In this paper, we derive the Cramer-Rao lower bound (CRLB) for a newly developed approach for direction of arrival (DoA) estimation in hybrid analog/digital (HAD) receivers under snapshot constraints. In such cases, the inherent structure of the received signals can be exploited for reliable DoA estimation rather than using statistical averaging techniques. One approach to exploit this structure is the matrix pencil method (MPM). Unfortunately, existing HAD receivers tangle the signals at the output of the HAD receiver, hindering the direct use of the MPM. To address this difficulty, an approach developed in [1] enables the MPM to expose the structure of the output signal of the analog combiner by leveraging periodic, potentially unknown signals to disentangle the output of the HAD receiver. We derive the CRLB for this approach and show that it yields output signals resembling those of a fully-digital receiver, albeit with a snapshot penalty. Numerical simulations show that the developed approach achieves performance within a small gap of the corresponding CRLB and outperforms existing counterparts.

Refractive metasurfaces (RMTSs) offer a promising solution to improve energy efficiency of wireless systems. To address the limitations of single-layer RMTSs, stacked intelligent metasurfaces (SIMs), which form the desired precoder and combiner in the wave domain, have been proposed. However, previous analyses have overlooked hardware non-idealities that significantly affect SIM performance. In this paper, we study the achievable sum-rate of SIM antennas in an uplink scenario, accounting for hardware constraints. We propose a system model that includes noise and hardware effects, formulate a non-convex sum-rate optimization problem, and solve it using gradient ascent and interior point methods. We compare SIMs and digital phased arrays (DPAs) under Rayleigh fading and 3GPP channels with two conditions: an equal number of$\mathbf{R F}$chains and an equal physical aperture size. Our results show SIMs outperform DPAs under equal number of RF chains but underperform DPAs with equal aperture size.

We propose a low-complexity downlink channel covariance matrix estimation for massive multiple-input multiple-output systems in which the base station (BS) is equipped with a uniform rectangular antenna array (URA). This scheme can be expressed in the form of an affine transformation which depends only on the uplink and downlink carrier frequencies, and the BS array configurations. An upper bound on the estimation error is derived, which shows that the accuracy of the proposed scheme increases with the number of URA antennas and the compactness and differentiability class of the periodic extension of a non-linearly transformed version of the angular power spread. The performance superiority of the proposed scheme over its existing counterparts is confirmed through simulations.

Massive multiple-input multiple-output (MIMO) systems, wherein a massive number of antennas are deployed at the base stations, are expected to play a significant role in 5G networks. The drawback of using the massive MIMO technique is the need for advanced and complex signal processing schemes. In recent years, several iterative and learning-based techniques have been introduced to address the need for low-complexity signal detection in the uplink of a massive MIMO system. The complexity of the iterative methods is highly affected by the number of needed iterations. On the other hand, although the performance of low-complexity learning-based techniques is close to optimal, they need retraining after major changes in the wireless communication channel. In this paper, we introduce Hint, a robust learning-based technique that finds an initial vector tailored for the current realization of the wireless channel; this vector initializes the iterative detector to complete the task of massive MIMO detection.

With the introduction of Advanced Antenna Systems (AAS) in cellular communication technologies, such as LTE and NR, the same resource can be allocated simultaneously to multiple users via spatial multiplexing. However, this raises new challenges to resource allocation strategy to decide opportunistic co-scheduling on a given resource to increase the system capacity without adversely impacting the user fairness. In addition, the effects of transmit power sharing and inter-user interference on co-scheduling need to be considered in the allocation decision. In this paper, a generic framework for resource allocation considering all these aspects of Multi-User Multi-Input Multi Output (MU-MIMO) in cellular Orthogonal Frequency Division Multiple Access (OFDMA) systems is presented and a scheduling algorithm for optimum resource allocation is provided. The performance of the proposed algorithm is evaluated for a two dimensional AAS using SCM-5G channel model.

Agile networking can reduce over-engineering, costs, and energy waste. Toward that end, it is vital to exploit all degrees of freedom of wireless networks efficiently, so that the service quality is not sacrificed. In order to reap the benefits of flexible networking, we propose a spatial network configuration (SNC) scheme, which can result in efficient networking; both from the perspective of network capacity and profitability. First, the SNC utilizes the drone-base-stations (drone-BSs) to configure access points. Drone-BSs are shifting paradigms of heterogeneous wireless networks by providing radically flexible deployment opportunities. On the other hand, their limited endurance and potential high cost increase the importance of utilizing drone-BSs efficiently. Therefore, second, user mobility is exploited via user-in-the-loop (UIL), which aims at influencing users' mobility by offering incentives. The proposed uncoordinated SNC is a computationally efficient method, yet, it may be insufficient to exploit the synergy between the drone-BSs and UIL. Hence, we propose a joint SNC, which increases the performance gain along with the computational cost. Finally, the semi-joint SNC combines the benefits of the joint SNC with computational efficiency. The numerical results show that the semi-joint SNC is two orders of magnitude faster than the joint SNC, and a profit of more than 15% can be obtained compared to conventional systems.

In this paper, we characterize the degrees of freedom (DoF) region of a MIMO device-relaying cellular network (DRCN) with three users and one base station (BS), where each user exchanges unicast messages with the BS. We assume that one of the users has no direct link to the BS, and hence, device-relaying is utilized to exchange data between this user and the BS, i.e., data is relayed via another user which has a direct link to the BS and a device to device (D2D) link to this user. We assume that each node operates in perfect full-duplex mode. Cut-set and genie-aided bounds are utilized to derive an outer bound on the DoF region. We provide achievability schemes that utilize signal space alignment for network coding, null-space beamforming and zero-forcing. The achievable schemes provide an inner bound on the DoF region that coincides with the outer bound.

