This paper studies the Multi-Input-Multi-Output (MIMO) interference networks with arbitrary number of transmitters and receivers, where both the transmitters and receivers are equipped with caches. The main goal is to design content placement and delivery schemes that minimize the worst case normalized delivery time (NDT). First, we propose a delivery scheme for the cache-aided Single-Input-Multiple-Output (SIMO) interference networks. Then, we obtain the achievable NDT of the cache-aided MIMO interference networks using the decomposition property of splitting each multi-antenna transmitter into multiple single antenna transmitters. Furthermore, we derive an information-theoretic bound on the optimal NDT of the cache-aided MIMO interference network. Analytical results show that the proposed scheme is within a multiplicative gap of 2 from the derived lower bound independent of all system parameters for any uncoded cache placement scheme. We also derive a novel delivery scheme for the cache-aided Multi-Input-Single-Output (MISO) interference network outperforming our proposed scheme for the cache-aided MIMO interference network. The numerical results show the superiority of our proposed scheme over the state-of-the-art schemes in the literature. Our results show that the coded caching gain has a more significant contribution in reducing the transmission latency than the spatial multiplexing gain. Our results indicate that the receive-antennas become more effective in reducing the NDT than the transmit-antennas in the presence of caches at the receiver-side. In addition, we show that increasing the number of transmit-antennas has a higher gain in reducing the NDT than adding more transmitters in the cache-aided MISO interference network.

Due to the advances in machine learning techniques, recommender systems nowadays are capable of learning and influencing the users’ decisions. Hence, recommendations became an important facility to reduce the cost (or increase the profit) of the operators of the demand networks. In this paper we formulate and study the problem of dynamically optimizing the demand shaping, through content recommendation, and proactive caching. The formulated problem suffers from the curse of dimensionality, so we devise an approximate algorithm optimizing only over a short look-ahead window. The approximate problem is not convex, as such we utilize non-convex optimization techniques to tackle the problem. To verify the efficiency of our proposed solution, we establish a lower bound on the minimum achievable cost and contrast it with our solution.

Centralized coded caching and delivery is studied for a radio access combination network (RACN), whereby a set of H edge nodes (ENs), connected to a cloud server via orthogonal fronthaul links with limited capacity, serve a total of K user equipments (TIEs) over wireless links. The cloud server is assumed to hold a library of N files, each of size F bits; and each user, equipped with a cache of size μRN F bits, is connected to a distinct set of r ENs each of which equipped with a cache of size μTN F bits, where μT, μR∈ [0, 1] are the fractional cache capacities of the TIEs and the ENs, respectively. The objective is to minimize the normalized delivery time (NDT), which refers to the worst case delivery latency when each user requests a single distinct file from the library. Three coded caching and transmission schemes are considered, namely the MDSIA, soft-transfer and zero-forcing (ZF) schemes. MDS-IA utilizes maximum distance separable (MDS) codes in the placement phase and real interference alignment (IA) in the delivery phase. The achievable NDT for this scheme is presented for r = 2 and arbitrary fractional cache sizes μTand μR, and also for arbitrary value of r and fractional cache size μTwhen the cache capacity of the TIE is above a certain threshold. The soft-transfer scheme utilizes soft-transfer of coded symbols to ENs that implement ZF over the edge links. The achievable NDT for this scheme is presented for arbitrary r and arbitrary fractional cache sizes μTand μR. The last scheme utilizes ZF between the ENs and the TIEs without the participation of the cloud server in the delivery phase. The achievable NDT for this scheme is presented for an arbitrary value of r when the total cache size at a pair of TIE and EN is sufficient to store the whole library, i.e., μT+μR≥ 1. The results indicate that the fronthaul capacity determines which scheme achieves a better performance in terms of the NDT, and the soft-transfer scheme becomes favorable as the fronthaul capacity increases.

This paper studies the Multi-Input-Multi-Output (MIMO) interference networks with arbitrary number of transmitters and receivers, where both the transmitters and receivers are equipped with caches. Our objective is to propose content placement and delivery schemes that minimize the worst case normalized delivery time (NDT). First, we design a delivery scheme for the cache-aided Single-Input-Multiple-Output (SIMO) interference networks. Then, we obtain the achievable NDT of the cache-aided MIMO interference networks by using the decomposition property. The numerical results show the superiority of our proposed scheme over the state-of-the-art schemes in the literature. Furthermore, we show that increasing the receiver-cache sizes achieves a higher gain than increasing the number of receive-antennas. In other words, the coded caching gain has a more significant contribution in reducing the transmission latency than the spatial multiplexing gain.

