non-convex parts to arrive at a sequence of convex quadratic programs, which can be solved efficiently by modern convex solvers. Finally, a post-processing procedure is proposed to obtain a high-performance feasible solution from the continuous relaxation. Numerical results show that the proposed algorithms converge rapidly and the proposed scheme significantly improves the network EE compared to the existing schemes.

We consider the virtualization technique in the downlink transmission of limited fronthaul capacity cloud-radio access networks. A novel virtual computing resource allocation (VCRA) method which can dynamically split the users workload into smaller fragments to be served by virtual machines is presented. Under the proposed scheme, we aim at maximizing the network energy efficiency by a joint design of virtual computing resources, transmit beamforming, remote radio head (RRH) selection, and RRH-user association. Moreover, we construct a more realistic fronthaul power consumption model, which is directly proportional to users' rate transmitted by the corresponding RRHs. The formulated problem is combinatorial and difficult to solve in general. Our first contribution is to customize a branch-and-reduce-and-bound method to attain a globally optimal solution. To compute a high-quality approximate solution, a standard routine is used to deal with the continuous relaxation of the original problem. However, the proposed continuous relaxation is non-convex which implies another challenge. For a practically appealing solution approach, we resort to a local optimization method, namely the difference of convex algorithm. Our second contribution is on the use of Lipschitz continuity to arrive at a sequence of convex quadratic programs, which can be solved efficiently by modern convex solvers. Finally, a post-processing procedure is proposed to obtain a high-performance feasible solution from the continuous relaxation. Extensive numerical results demonstrate that the proposed algorithms converge rapidly and achieve near-optimal performance as well as outperform other known methods. Moreover, we numerically show that the VCRA scheme significantly improves the system energy efficiency compared to the existing schemes.

This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by fronthaul depends on the rate served by the corresponding remote radio head (RRH). Then, we formulate a joint design of RRH selection, RRH-user association, and transmit beamforming for the problem of energy efficiency maximization. The formulated problem is a mixed-integer nonconvex program, which is generally NP-hard. For this nonconvex program, we leverage successive convex approximation (SCA) method to develop efficient iterative algorithms to find a high performance. Particularly, we iteratively approximate the continuous nonconvex constraints by conic ones so that the problem obtained at each iteration is a mixed-integer second order cone programming (MI-SOCP) for which dedicated solvers are available. To further reduce the computational complexity, an algorithm based on continuous relaxation and post-processing is proposed. Results show that our proposed algorithms converge faster and outperform known solutions.

This paper considers the downlink transmission of cloud-radio access networks (C-RANs) with limited fronthaul capacity. We formulate a joint design of remote radio head (RRH) selection, RRH-user association, and transmit beamforming for simultaneously optimizing the achievable sum rate and total power consumption, using the multi-objective optimization concept. Due to the non-convexity of per-fronthaul capacity constraints and introduced binary selection variables, the formulated problem is combinatorial and nonconvex, which is generally NP-hard. To deal with this difficulty, we develop a new framework which iteratively approximates the continuous non-convex constraints by convex ones in the form of second order cones. The problem arrived at each iteration is a mixed integer second order cone programming which can be solve optimally and efficiently. Numerical results show that our proposed algorithms converge rapidly and outperform the existing solutions.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CAPEX and OPEX costs, QoS or QoE, multi-tier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield “turnkey” WAV strategies.

This paper presents the measurements results of a 60 GHz wireless channel in underground mine galleries at depths of 40 m and 70 m. Different antenna polarizations and configurations were considered in this study. Results show that the rough surface scattering and the gallery dimensions of the underground mine significantly impact on the time dispersion characteristics. Particularly, a vertical antenna configuration provides a larger number of multipath than a horizontal one. Due to the fact of gallery dimension and surface roughness characteristics, the 70 m-depth gallery provides a lower value of delay spread and more time variation phenomenon than the 40 m-depth. Omnidirectional antenna configurations are also shown to be not feasible for point to point link. The characteristics of the power delay profile of the scattered channel based on the antenna radiation pattern and impact on its time dispersion are discussed.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CaPeX and OPEX costs, QoS or QoE, multitier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield ”turnkey” WAV strategies.