This paper investigates the weighted sum degrees of freedom (DoF) of the MIMO Y channel that consists of three users, where the j-th user is equipped with Mjantennas, and a relay equipped with N antennas. In this network, each user conveys two private messages to the other two users in addition to a common message directed to both of them. As there is no direct link between the users, communication occurs through the relay. We define a weighted sum DoF metric that integrates all the network messages and weights the common message by a factor of α. Then, we study the weighted sum DoF maximization problem for α ≥ 0. Specifically, we show that the weighted sum DoF of the network, with M1≥ M2≥ M3, is given by min{2N, 2M2+ 2M3, M1+ M2+ M3}, for 0 ≤ α ≤ 4/3. While, for 4/33) + 3α/2 M3, 2(2N - M2- M3) + 3α/2 (M2+ M3- N), (6N - 2(M1+ M2+M3))+ 3α/2 (M1+ M2+ M3-2N), 2M2+ 2M3, M1+ M2+ M3}, and finally, for α > 2, the weighted sum DoF is equal to min{3α/2 N, α/2 (2N + M3), 2(N - 3/2M3) + 2αM3, α/2 (N + M2+ M3), N + M2- 3M3+ 2αM3, α/2 (M1+ M2+ M3), M1+ M2- 3M3+ 2αM3, 2(M2- M3) + 2αM3}. Achievability of the sum DoF is shown by using signal space alignment for network coding in the uplink phase, and zero-forcing precoding in the downlink phase.

The ability of physical layer relay caching to increase the degrees of freedom (DoF) of a single cell was recently illustrated. In this paper, we extend this result to the case of multiple cells in which a caching relay is shared among multiple non-cooperative base stations (BSs). In particular, we show that a large DoF gain can be achieved by exploiting the benefits of having a shared relay that cooperates with the BSs. We first propose a cache-assisted relaying protocol that improves the cooperation opportunity between the BSs and the relay. Next, we consider the cache content placement problem that aims to design the cache content at the relay such that the DoF gain is maximized. We propose an optimal algorithm and a near-optimal low-complexity algorithm for the cache content placement problem. Simulation results show significant improvement in the DoF gain using the proposed relay-caching protocol.

Device-to-Device (D2D) communications have been highlighted as one of the promising solutions to enhance spectrum utilization of LTE-Advanced networks. In this paper, we consider a D2D transmitter cooperating with a cellular network by acting as a relay to serve one of the cellular users. We consider the case in which the D2D transmitter is equipped with an energy harvesting capability. We investigate the trade-off between the amount of energy used for relaying and the energy used for decoding the cellular user data at the relaying node. We formulate an optimization problem to maximize the cellular user rate subject to a minimum rate requirement constraint for the D2D link. Moreover, we consider the case when receiving nodes are equipped with successive interference cancellation (SIC) capability and investigate the effect of using SIC on our proposed system performance. Finally, we show via numerical simulations the benefits of our cooperation-based system as compared to the non-cooperative scenario.

In this paper, experimental measurements of the received signal strength in a smart home test bed are presented. The measurements are used to develop a topology-independent probabilistic indoor path loss model. The proposed path loss model adds a random loss component to the log-distance path loss model to account for wall penetration, reflection, scattering, and diffraction effects. The proposed model is incorporated into the network simulator ns-3 to simulate IEEE 802.11 and IEEE 802.15.4 networks. Our results indicate that the throughput of both networks degrades as the density of the nodes increases due to increasing the connectivity of the interference links.

In this paper, a novel adaptive physical-layer identity detection algorithm for LTE systems is presented. The proposed algorithm can estimate the location of the primary synchronization signal (PSS) and detect the physical-layer identity in the presence of jamming or interference. Multiple parallel adaptive filters are used to suppress the jamming signal without using any a priori information about its characteristics. Each filter is designed using the linearly constrained minimum variance (LCMV) criterion to minimize the output corresponding to any received signal that does not match the signature of the PSS. The frequency response of the adaptive filters at the PSS timing detection instant is used to suppress the interference/jamming signal during physical-layer identity estimation. Simulation results are presented to illustrate the superior performance of the proposed algorithm compared to earlier non- adaptive PSS detection algorithms.

We consider the problem of optimizing the performance of a cooperative cognitive radio user subject to constraints on the quality-of-service (QoS) of the primary user (PU). In particular, we design the probabilistic admission control parameter of the PU packets in the secondary user (SU) relaying queue and the randomized service parameter at the SU under non-work-conserving (non-WC) and WC cooperation policies. In the non-WC policy, two constrained optimization problems are formulated; the first problem is maximizing the SU throughput while the second problem is minimizing the SU average delay. In both problems, a constraint is imposed on the maximum allowable average delay of the PU. We show the equivalence of the two problems and develop a low-complexity line search algorithm to find the optimal parameters. Subsequently, the idea of optimizing the SU average delay is developed for the more complex WC policy, for its superior resource utilization and performance. Due to the sheer complexity of this optimization problem, we formulate another problem whose solution yields a suboptimal upper bound on the optimal SU delay. Afterwards, a practical WC-policy-based algorithm is designed in order to closely approach the optimal value of the SU delay. We show, through numerical results, that the proposed cooperation policies represent the best compromise between enhancing the SU QoS and satisfying the PU QoS requirements. Furthermore, the superior performance of the suboptimal WC policy over the non-WC policy is illustrated. Finally, the merits of the WC-policy-based algorithm are demonstrated through extensive simulations.

In this paper, we characterize the total degrees of freedom (DoFs) of the full-duplex asymmetric multiple-input multiple- output (MIMO) three-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. We study this system under two message configurations; the first configuration is when each node has two unicast messages to be delivered to the two other nodes, while the second configuration is when each node has two unicast messages as well as one broadcast message to be delivered to the two other nodes. For each configuration, we first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterward, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes for each configuration are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming. We show that the derived outer and inner bounds on the total DoF are tight for each message configuration.