We consider a fog radio access network (F-RAN) with multiple transmitters and receivers, where each transmitter is connected to the cloud via a fronthaul link. Each network node has a finite cache, where it fills its cache with portions of the library files in the off-peak hours. In the delivery phase, receivers request each library files according to an arbitrary popularity distribution. The cloud and the transmitters are responsible for satisfying the requests. This paper aims to design content placement and coded delivery schemes for minimizing both the expected normalized delivery time (NDT) and the peak NDT which measures the transmission latency. We propose achievable transmission policies, and derive an information-theoretic bound on the expected NDT under uniform popularity distribution. The analytical results show that the proposed scheme is within a gap of 2.58 from the derived bound for both the expected NDT under uniform popularity distribution and the peak NDT. Next, we investigate the expected NDT under an arbitrary popularity distribution for an F-RAN with transmitter-side caches only. The achievable and information-theoretic bounds on the expected NDT are derived, where we analytically prove that our proposed scheme is optimal within a gap of two independent of the popularity distribution.

We investigate dynamic content caching in relay networks where an intermediate relay station (RS) can adaptively cache data content based on their varying popularity. With the objective of minimizing the time average cost of content delivery, we formulate and study the problem of optimal RS cache allocation when the popularities of data content are unknown apriori to the network. While optimal dynamic cache control suffers the curse of dimensionality, we develop a fundamental lower bound on the achievable cost by any caching policy. Inspired by the structure of such lower bound, we develop a reduced-complexity policy that is shown numerically to perform close to the lower bound.

In this paper, we consider a class of wireless powered communication devices using hybrid automatic repeat request (HARQ) protocol to ensure reliable communications. In particular, we analyze the trade-off between accumulating mutual information and harvesting RF energy at the receiver of a point-to-point link over a time-varying independent and identically distributed (i.i.d.) channel. The transmitter is assumed to have a constant energy source while the receiver relies, solely, on the RF energy harvested from the received signal. At each time slot, the incoming RF signal is split between information accumulation and energy accumulation with the objective of minimizing the expected number of re-transmissions. A major finding of this work is that the optimal policy minimizing the expected number of re-transmissions utilizes the incoming RF signal to either exclusively harvest energy or to accumulate mutual information. This finding enables achieving an optimal solution in feasible time by converting a two dimensional uncountable state Markov decision process (MDP) with continuous action space into a countable state MDP with binary decision space.

We investigate the performance of caching in relay networks where an intermediate relay station (RS) caches content for future demand by end users. With uncertain user demand over multiple data items and dynamically changing wireless links, we characterize the optimal transmission time for serving data items, cached data portion allocation of relay station and optimal service portion, which represents a part from the cached portion, to minimize the total average transmission energy. We argue that under several settings fully caching the higher popular items is the optimal caching policy which minimizes the total expected transmission energy.

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.

Centralized coded caching and delivery is studied for a partially-connected fog radio access network (F-RAN), whereby a set of H edge nodes (ENs) (without caches), connected to a cloud server via orthogonal fronthaul links, serve K users over the wireless edge. The cloud server is assumed to hold a library of N files, each of size F bits; and each user, equipped with a cache of size MF bits, is connected to a distinct set of r ENs; or equivalently, the wireless edge from the ENs to the users is modeled as a partial interference channel. The objective is to minimize the normalized delivery time (NDT), which refers to the worst case delivery latency, when each user requests a single file from the library. An achievable coded caching and transmission scheme is proposed, which utilizes maximum distance separable (MDS) codes in the placement phase, and real interference alignment (IA) in the delivery phase, and its achievable NDT is presented for r = 2 and arbitrary cache size M, and also for arbitrary values of r when the cache capacity is sufficiently large.

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.

This paper studies the decentralized coded caching for a Fog Radio Access Network (F-RAN), whereby two edge-nodes (ENs) connected to a cloud server via fronthaul links with limited capacity are serving the requests of K r users. We consider all ENs and users are equipped with caches. A decentralized content placement is proposed to independently store contents at each network node during the off-peak hours. After that, we design a coded delivery scheme in order to deliver the user demands during the peak-hours under the objective of minimizing the normalized delivery time (NDT), which refers to the worst case delivery latency. An information-theoretic lower bound on the minimum NDT is derived for arbitrary number of ENs and users. We evaluate numerically the performance of the decentralized scheme. Additionally, we prove the approximate optimality of the decentralized scheme for a special case when the caches are only available at the ENs.

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.