Simultaneous bidirectional transmission and reception of signals on a single channel in a full duplex (FD) system is gaining increased attention from both academia and industry. Recent advances in radio transceiver design have been able to minimize the self interference (SI) to a great extent making realization of a FD transceiver possible. For FD deployment in a multi-cell environment, minimizing SI is not sufficient due to the presence of a complex array of network-wide interference. This paper investigates the critical deployment challenges for a dense urban FD multi- cell network and provides solutions for successful deployment of FD cellular networks. Extensive simulation results show that the proposed user selection and power control algorithms are able to increase the FD performance gain by more than 80% when compared to the traditional half duplex (HD) counterpart.

This paper considers the power minimization problem in downlink of cloud radio access networks with limited fronthaul capacity. A joint design of beamforming, remote radio head (RRH) selection and RRH-user association that explicitly takes into account per- fronthaul capacity constraints is considered. The problem of interest is in fact a combinatorial program which is generally NP- hard. We naturally write the considered problem as a mixed integer program by introducing binary selection variables. The challenge is that even if these binary selection variables are relaxed to be continuous, the resulting problem is still nonconvex. For such a problem, finding a high- quality solution, rather than an optimal one, is a more realistic goal. Towards this end we propose two iterative algorithms to deal with combinatorial nature of the joint design problem. In the first method, by novel transformations, we iteratively approximate the continuous nonconvex constraints by convex conic ones using successive convex approximation framework. More explicitly the problem arrived at each iteration of the first method is a mixed-integer second order cone program (MISOCP) for which dedicated solvers are available. The second method is a simplified variant of the first one where we further relax the binary variables in each iteration to be continuous. That is to say, the second method merely requires solving a sequence of SOCPs. After convergence, we then perform a postprocessing procedure on the relaxed selection variables to search for a high-performance solution. Numerical results are presented to demonstrate the superiority of the proposed algorithms over existing methods based on sparse-inducing norm.

Wireless access virtualization is an emerging avenue for research for future 5G networks. For its ability to augment network sharing and its subsequent impact on reducing network setup and operational costs, network virtualization is greatly sought after by telecommunications operators all over the world. This paper classifies virtual wireless access into three possible PHY-MAC models that differ in terms of the degree of segregation of baseband signal processing and radio access units. One of the models uses special purpose hardware while another leverages software defined networking (SDN) and cloud computing technologies for implementing virtual wireless access using general purpose hardware. The proposed models differ in terms of their associated network operational cost as well as in terms of the level of QoS they can provide. A new multi-criteria utility function is hence proposed in order to assess the tradeoffs between network cost & QoS of these models from a PHY-MAC layer perspective. The new utility function provides guidelines for a network designer to choose the optimal virtualization model that best fits an operator's budget constraint as well as the QoS requirement of the intended service. Analytical results show that a novel hybrid model that properly combines both special purpose and SDN & cloud computing technologies maximizes the newly introduced utility function by attaining the best balance between overall network cost and QoS. This occurs in most expected practical cases where precisely, one of the two does not relatively outweigh the other and viceversa.

Virtualization is seen as a killer application of software defined networking (SDN). Virtual radio access network (RAN) is an emerging concept for 5G and beyond 5G networks and it is gaining increased attention from both academia and industry alike. Moreover, due to the current telecommunication trend of increasing network traffic and decreasing revenue, telecom operators all over the world are looking for network function virtualization (NFV) to reduce network deployment and running cost by maximizing resource sharing. In this paper, we classify virtual RAN into three possible PHY-MAC models that leverage SDN for virtualizing the underlying RAN substrate. A novel multi-criteria utility function is also proposed to evaluate the trade-offs between network cost and achievable QoS from PHY-MAC layers perspectives of these virtual RAN models. Analytical results show that a hybrid virtualization model attains the optimal balance between network cost and QoS and hence is the best virtual RAN model.

This paper presents reflection coefficient measurements in order to analyze the scattering effect of rough walls and floor on mm-Wave propagation at 60 GHz in an underground mine. A 60 GHz frequency domain measurement system with directional antennas is considered. Reflection coefficients are obtained by individual reflected signals and line of sight (LOS) signals with a particular reflective angle then compared with theoretical models. Results suggest a distinguishable reflection and scattering characteristics between mine wall and floor. In specular directions, the path loss difference between the LOS and the reflected signal lies between 11 dB to 18 dB. In both surfaces, strong reflections on specular directions and scattering on non specular directions have been observed. Moreover, wall surface of the mine produces more scattering with strong reflections than floor surface. These reflection coefficient parameters are useful to estimate multipath signal strength in channel modelling for propagation prediction in underground mine.