In this paper, we study the general multiple input multiple output (MIMO) multi-way relay channel, i.e., MIMO Y channel, with common and private messages. In this channel, K users exchange messages through a common relay. Each user transmits a private message to each user in addition to a common message to all the other users. The ith user and the relay are equipped with Miand N antennas, respectively. First, we derive the degrees of freedom (DoF) region of the symmetric three-user MIMO Y channel, where Mi= M and i ∈ (1,2,31. Due to the symmetry of the network, we focus on the case where the DoF of all private messages are equal and the DoF of all common messages are equal. In this case, the DoF region has two dimensions: the DoF of private messages and the DoF of common messages. We develop an outer bound on the DoF region based by using cut-set and one-sided genie bounds. We prove the achievability of the outer bound on the DoF region by using linear beamforming and signal space alignment (SSA) schemes. Second, based on our study of the DoF region of the symmetric channel, we define a weighted sum DoF metric that integrates all the network messages and weights the common messages by a factor of α. We study the weighted sum DoF maximization problem and show that sending common messages only is optimal when α exceeds 43. Next, we focus on the weighted sum DoF with α = 2 that represents the total number of received interference-free streams at the users. First, we show that the weighted sum DoF, with α = 2, of the MIMO Y channel with an arbitrary number of antennas is given by min(3N, 2N + M3, N + M2+ M3, 2M2+ 2M3, M1+ M2+ M3). Second, we study the weighted sum DoF, with α = 2, of the K-user case in the symmetric setting. We derive an outer bound on the weighted sum DoF using cut-set bounds, and show that the network has K min(N, M) weighted DoF. The achievability results are obtained by using SSA for network coding in the multiple access phase, and zero-forcing precoding in the broadcast phase.

In this paper, we consider a heterogeneous network composed of a full-duplex macrocell and a half- duplex femtocell. The macro-base station (BS) is equipped with L antennas where each antenna can be utilized either for downlink transmission or uplink reception. On the other hand, the femto-BS is equipped with M antennas that are used for downlink transmission. We assume that each user equipment has N antennas where L>M≥N. We investigate the benefit of using interference alignment for cross-tier and full-duplex interference management and present precoding schemes that are capable of achieving the total degrees of freedom of the network. We show that full-duplex operation of the macro-BS improves the degrees of freedom (DoF) of the system when M2N, otherwise half-duplex operation is optimal. Furthermore, the DoF of the system can be improved by 50\% via full-duplex macro-BS operation when M=N.

In this paper, we consider a multiple-access fading channel where N users transmit to a single base station (BS) within a limited number of time slots. We assume that each user has a fixed amount of energy available to be consumed over the transmission window. We derive the optimal energy allocation policy for each user that maximizes the total system throughput under two different assumptions on the channel state information. First, we consider the offline allocation problem where the channel states are known a priori before transmission. We solve a convex optimization problem to maximize the sum-throughput under energy and delay constraints. Next, we consider the online allocation problem, where the channels are causally known to the BS and obtain the optimal energy allocation via dynamic programming when the number of users is small. We also develop a suboptimal resource allocation algorithm whose performance is close to the optimal one. Numerical results are presented showing the superiority of the proposed algorithms over baseline algorithms in various scenarios.

Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and terrestrial channels cause the placement of the drone-cells to diverge from placement of terrestrial base stations. In this paper, we first highlight the properties of the drone-cell placement problem, and formulate it as a 3-D placement problem with the objective of maximizing the revenue of the network. After some mathematical manipulations, we formulate an equivalent quadratically-constrained mixed integer non-linear optimization problem and propose a computationally efficient numerical solution for this problem. We verify our analytical derivations with numerical simulations and enrich them with discussions which could serve as guidelines for researchers, mobile network operators, and policy makers.

In this paper, we characterize the asymmetric total degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) 3-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. Each node has two unicast messages to be delivered to the two other nodes. We first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterwards, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming.

In this paper we characterize the proactive diversity gain of a cognitive network with predictable primary and secondary requests. Network performance is analyzed under two proposed proactive service policies that preserve higher priority for the primary user. The first policy preserves the primary diversity bound as if there is no secondary user in the network, whereas the second policy boosts the secondary diversity with guaranteed higher primary diversity. For each policy, we derive diversity gain bounds for primary and secondary users. We show that the predictability of secondary requests can remarkably boost quality of service (QoS) of the secondary user compared to the previous literature when secondary requests are nonpredictable. We provide numerical simulations to validate our analytical findings and demonstrate performance merits.

In this paper, we compare the potential gain that can be obtained from separate-antenna full-duplex transceivers in cellular networks with that obtained from cooperative operation of half-duplex base stations. The gain is characterized in terms of the total degrees of freedom (DoF). In particular, we consider a system composed of two adjacent MIMO base stations. We consider a single time-frequency resource unit that is used by each base station to communicate with one MIMO user. For the full-duplex case, we assume that each node has a configurable transceiver that can allocate some antennas to the uplink and the remainder to the downlink. We provide an upper bound on the total DoF of the full-duplex system and derive the optimal antenna allocation at each node. We compare the derived upper bound for the full-duplex transceivers with the achievable DoF in the case of half-duplex cooperative multipoint transmission. Our results indicate that the achievable DoF in the cooperative case is always greater than or equal to the upper bound on the DoF of the full-duplex system. We further investigate the case of full-duplex cooperative multipoint transmission and show that the maximum DoF gain due to full-duplex operation cannot exceed 12.5% of the DoF of the half-duplex cooperative system.

In this paper, proactive resource allocation based on user location for point-to-point communication over fading channels is introduced, whereby the source must transmit a packet when the user requests it within a deadline of a single time slot. We introduce a prediction model in which the source predicts the request arrival Tpslots ahead, where Tpdenotes the prediction window (PW) size. The source allocates energy to transmit some bits proactively for each time slot of the PW with the objective of reducing the transmission energy over the non-predictive case. The requests are predicted based on the user location utilizing the prior statistics about the user requests at each location. We also assume that the prediction is not perfect. We propose proactive scheduling policies to minimize the expected energy consumption required to transmit the requested packets under two different assumptions on the channel state information at the source. In the first scenario, offline scheduling, we assume the channel states are known a-priori at the source at the beginning of the PW. In the second scenario, online scheduling, it is assumed that the source has causal knowledge of the channel state. Numerical results are presented showing the gains achieved by using proactive scheduling policies compared with classical (reactive) networks. Simulation results also show that increasing the PW size leads to a significant reduction in the consumed transmission energy even with imperfect prediction.

We consider a cooperative relaying system with any number of source terminals, one shared relay, and a common destination. We assume a slotted time division multiple access (TDMA) framework in which each source terminal is allocated a fraction of the time. We propose a novel hybrid cooperative scheme for the described network. In contrast to former works which assume that the relay only transmits in the idle time slots, we assume that the relay can, simultaneously, transmit with the source terminals via multi-access channel (MAC). In hybrid cooperative scheme, the relay operates in two modes each with a certain probability; the TDMA mode and the MAC mode. We derive expressions for the stability conditions and the average delay for all the queues in the network. We design the probability of each relaying mode such that the stable throughput is maximized while the network queues are stable. The problem is formulated as a non-convex quadratic constrained quadratic programming (QCQP) optimization problem. Numerical results reveal that the hybrid cooperative scheme significantly enhances the performance of the network in terms of stability region, average delay, and spectral efficiency.

Channel state information at the transmitter affects the degrees of freedom of the wireless networks. In this paper, we analyze the DoF for the K-user multiple-input single-output (MISO) broadcast channel (BC) with synergistic alternating channel state information at the transmitter (CSIT). Specifically, the CSIT of each user alternates between three states, namely, perfect CSIT (P), delayed CSIT (D) and no CSIT (N) among different time slots. For the K- user MISO BC, we show that the total achievable degrees of freedom (DoF) are given by K2/(2K-1) through utilizing the synergistic benefits of CSIT patterns. We compare the achievable DoF with results reported previously in the literature in the case of delayed CSIT and hybrid CSIT models.

We study the problem of optimizing the performance of cognitive radio users with opportunistic real-time applications subject to primary users quality-of-service (QoS) constraints. Two constrained optimization problems are formulated; the first problem is maximizing the secondary user throughput while the second problem is minimizing the secondary user average delay, subject to a common constraint on the primary user average delay. In spite of the complexity of the optimization problems, due to their non-convexity, we transform the first problem into a set of linear programs and the second problem into a set of quasiconvex optimization problems. We prove that both problems are equivalent with identical feasible sets and optimal solutions. We show, through numerical results, that the proposed cooperation policy represents the best compromise between enhancing the secondary users QoS and satisfying the primary users QoS requirements.

We consider a cognitive radio system that consists of primary user, secondary user, and their destinations. The secondary user has a relaying capability, i.e., it transmits the relayed packets from the primary user. Unlike most of the previous works that restrict the secondary user to transmit only in the idle time slots, we assume that the secondary user interferes on the primary user with certain probability that is optimized to maximize the stable throughput of the secondary network under certain level of quality of service constraints for the primary one. We show how significantly our proposed scheme improves the performance of the secondary user and increases the maximum stable throughput of the primary user over the traditional cooperative policies that restrict the secondary user to exploit only the periods of silence of the primary user.

Abstract In this paper, we consider a cognitive scenario where an energy harvesting secondary user shares the spectrum with a primary user. The secondary source helps the primary source in delivering its undelivered packets during periods of silence of the primary source. The primary source has a queue for storing its data packets, whereas the secondary source has two data queues: a queue for storing its own packets and the other for storing the fraction of the undelivered primary packets accepted for relaying. The secondary source is assumed to be a battery‐based node, which harvests energy packets from the environment. In addition to its data queues, the secondary user has an energy queue to store the harvested energy packets. The secondary energy packets are used for primary packets decoding and data packets transmission. More specifically, if the secondary energy queue is empty, the secondary source can neither help the primary source nor transmit a packet from the data queues. The energy queue is modeled as a discrete‐time queue with Markov arrival and service processes. Because of the interaction of the queues, we provide inner and outer bounds on the stability region of the proposed system. We investigate the impact of the energy arrival rate on the stability region. Numerical results show the significant gain of cooperation.Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, we investigate the degrees of freedom (DoF) of the two-user single input single output (SISO) X channel with alternating channel state information at the transmitters (CSIT). Three cases are considered for the availability of CSIT; perfect, delayed and no-CSIT. Each state is associated with a fraction of time denoted by λP, λDand λN, respectively. We provide new results for the achievable DoF of the channel when the available CSIT alternates between these three cases under a certain distribution for Λ(λP, λD, λN). Specifically, we show that the two-user SISO X channel with alternating CSIT for Λ(1/8, 3/8, 1/2) can achieve 5/4 DoF. The achieved DoF in this case lie between the maximum DoF of the channel, i.e., 4/3 DoF for Λ(1, 0, 0), and the 6/5 DoF achieved for Λ(0, 1, 0).

We study the impact of a full-duplex secondary node on a cognitive cooperative network with Multipacket Reception (MPR) capabilities at the receivers. Motivated by recent schemes that make full-duplex communication feasible, we study a model with one primary and one secondary transmitter-receiver pair, where the secondary transmitter is able to relay primary unsuccessful packets. Cooperation between primary and secondary users has been previously shown to be beneficial for the primary and the secondary users in terms of stable throughput. Our model assumes an imperfect full-duplex secondary node that can transmit and receive simultaneously, cancelling self-interference to a certain extent. Furthermore, we assume that the secondary transmitter chooses between cooperating with the primary user and transmitting secondary packets probabilistically according to some optimized probabilities that depend on both the channels in the network and the state of the primary user. We determine these probabilities by formulating a constrained optimization problem with the secondary throughput as the objective function and the stability of the primary queues as constraints. Using the dominant system approach, we show that the optimization problem has a quasi-concave structure, to which the optimal solution can be easily found. Using Numerical results, we characterize the cases where the full-duplex capability is beneficial to the system, namely, we show that the full-duplex secondary node greatly increases both the secondary throughput and the primary maximum stable throughput in channels with receivers that have strong MPR capability.