Fourth generation standards will provide interoperability between different wireless access technologies. This will be partly enabled by Vertical Handoff (VHO) which ensures a continuation of service when the access technology is switched, e.g. from a Wireless Local Area Network (WLAN) to a Cellular Network (CN) and vice versa. In this paper, we propose a VHO decision algorithm based on scalar Kalman filtering. Criteria such as probability of false handoff, number and position of handoffs are used to evaluate and compare our work with existing handoff algorithms based on filtering techniques. Our algorithm is shown to limit by 40 percent, in a worst case scenario, the probability of false handoff when compared to other HO algorithms.

The paper presents design of a linear precoder for orthogonal space-time block coded orthogonal frequency division multiplexing (OFDM)-based multiple-input multiple-output (MIMO) antenna cognitive radio (CR) when operating in correlated Rayleigh fading channels. Unlike previous studies on precoder design for CR, this proposed linear precoder is capable of handling both transmit and receive correlation in a multi-carrier based CR system. The linear precoder is designed to minimize an upper bound on the average pairwise error probability, constrained to a set of per subcarrier transmit power constraints at the CR transmitter and a set of interference power thresholds at primary user receivers. The CR transmitter exploits the knowledge of transmit and receive correlation matrices while designing the precoder. It is shown that the linear precoder design problem is convex with these constraints, and convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal precoder matrices. Computer simulations are performed to investigate the performance of the proposed linear precoder in a CR system.

This paper presents an Ultra-Wideband (UWB) computationally-efficient fast acquisition system suggested for ranging in indoor, Line-Of-Sight (LOS) environments. The performance of the proposed scheme is evaluated and its implementation issues are discussed. The design complexity leverages field-programmable gate arrays (FPGA) to implement the parallel processing concept. Timing acquisition at high sampling rates of the ultra-short pulses used in UWB communications can be costly and slow for ranging. This is due to the large number of required operations in an intensive software-based signal processing. The proposed UWB scheme in this paper uses an efficient block-processing technique that simplifies hardware implementation with a greatly reduced number of operations and acquisition time, while also offering accurate ranging capabilities over the considered indoor channel at high levels of multiple-user interference (MUI) and Gaussian noise.

This paper presents a blind parameter estimation algorithm for orthogonal frequency division multiplexing (OFDM) signal affected by a time-dispersive channel, timing offset, carrier frequency offset and additive Gaussian noise. Unlike the previous studies, this paper presents the second-order cyclostationarity of OFDM signal considering the effect of time-dispersive channel. The cyclostationarity properties of received OFDM signal in time-dispersive channel is exploited to estimate the OFDM parameters. These parameters includes OFDM symbol period, useful symbol period, cyclic prefix factor, number of subcarriers and carrier frequency offset. Simulations are performed to investigate the performance of OFDM parameter estimation algorithm in diverse channel conditions.

This paper presents a lower-bound on the ergodic sum capacity of single-input single-output (SISO) opportunistic spectrum sharing multiple access channel (MAC) in Rayleigh fading channels with imperfect channel estimates. Unlike the previous studies, this paper considerers the channel estimation errors for both sets of SISO channels between the secondary user (SU) transmitters and the SU receiver and between the SU transmitters and the primary user receivers. By considering these channel estimation errors, an optimal power allocation policy for each SU transmitter is derived to achieve a lower-bound of the ergodic sum capacity of opportunistic spectrum sharing MAC, subject to a set of SUs transmit power constraints and a set of interference power constraints at each PU receiver. Furthermore, convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal power allocation for each SU transmitter. Numerical results are presented to illustrate the influences of the channel estimation errors on the ergodic sum capacity.

Next generation wireless networks are foreseen to be heterogeneous in nature.Wireless networks consisting of different access technologies with different bandwidth and coverage area will coexist to provide roaming users with their requirements. Handoff among heterogeneous networks, i.e. vertical handoff (VHO), has attracted enormous attention from researchers over the last couple of years. Absence of symmetry is the core distinction between homogeneous and heterogeneous networks, as one network has preference over the other network. Therefore a proficient handoff mechanism is crucial for making the experience seamless to the user, trim down the number of unnecessary handoffs, as well as to capitalize on the underlay network utilization. In this article, we propose an advanced filtering based VHO algorithm in 3G/WLAN and discuss its performance. Performance criteria are based on the number of handoffs.