We investigate the degrees of freedom (DoF) of the downlink of a cellular relay network. In this network, two base stations transmit to two mobile stations via relays due to the absence of a direct communication link. Each base station and mobile station is equipped with $M$ antennas. Each base station has two messages; one to each mobile station, and uses two relays to transmit to the mobile stations. The relays are half duplex, decode-and-forward and equipped with $N$ antennas each. We consider two configurations of the relays; shared and dedicated relays. In the shared relays configuration, the system has two relays that are used by both base stations. Whereas, in the dedicated relays configuration, each base station has two dedicated relays, i.e., the system has four relays. We consider all possible relaying schemes where the base stations can use the relays either simultaneously or alternately. We derive an upper bound on the DoF achievable by each relaying scheme as a function of the ratio between $N$ and $M$. Furthermore, we propose an achievable scheme that uses interference alignment to achieve the upper bound on the DoF for the shared relays configuration, and for all values of $M$ and $N$ except for $1<;\frac{N}{M}<;\frac{5}{2}$ in the dedicated relays configuration.

In this paper we investigate the degrees of freedom of a cellular relay network that consists of two base stations, two mobile stations and four decode-and-forward relays. The base stations and the mobile stations are equipped with M antennas each, whereas the relays are equipped with N antennas each. In addition, each base station has an independent message to each mobile station. The relays are used to froward the messages from the base stations to the mobile station as there is no direct link. We consider three different relaying architectures where the two relays associated with each base station simultaneously or alternately transmit their messages. We derive an upper bound on the degrees of freedom achievable by each relaying architecture as a function of the ratio between N and M. Furthermore, we propose an achievable scheme that uses interference alignment to achieve the upper bound on the DoF for all values of M and N except for 1 ≤ N/M ≤ 5/2.

We study a cognitive radio system where the secondary users can relay the unsuccessful packets of the primary user. We study a model with one primary link and two secondary links with Multipacket Reception capability (MPR) added to the receivers. Secondary users relaying the primary unsuccessful packets are shown to increase the primary maximum stable throughput and increase the secondary user transmission opportunities. MPR capability is shown to further increase the secondary transmission opportunities as the secondary users can relay with a rate higher than 1 packets/slot as opposed to conventional relaying schemes. Our goal is to control the relaying procedure in secondary nodes such that the secondary transmission opportunities are maximized. We formulate this problem as a constrained optimization problem and then transform it to a linear programming problem. We derive an approximation for the probability of primary idle slots which translates to secondary transmission opportunities, as well as lower and upper bounds for the primary maximum stable throughput. Results show that under some channel conditions, the MPR relaying scheme can outperform other conventional relaying schemes in terms of secondary throughput.

In this paper, the degrees of freedom (DoF) of the two-user single input single output (SISO) X channel are investigated. Three cases are considered for the availability of channel state information at the transmitters (CSIT); perfect, delayed, and no-CSIT. A new achievable scheme is proposed to elucidate the potency of interference creation-resurrection (IRC) when the available CSIT alternates between these three cases. For some patterns of alternating CSIT, the proposed scheme achieves 4/3 DoF, and hence, coincides with the information theoretic upper bound on the DoF of the X channel with perfect and instantaneous CSIT. The CSIT alternation patterns are investigated where the patterns that provide extraordinary synergistic gain and dissociative ones are identified.

In this paper, we study the problem of cooperative communications in cognitive radio systems where the secondary user has limited relaying room for the overheard primary packets. More specifically, we characterize the stable throughput region of a cognitive radio network with a finite relaying buffer at the secondary user. Towards this objective, we formulate a constrained optimization problem for maximizing the secondary user throughput while guaranteeing the stability of the primary user queue. We consider a general cooperation policy where the packet admission and queue selection probabilities, at the secondary user, are both dependent on the state (length) of the finite relaying buffer. Despite the sheer complexity of the optimization problem, attributed to its non-convexity, we transform it to a linear program. Our numerical results reveal a number of valuable insights, e.g., it is always mutually beneficial to cooperate in delivering the primary packets in terms of expanding the stable throughput region. In addition, the stable throughput region of the system, compared to the case of infinite relaying queue capacity, marginally shrinks for limited relaying queue capacity.

In this paper, a platform for measuring the impulse response of wireless multiple-input-multiple-output (MIMO) vehicle-to-vehicle (V2V) channels is presented. The platform is developed using Rice University Wireless Open-Access Research Platform (WARP) boards and utilized to perform an experimental study of V2V channels through conducting field measurements. A full characterization of MIMO-V2V channels is given via extracting the channel parameters from the acquired measurements. These parameters include the power-delay profile, the Doppler spectrum, and the MIMO transmit and receive correlation matrices of the channel. Numerical simulations are utilized to examine the effect of the channel parameters on the bit error rate (BER) performance of an orthogonal frequency division multiplexing (OFDM) based system.

In this paper, a multiple-access wireless network consisting of two transmitters and one receiver is considered. The transmitters can access the same channel simultaneously and the receiver performs successive interference cancellation (SIC) to decode the messages from both senders. A two-dimensional Markov chain is used to model the medium access control layer behavior of the system, where the state represents the queue length of the transmitters. In this model a general number of packets can be transmitted from any user in a single time slot. A probabilistic cross-layer scheme is proposed to regulate the transmission process between both senders and the receiver. The proposed scheme probabilistically selects the number of packets transmitted from each user and the SIC decoding order at the receiver in order to achieve minimum total average packet delay while satisfying the power constraints for each transmitter. The problem is formulated as a constrained optimization problem then transformed it to a set of convex feasibility problems that can be solved efficiently using the bisection algorithm.

A novel transmission scheme is developed for the downlink frame of cellular networks. Each base station (BS) aims at iteratively balancing the throughput at the mobile stations (MSs) of its cell with the interference it causes at the MSs of the neighboring cells, requiring negligible coordination between the BSs. A simplified version of the scheme that neither requires iterations nor cooperation is also proposed. Simulation results show that the proposed schemes achieve substantial gains over well-known schemes in the literature.

In this paper, an iterative blind estimator for fractional carrier frequency offset (CFO) in orthogonal frequency division multiplexing (OFDM) systems is proposed. The estimator utilizes the null subcarriers transmitted at the edge of the spectrum and does not require any training. In addition, the proposed estimator does not require any prior knowledge of the frequency response of the channel. The problem is formulated using a state-space model, and an extended Kalman filter (EKF) is employed to estimate the CFO iteratively. Simulation results illustrate the enhanced ability of the proposed algorithm, relative to the existing approaches, to estimate and track the CFO even in the presence of high Doppler.

In this paper, we study the performance of the downlink of a cellular network with automatic repeat-request (ARQ) and a half duplex decode-and-forward shared relay. In this system, two multiple-input-multiple-output (MIMO) base stations serve two single antenna users. A MIMO shared relay retransmits the lost packets to the target users. First, we study the system with direct retransmission from the base station and derive a closed form expression for the outage probability of the system. We show that the direct retransmission can overcome the fading, however, it cannot overcome the interference. After that, we invoke the shared relay and design the relay beamforming matrices such that the signal-to-interference-and-noise ratio (SINR) is improved at the users subject to power constraints on the relay. In the case when the transmission of only one user fails, we derive a closed form solution for the relay beamformers. On the other hand when both transmissions fail, we pose the beamforming problem as a sequence of non-convex feasibility problems. We use semidefinite relaxation (SDR) to convert each feasibility problem into a convex optimization problem. We ensure a rank one solution, and hence, there is no loss of optimality in SDR. Simulation results are presented showing the superior performance of the proposed relay beamforming strategy compared to direct ARQ system in terms of the outage probability.

The recent witnessed evolution of cellular networks from a carefully planned deployment to more irregular, heterogeneous deployments of Macro, Pico and Femto-BSs motivates new analysis and design approaches. In this paper, we analyze the coverage probability in cellular networks assuming repulsive point processes for the base station deployment. In particular, we characterize, analytically using stochastic geometry, the downlink probability of coverage under a Matern hardcore point process to ensure minimum distance between the randomly located base stations. Assuming a mobile user connects to the nearest base station and Rayleigh fading, we derive two lower bounds expressions on the downlink probability of coverage that is within 4% from the simulated scenario. To validate our model, we compare the probability of coverage of the Matern hardcore topology against an actual base station deployment obtained from a public database. The comparison shows that the actual base station deployment can be fitted by setting the appropriate Matern point process density.

A cognitive network is considered that consists of a base station (BS) communicating with multiple primary and secondary users. Each secondary user can access only one of the orthogonal primary channels. A model is considered in which the primary users can tolerate a certain average delay. A special case is also considered in which the primary users do not suffer from any delay. A novel cross-layer scheme is proposed in which the BS performs successive interference cancellation and thus a secondary user can coexist with an active primary user without adversely affecting its transmission. A scheduling algorithm is proposed that minimizes the average packet delay of the secondary user under constraints on the average power transmitted by the secondary user and the average packet delay of the primary user. A resource allocation algorithm is also proposed to assign the secondary users' channels such that the total throughput of the network is maximized. Our results indicate that the network throughput increases significantly by increasing the number of transmitted packets of the secondary users and/or by allowing a small delay for the primary user packets.

The widespread usage of WLANs and mobile devices has fostered the interest in localization systems for wireless environments. The majority of research in the context of wireless-based localization systems has focused on device-based active localization, in which devices are attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor to participate actively in the localization process. Previous studies have focused on small areas and/or controlled environments. In this paper, we present the design, implementation, and analysis of Nuzzer, a large-scale DfP localization system, which tracks entities in real environments, rich in multipath. We first present probabilistic techniques for DfP localization of a single entity and evaluate their performance both analytically and in typical office buildings. Our results show that Nuzzer gives location estimates with less than 2-meters median distance error. We then give an algorithm for estimating the number of entities in an area of interest and localizing them into coarse-grained zones to enhance the scalability of the system. This indicates the suitability of Nuzzer to a large number of application domains.

A cognitive network is considered in which a primary user and a secondary user are transmitting to a common receiver. Successive interference cancellation is performed at the common receiver to guarantee that no interference is experienced by the primary user. At the beginning of each time slot, the secondary user senses the channel of the primary user to determine if the primary user is active or idle. The sensing scheme is not perfect and thus there are nonzero probabilities of miss detection and false alarm. The secondary user transmits a variable number of packets in each time slot and the number of transmitted packets is determined via a probabilistic cross-layer algorithm which minimizes the average packet delay of the secondary user under an average power constraint. A constraint on the maximum collision probability is imposed to guarantee an acceptable quality of service for the primary user. The problem is shown to be quasi-convex, and thus, can be solved efficiently. Our results indicate that even with sensing errors, the throughput of the network increases significantly with increasing the number of transmitted packets. However this comes at the expense of increasing the average delay of the secondary user.