IEEE 802.11 based wireless networks are widely deployed in densely populated areas such as university campuses, airports, offices, cafeterias, etc. Their popularity is rising because of their low cost and high bandwidth except that they cover small coverage areas. In order to cover large areas several access points (AP) are required, which makes it disruptive technology. During roaming, the mobile station (STA) makes frequent handoffs (HO) between APs. Scanning delay during the HO process is quite high, which makes it unsuitable for real-time applications such as VoIP (voice over internet protocol). In this article, we present a technique to reduce the MAC layer HO delay. Using an analytical model, we discuss our technique along with numerical results, and show that the scanning delay is within VoIP constraint which is a major obstacle for WLANs to be used for real-time applications.

A new interference estimation approach is presented for the underlay secondary spectrum sharing paradigm, which will increasingly become a necessity as a result of increasing wireless communication demands. Our scheme is especially designed to deal with very low communication between a smart antennas equipped secondary network and a primary (legacy) wireless network. Since only the primary antennas' coarse probabilistic locations are known by the secondary network, an uncertainty area is considered for each antenna in terms of its intersection with secondary network radio coverage areas. With only few offline communicated coexistence constraints to be respected by both networks, a Monte Carlo simulation is used to statistically establish the coexistence scheme. Although computationally expensive as compared to our previous technique, the one presented in this paper now approaches the theoretical accuracy upper bound for this coexistence context, hence increasing the wireless coexistence worthiness.

The scarcity of the radio spectrum now encourages the use of cognitive radios so that highly sought frequency bands could be shared between a secondary and a primary (legacy) network. This paper presents a new interference estimation technique for a smart antenna equipped MANET (Mobile Ad hoc NETwork), acting as a secondary network, to estimate its interference to fixed primary network devices by means of uncertainty ellipses surrounding the coarse probabilistically estimated location of those devices. The MANET can thus assess by simulation the impact of its future spectrum sharing with the primary network and takes countermeasures accordingly. Simulation results demonstrate the advantage of using this new technique compared to our previous technique that uses uncertainty circles.

Cognitive radio (CR) is a recent innovation based on an intelligent radio design paradigm that can vastly improve utilization of valuable radio spectrum. However, successful deployment of CR technology in next generation wireless networks requires many new research challenges to be addressed, especially in the medium access control (MAC) layer. In this paper, we propose a novel MAC design, referred as Opportunistic Multichannel Cognitive MAC (OMC-MAC), for distributed CR networks to address some of these most important design issues. We also develop an analytical framework to study the performance of our proposed protocol in terms of important performance measures. The results achieved from the analytical model and validated by simulation, show that our simple yet efficient design achieves excellent spectrum utilization, shows superb robustness in presence of sensing error and handles multichannel hidden terminal problem very effectively.

We propose a power loading scheme for multi- carrier cognitive radio (CR) network employing multiple-input multiple-output (MIMO) antennas. We allocate power to different transmitting antennas within different subcarriers maximizing the total system capacity while maintaining the interference to primary user within a prescribed limit. We formulate this as a convex optimization problem and use numerical methods to solve for optimal power allocation. We also compare the performance of power loading scheme proposed in this paper to conventional uniform power loading scheme with and without interference constraint. Simulation results show that the capacity of MIMO CR using our proposed power loading scheme increases significantly with increase in interference temperature limit and the number of transmit antennas. However, we also confirm that if we include interference constraint in the conventional uniform power loading schemes, the capacity does not increase proportionally with increase in number of transmit antennas as those schemes do not take the instantaneous channel condition between cognitive user transmitter and primary user receiver into account.

In this paper, we introduce a spectrum holes detection approach, which combines blind modulation classification, angle of arrival estimation and number of sources detection. We perform eigenspace analysis to determine the number of sources, and estimate their angles of arrival. In addition, we classify detected sources as primary or secondary users with their distinct second-order/one-conjugate cyclostationarity features. Extensive simulations carried out indicate that the proposed system identifies and locates individual sources correctly, even at -4 dB SNR.

Efficient and reliable power allocation algorithm in cognitive radio (CR) networks is a challenging problem. Traditional water-filling algorithm is inefficient for CR networks due to the interaction with primary users. In this paper, we consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. Finally, we discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them.