We study a cellular setting in which an introduced multiple-antenna relay station (RS) can possibly assist the bidirectional communication between a multiple-antenna base station (BS) and a set of single-antenna mobile stations (MSs). Through a proposed six-phase communication protocol with arbitrary number of antennas and MSs, we characterize the maximum number of degrees of freedom (DoF) that can be attained when the BS-MSs direct link is active or down. When the direct link is available, we show that the introduction of a multiple-antenna RS cannot increase the maximum DoF regardless of the number of antennas it is equipped with. In the absence of a BS-MSs direct link, the maximum DoF can be limited by the number of RS antennas since all ongoing communication takes place through the RS. It is also shown that the characterized maximum DoF is achieved via recently proposed network-coding based two-way relaying techniques. Finally, we conclude that a widely used two-phase multiple access/broadcast (MABC) two-way relaying protocol can be DoF-limiting in some cases due to its inherent inability to exploit the possibly available BS-MSs direct-link.

In this paper, the 3-user Gaussian MIMO interference channel with M antennas at each transmitter and N antennas at each receiver is considered. It is assumed that the channel coefficients are constant and known to all transmitters and receivers. A novel scheme is presented that spans a new achievable degrees of freedom region. For some values of M and N, the proposed scheme achieves higher number of DoF than those achieved by earlier schemes, while for other values it meets the best known upperbound. Simulation results are presented showing that the proposed schemes can achieve more DoF than earlier approaches.

Space frequency block coding with orthogonal frequency division multiplexing (SFBC-OFDM) suffers from the effect of inter-carrier interference (ICI) in doubly-selective communication channels. In this paper, a scheme is proposed in which windowing is applied to the received signal to reduce the effect of ICI to a limited number of neighboring sub-carriers. The sub-carriers holding the SFBC components of each codeword are separated by a number of sub-carriers larger than the ICI range, and hence, they do not interfere with each other. In order to preserve the structure of the SFBC, the separation between the codeword components is also selected within the coherence bandwidth of the channel. As a result, the diversity gain of the SFBC is preserved. A decision feedback equalizer is proposed to estimate the transmitted data symbols with low complexity. Simulation results are presented showing the ability of the proposed scheme to significantly improve the performance of SFBC-OFDM and preserve its diversity gain.

In this paper, we consider a cognitive relaying network in which the secondary user accesses the channel with a certain access probability that depends on the feedback information sent by the primary destination. In addition, the secondary user is granted relaying capabilities by which it can relay primary traffic that was unsuccessfully transmitted by the primary user. We show that this proposed scheme enhances the performance of the secondary user as well as the primary user, while the QoS requirements of the primary user is unviolated. The secondary user can avoid sure collisions with the primary transmissions exploiting the feedback information from the primary user. Also, due to the fact that relaying the unsuccessfully transmitted primary traffic increases the availability of the channel for its own packets, the secondary throughput is increased and the primary delay is decreased.

Human motion has strong impact on the received signal strength (RSS) of indoor wireless links that can be exploited for variance-based device-free positioning. In this paper, we investigate the effect of human motion on the variance of the RSS of wireless local area networks (WLAN) operating at 2.4 GHz. Using measurements, the RSS variance for human in-place motion is determined as a function of the human position in a corridor setting. We provide ray tracing and empirical models to capture this effect. The accuracy of the different models is compared under different scenarios. Furthermore, we investigate the effect of having multiple-entities in the same area of interest on the RSS variance and provide models for it.

In this paper, a multiuser cellular two-way relaying scenario is considered where multiple single-antenna mobile stations (MSs) and one multiple-antenna base station (BS) communicate, bidirectionally, via one half-duplex multiple-antenna relay station (RS). Furthermore, the case when the number of antennas at the RS is not sufficient to decode the individual messages is addressed. For this case, a two-phase two-way relaying scenario is considered. In the first phase, the multiple access, a minimum Mean Square Error (MSE) optimization problem is formulated which is found to be non-convex. Thus, an iterative scheme is proposed to compute the MS transmit powers, the BS beamforming vectors, and the corresponding RS linear receivers to minimize the maximum MSE for multiple pairs subject to power constraints on the transmitting terminals. In the second phase, the broadcast phase, the beamforming vectors at the RS are designed to minimize the maximum MSE at the MSs subject to relay power constraints, and the receivers at the BS are designed accordingly. In a two-pair scenario, simulation results are provided showing the superior performance of the proposed methods compared to earlier approaches in terms of the bit-error rate. Also, it is shown that as the system scales up in terms of signal space dimensions and number of accommodated pairs, the performance gap between the proposed scheme and the earlier approaches increases.

We consider a wireless communication scenario with K source-destination pairs communicating through several half-duplex amplify-and-forward relays. We design the relay beamforming matrices by minimizing the total power transmitted from all the relays subject to quality of service constraints on the received signal to interference-plus-noise ratio at each destination node. We propose a novel method for solving the resulting nonconvex optimization problem in which the problem is decomposed into a group of second-order cone programs (SOCPs) parameterized by K real parameters. Grid search or nested bisection can be used to search for the optimal values of these parameters. We provide numerical simulations showing the superior performance of the proposed algorithms compared to earlier suboptimal approximations and their ability to approach the globally optimal solution of the non-convex problem.

An interference alignment (IA) scheme is presented that allows multiple opportunistic transmitters (secondary users) to use the same frequency band of a pre-existing primary link without generating any interference. The primary and secondary transmit-receive pairs are equipped with multiple antennas. Under power constraints on the primary transmitter, the rate of the primary user is maximized by water-filling on the singular values of its channel matrix leaving some eigen modes unused, and hence, the secondary users can align their transmitted signals to produce a number of interference-free dimensions at each secondary receiver without causing any interference to the primary user. An outer bound is developed on the degrees of freedom (DoF) of the secondary users. In the case of a symmetric secondary network with time-varying channel coefficients havingMantennas at each node and operating in the presence of a primary link withd0active eigen modes, a precoding scheme is presented for the secondary transmitters that can asymptotically achieve the available (M-d0)+/2 DoF per secondary user. An iterative algorithm is also presented that utilizes channel reciprocity to achieve the proposed cognitive IA scheme. For a cognitive 3-user secondary network with constant channel coefficients, a novel closed-form solution is derived for the precoding matrices of the secondary users.