A major application of wireless communications in confined indoor areas is positioning. Ultra-wideband (UWB) has been recently promoted as a very promising physical support for such use. However, fast and accurate timing acquisition of the ultra-short pulses transmitted in indoor environments is significantly challenging, and even more so in hostile areas such as underground mines. This paper presents an UWB fast acquisition system proposed for positioning in an underground mining environment. The parameters of the proposed UWB acquisition system are detailed and its effectiveness is confirmed by computer simulations.

This paper presents a new adaptive antenna-array beamforming receiver for multipath correlated signals in hostile environments, such as indoor confined or underground areas, where intersymbol interference (ISI) and intrasymbol interference (isi) are predominant. The proposed receiver uses a new synchronization approach for multipath propagation and is based on sequential blind CMA and nested LMS beamformings with adaptive fractional-time-delay estimation. This approach uses on one hand CMA and LMS to recover any time path arrival (TPA) that is an integer multiple of the sampling interval, and nested adaptive fractional time delay estimation with LMS on the other hand to recover any TPA that is a non-integer multiple of the sampling interval. Coherent Maximum Ratio Combining (MRC) with hard Decision Feedback Identification (DPI) is also proposed for optimal and constructive combination of these different extracted paths. Analysis and results show the promising performance of the new adaptive antenna-array structure for different operating conditions and modulation schemes.

Ultra-wideband (UWB) has been recently promoted as a very promising technology for wireless communications. Rapid and accurate timing acquisition of ultra-short pulses and the high sampling rates create challenges for both signal acquisition and the overall UWB transceiver implementation, and even more so under non-ideal conditions. In this paper, we evaluate the performance of a computationally-efficient implementation of a DS-UWB acquisition scheme. The suggested rapid acquisition system based on a block-processing technique adapted to a circular frequency domain correlation, shows explicit design characteristics that offer greatly improved acquisition time, accuracy and implementation cost, while also yielding very satisfactory performance at high noise and MAI levels.

In a harsh indoor environment, fingerprinting geolocation techniques perform better than the traditional ones, based on triangulation, because multipath is used as constructive information. However, this is generally true in static environments as fingerprinting techniques suffer degradations in location accuracy in dynamic environments where the properties of the channel change in time. This is due to the fact that the technique needs a new database collection when a change of the channel's state occurs. In this paper, a novel solution based on a hierarchy of artificial neural networks (ANNs) is proposed to enhance such a geolocation system. It is shown that the enhanced system detects the change in the channel's properties via geolocation reference points, identifies the new channel state and activates a new database that best represents the current radio environment

In this paper, a new technique enabling path diversity maximum ratio combining (MRC) is proposed to leverage the performance of the previously proposed Sequential Blind Beamforming (SBB) method. The latter mitigates the inter-symbol and intra-symbol interferences and recovers the signal and its integer and non-integer (fractional) multiple replicas using jointly CMA, LMS and adaptive fractional time delay estimation. While implementing EGC at the combining step can give an acceptable performance in the SBB, since the resolved paths have common phase ambiguity, more substantial improvement can be obtained by implementing coherent MRC with hard decision feedback identification. Simulations results in different scenarios validate the superiority of the SBB using the proposed MRC compared to the EGC path combiner.

This paper presents a new adaptive antenna-array structure using CMA/fractional-delay sequential blind beamforming for multipath correlated signals in environments, such as indoor, confined or underground areas where the multipath problem is more severe than the co-channel interference. The new receiver uses a new synchronization approach for multipath propagation, based on combining a CMA adaptive antenna array and an adaptive fractional time delay estimation filter. This approach is designed to sequentially recover multipath rays based on adaptive time delay estimation for fractional time path arrival delays. The bit-error rate is evaluated for different operating conditions. Simulation results show the promising performance of the new adaptive antenna-array structure