We investigate power allocation for users in a shared spectrum network. In such a network, the primary (licensed) users communicate under a minimum guaranteed quality of service (QoS) requirements, whereas the secondary users opportunistically access the primary band. Our objective is to find a power control scheme that determines the transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service of the primary users greater than a specified minimum limit. In the assumed model, no interference cancellation is done at the receivers resulting in a non-convex optimization problem. It has been shown previously that binary power control almost always achieves the global optimum solution when no QoS constraints are imposed. This is not necessarily the case in our scenario, however. We introduce a distributed algorithm for "ternary" power allocation to be used when individual measurements are available at each node. We show via simulations the relative efficiency of the proposed algorithm compared to previously suggested ones. If a central controller exists with available information about the system parameters, we enhance the performance of the proposed algorithm through an iterative geometric programming (GP) algorithm and prove its convergence to a better solution than ternary power allocation.

WLAN RSS-based localization has been a hot research topic for the last years. To obtain high accuracy in the noisy wireless channel, WLAN location determination systems usually use a calibration phase, where a radio map, capturing the signal strength signatures at different locations in the area of interest, is built. The radio map construction process takes a lot of time and effort, reducing the value of WLAN localization systems. In this paper, we propose 3D ray tracing as a way for automatically generating a highly accurate radio map. We compare this method to previously used propagation modeling-based methods like the Wall Attenuation Factor and 2D ray tracing models. We evaluate the performance of each method and its computational cost in a typical residential environment. We also examine the sensitivity of the localization accuracy to inaccurate material parameters. Our results quantify the accuracy- complexity trade-off of the different proposed techniques with 3D ray tracing giving the best localization accuracy compared to measurements with acceptable computational requirements on a typical PC.

In this paper, we consider a wireless communication scenario with multiple source-destination pairs communicating through several cooperative amplify-and-forward relay terminals. The relays are equipped with multiple antennas that receive the source signals and transmit them to the destination nodes. We develop two iterative relay beamforming algorithms that can be applied in real-time. In both algorithms, the relay beamforming matrices are jointly designed by minimizing the received power at all the destination nodes while preserving the desired signal at each destination. The first algorithm requires the existence of a local processing center that computes the beamforming coefficients of all the relays. In the second algorithm, each relay can compute its beamforming coefficients locally with the help of some common information that is broadcasted from the other relays. This is achieved at the expense of enforcing the desired signal preservation constraints non-cooperatively. We provide two extensions of the proposed algorithms that allow the relays to control their transmission power and to modify the quality of service provided to different sources. Simulation results are presented validating the ability of the proposed algorithms to perform their beamforming tasks efficiently and to track rapid changes in the operating environment.

A new method is proposed for the blind subspace-based identification of the coefficients of time-varying (TV) single-input multiple-output (SIMO) FIR channels. The TV channel coefficients are represented via a finite basis expansion model, i.e. linear combination of known basis functions. In contrast to earlier related works, the basis functions need not be limited to complex exponentials, and therefore do not necessitate the a priori estimation of frequency parameters. This considerably simplifies the implementation of the proposed method and provides added flexibility in applications. The merits of the proposed technique, including asymptotic consistency, are demonstrated by numerical simulations.

In this paper, we consider a cooperative relaying scenario with multiple sources transmitting to one or more destination nodes through several relay terminals. Each relay is equipped with multiple receive and transmit antennas. We assume that the relays can estimate their uplink (relay-destination) channels with enough accuracy and that they have access to the training sequences transmitted by the sources. We present two adaptive training-based algorithms for multiuser relay beamforming. Both algorithms use Kalman filtering to estimate the beamforming matrices iteratively. The first algorithm is centralized where the relay terminals forward their received data to a processing center that computes the beamforming coefficients and feeds them back to the relays. In the second algorithm, each relay terminal can estimate its beamforming matrix locally using its received data and some common information that is broadcasted by the other relays. We present numerical simulations that validate the good performance of the proposed beamforming algorithms in stationary and nonstationary signal environments.

In this paper, we develop a beamforming algorithm for multiuser MIMO-relaying wireless systems. We consider a relaying scenario with multiple sources transmitting to one or more destination nodes through several relay terminals. Each relay is equipped with multiple antennas. We jointly design the beamforming matrices of the cooperating relays by minimizing both the noise received at each destination node and the interference caused by the sources not targeting this node. We impose additional constraints that preserve the received signal from each source at its targeted destination node. The relay beamforming problem is shown to be a convex optimization problem and is formulated as a second-order cone program that can be efficiently solved using interior point methods. Numerical simulations are presented showing the superior performance of our beamforming technique compared to previously proposed zero forcing relay beamforming.

In this paper, we develop a state-space approach to the blind multiuser detection problem with robustness against mismatches in the desired user signature and the time-varying number of users in the channel. The solution is obtained adaptively using a second-order extended Kalman filter (EKF) and requires only O(L2) operations per iteration, where L is the dimension of the subspace containing the signatures of all the users. We also present a state-space approach to the decision directed multiuser detection problem and an algorithm for switching between robust blind and decision directed detection. The proposed switching algorithm is based on using the normalized innovation square (NIS) of the blind detector to test for its convergence and the NIS of the decision directed detector to detect nonstationarities. Thus, it combines the advantages of both these detection schemes and can achieve an output signal- to-interference-plus-noise ratio (SINR) comparable to that of the minimum mean square error (MMSE) detector without any training, even in the presence of mismatches in the desired user signature. Therefore, it is well suited to practical nonstationary environments where users repeatedly enter and leave the system making the cost of retraining un affordable.