The location of people, mobile terminals and equipment is highly desirable for operational enhancements in the mining industry. In an indoor environment such as a mine, the multipath caused by reflection, diffraction and diffusion on the rough sidewall surfaces, and the non-line of sight (NLOS) due to the blockage of the shortest direct path between transmitter and receiver are the main sources of range measurement errors. Unreliable measurements of location metrics such as received signal strengths (RSS), angles of arrival (AOA) and times of arrival (TOA) or time differences of arrival (TDOA), result in the deterioration of the positioning performance. Hence, alternatives to the traditional parametric geolocation techniques have to be considered. In this paper, we present a novel method for mobile station location using wideband channel measurement results applied to an artificial neural network (ANN). The proposed system, the wide band neural network-locate (WBNN-locate), learns off-line the location 'signatures' from the extracted location-dependent features of the measured channel impulse responses for line of sight (LOS) and non-line of sight (NLOS) situations. It then matches on-line the observation received from a mobile station against the learned set of 'signatures' to accurately locate its position. The location accuracy of the proposed system, applied in an underground mine, has been found to be 2 meters for 90% and 80% of trained and untrained data, respectively. Moreover, the proposed system may also be applicable to any other indoor situation and particularly in confined environments with characteristics similar to those of a mine (e.g. rough sidewalls surface).

We present a position-based resource allocation algorithm and evaluate the gain of zone division by a simulator that realistically replicates the imperfect operations of a real system. I he positions are important in the sense of how they affect the level of interference in adjacent cells (or sectors), and is a function of the distance to adjacent base stations (BSs) and the shadowing effects of the propagation environment. The queued packet algorithm (QPA) introduced here from [E.C. Haddad, 2002] is based on the occupancy of virtual queues for users grouped in zones where the resource requirements may be considered as similar. We evaluate the gain of a 4-zone division versus a 2-zone division for an assignment region at capacity for various propagation conditions and mobile distributions in the system. We consider stable operation of the system with long-term fairness achieved between users in different zones of the same cell. We show that the capacity gain of 4-zone division ranges between 8% and 15% compared to the 2-zone division.

This paper presents comprehensive experimental results obtained from narrowband and wideband radio channel measurements in an underground mine with narrow veins at 2.4 GHz. From CW measurement data, large-scale distance-power curves and path-loss exponents of the environment are determined. Other relevant parameters such as mean excess delay, maximum excess delay and rms delay spread are extracted from wideband measurement data. Results show a propagation behavior that is specific for these underground environments with rough surfaces.

This paper introduces and analyses a novel medium access control protocol for reverse links in wideband direct-sequence code-division multiple-access (DS-CDMA) mobile systems. The proposed protocol is particularly efficient when data consists of short packets. The new MAC protocol uses the time taken by the receiver to process the packets (the processing delay) to admit a new packet. When packet arrival is assumed to be Poisson, analysis and simulations show consistently that, for short packets, the new MAC scheme can handle a higher arrival rate than the conventional one, in which the processing delay is not used. The new MAC scheme shows only slight throughput degradation, a high utilization of the packet-switched data channel, and achieves a fair treatment of mobile stations.

We present the propagation characteristics at 2.45 and 18 GHz resulting from the statistical analysis of a narrowband measurement campaign in an underground mining environment. Parameters, such as the amplitude distribution of the envelope, level crossing rate, average fade duration and coherence time of the channel, have been examined. An analysis by linear regression has also been used to study the variations of the received power according to the transmitter-receiver distance.

This letter presents an efficient and accurate performance evaluation method for binary MC-CDMA systems with deterministic signature sequences. This method is based on a formulation of the characteristic function, and does not resort to any assumption on the statistical or spectral behavior of the interference. The accuracy of the Gaussian approximation method is also considered.

In order to explore design alternatives for point-to-multipoint high rate data transmission systems in various UHF and SHF bands, experimental measurements of radio propagation were made in urban and suburban areas. This paper reports on extensive continuous wave (CW) and wideband measurements performed at four carrier frequencies: 1.44275 GHz, 6.7 GHz, 14.72 GHz and 22.025 GHz. Measurements were carried out in the Montreal metropolitan and suburban areas with both transmitter and receiver stationary. The transmitter was located outside on the rooftop of a high rise building and the receiver inside another building. The receiver was then moved for each new set of measurements such that a whole room was covered in a grid-like fashion. Results from the temporal experiments show, that for the suburban area, the amplitude distributions are lognormal-distributed. The urban area presents more Ricean-distributed amplitude data. The data for the spatially-distributed case also showed that for the suburban and urban areas, the local means of the fluctuations are well described by a Nakagami distribution.

This paper presents a quick and accurate performance evaluation technique for direct-sequence spread-spectrum multiple-access (DS-SSMA) systems with deterministic signature sequences over Rician flat-fading and frequency-selective fading channels (with RAKE receivers), without resorting to any assumptions with respect to the distribution of the multiple-access interference (MAI). The method is based on a reduced-complexity formulation of the characteristic function method and its computational complexity is simply proportional to the spreading gain thus rendering it attractive for the study of future wideband CDMA systems. The paper also presents novel results with respect to the accuracy of a Gaussian approximation of MAI as a function of various channel and system parameters. It is notably observed that the type of signature sequence has a strong influence on the Gaussian approximation's accuracy which can degrade severely under a variety of conditions (e.g. with Walsh sequences over frequency-selective fading channels) even for a moderate to large number of users.

This paper presents a comparative evaluation of code-division-multiple access (CDMA) and frequency-division time-division-multiple-access (FD-TDMA) system capacities as a function of the radio link capacity (i.e. Shannon bound). This bound is first evaluated over time-varying frequency-selective fading channels by treating this information theoretic value of the capacity as a random variable. The total system sum-of-rates capacity is then evaluated for both multiple-access schemes using a multi-cell simulator and the 99% reliability level of the radio link capacity. System capacity is compared as a function of the number of cells per cluster and the use of power control in the FD-TDMA system, the spreading gain in the CDMA system, the receiver space diversity level, the number of channel multipath components as well as large-scale propagation parameters such as the shadowing standard deviation and the path-loss exponent. According to this methodology, it is observed that CDMA system capacity can be but is not always superior to FD-TDMA capacity. The spectral efficiency advantage (in terms of capacity per unit bandwidth) of CDMA over FD-TDMA systems is however much larger for larger spreading gains.

The primary objective of this paper is to estimate the capacity of a frequency-selective fading mobile radio channel used to communicate between N mobile units and a base station operating in space diversity and where M/spl ges/N. In general, the information theoretic value of the capacity of such a channel is not well defined because of the time-varying nature of the fading process. At best, the value of the capacity may be seen as a random variable evolving in time and whose distribution can be evaluated. The approach which has been followed in estimating the capacity uses a quasi-static model which computes the distribution over a large class of time dispersive possible realizations of the channel. Our final estimate of the numerical value of the capacity is based on the determination of an outage value corresponding to the 99% point on the cumulative distribution function. Our main result shows that a significant increase in the value of the capacity can be obtained by exploiting the inherent multipath diversity of the channel.>

In order to make the analytical evaluation of portable radio link performance tractable while avoiding lengthy simulations, intersymbol interference and cochannel interference are often modeled as non-fading, Gaussian noise. This paper investigates the viability of such an approach for wideband channels where equalization and space diversity are used to combat interference and signal fading. Comparisons of results obtained using such an assumption of interference with those of a simulation-based approach indicate that as long as the number of cochannel interferers is smaller than the space diversity order, the variance of the Gaussian interfering symbols can be adjusted to provide a reasonable estimate of performance over error rates of interest.>

Bidirectional suboptimal breadth-first decoding of convolutional codes is an attractive technique for slowly-varying and quasistatic fading channels as it restricts the extent of decoding errors due to correct path loss to very heavy noise or interference regions. The paper compares the performance of such a decoding scheme to the Viterbi algorithm over wideband TDMA indoor radio links where equalization and space diversity are also used to combat dispersive fading and cochannel interference. It is shown that, with dual space diversity, Viterbi decoding and bidirectional decoding of convolutional codes are both attractive alternatives, in terms of outage rate, to increasing the space diversity order from two to three. On the basis of equal computational complexity, bidirectional decoding is also shown to be superior to Viterbi decoding. Furthermore, this advantage increases as the bit error rate performance criterion becomes more stringent which makes bidirectional decoding particularly attractive for data applications.>

Compound strategies of equalization and space diversity in the form of an optimum baseband combiner are attractive for wide-band time division multiple access (TDMA) portable communication radio links in order to combat dispersive fading and cochannel interference. This paper investigates the performance of such a scheme in conjunction with convolutional coding and soft-decision Viterbi decoding via a semi-analytical technique based on the method of moments. Such an approach avoids a Gaussian characterization of interference and yields results for both ideal interleaving and no interleaving. With dual space diversity, three taps per forward filter and a data rate of 10 Mb/s, it is shown that, although a third space diversity branch remains preferable in terms of performance, channel coding can be a viable alternative, particularly in terms of outage rate, to increasing the space diversity order even in the absence of interleaving provided the signal-to-interference ratio is sufficiently high