We investigate the performance of dynamic proactive caching in relay networks where an intermediate relay station caches content for potential future use by end users. A central base station proactively controls the cache allocation such that cached content remains fresh for consumption for a limited number of time slots called proactive service window. With uncertain user demand over multiple data items and dynamically changing wireless links, we consider the optimal allocation of relay stations cache to minimize the time average expected service cost. We characterize a fundamental lower bound on the cost achieved by any proactive caching policy. Then we develop an asymptotically optimal caching policy that attains the lower bound as the proactive caching window size grows. Our analytical findings are supported with numerical simulations to demonstrate the efficiency of the proposed relay-caching.

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 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.

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, 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 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.

Abstract In this paper, we derive the capacity of the deterministic relay networks with relay messages. We consider a network that consists of five nodes, four of which can only communicate via the fifth one. However, the fifth node is not merely a relay as it may exchange private messages with the other network nodes. First, we develop an upper bound on the capacity region based on the notion of a single‐sided genie. In the course of the achievability proof, we also derive the deterministic capacity of a four‐user relay network (without private messages at the relay). The capacity achieving schemes use a combination of two network coding techniques: the simple ordering scheme and detour scheme. In the simple ordering scheme, we order the transmitted bits at each user such that the bi‐directional messages will be received at the same channel level at the relay, while the basic idea behind the detour scheme is that some parts of the message follow an indirect paths to their respective destinations. This paper, therefore, serves to show that user cooperation and network coding can enhance throughput, even when the users are not directly connected to each other. Finally, we make a conjecture about the capacity region of the generalK‐node relay network with relay messages. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, we introduce a new metric, namely: effective area spectral efficiency (EASE), to quantify the spectral efficiency as well as the spatial properties of decoding and forward (DF) relaying wireless communications networks with interference management. The EASE metric is based on the average affected area, the average ergodic capacity, and a new introduced index, namely: source relay communication index (SRCndx). We derive a closed-form expression for the maximum transmission range under Rayleigh fading environment. Based on the maximum transmission range, we define and derive the average affected area and the average ergodic capacity for DF relaying communications system. The SRCndx is used to validate the communication possibility between a source and a relay for given transmission parameters in a given environment, and provides information about the necessity of using relaying communications. We then introduce the EASE expression to quantify the spatial spectral utilization efficiency. Through mathematical analysis and numerical examples, we show that the EASE metric provides a new perspective on the design and optimization of wireless transmissions, especially the transmission power selection process.

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, we study the degrees of freedom (DoF) of the MIMO relay networks. We start with a general Y channel, where each user has Miantennas and aims to exchange messages with the other two users via a relay equipped with N antennas. Then, we extend our work to a general 4-user MIMO relay network. Unlike most previous work which focused on the total DoF of the network, our aim here is to characterize the achievable DoF region as well. We develop an outer bound on the DoF region based on the notion of one sided genie. Then, we define a new achievable region using the Signal Space Alignment (SSA) and the Detour Schemes. Our achievable scheme achieves the upper bound for certain conditions relating Mi's and N.

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.

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, we study the problem of cooperative spectrum sharing among a primary user (PU) and multiple secondary users (SUs) under quality of service (QoS) constraints. The SUs network is controlled by the PU through a relay which gets a revenue for amplifying and forwarding the SUs' signals to their respective destinations. The relay charges each SU a different price depending on its received signal-to-interference-and-noise ratio (SINR). The primary relay controls the SUs network and maximize any desired PU utility function. The PU utility function represents its QoS, which is affected by the SUs access, and its gained revenue to allow the access of the SUs. The problem of maximizing the primary utility is formulated as a Stackelberg game and solved through three different approaches, namely, the optimal, the heuristic and the suboptimal algorithms.

In this paper, we completely characterize the deterministic capacity region of a four-node relay network with no direct links between the nodes, where each node communicates with the three other nodes via a relay. Towards this end, we develop an upper bound on the deterministic capacity region, based on the notion of a one-sided genie. To establish achievability, we use the detour schemes that achieve the upper bound by routing specific bits via indirect paths instead of sending them directly.

We study the capacity region of a deterministic 4-node network, where 3 nodes can only communicate via the fourth one. However, the fourth node is not merely a relay since it can exchange private messages with all other nodes. This situation resembles the case where a base station relays messages between users and delivers messages between the backbone system and the users. We assume an asymmetric scenario where the channel between any two nodes is not reciprocal. First, an upper bound on the capacity region is obtained based on the notion of single sided genie. Subsequently, we construct an achievable scheme that achieves this upper bound using a superposition of broadcasting node 4 messages and an achievable “detour” scheme for a reduced 3-user relay network.

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.

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.

In this work, we analyze the diversity gain region (DGR) of the single-antenna Rayleigh fading Z-Interference channel (ZIC). More specifically, we characterize the achievable DGR of the fixed-power split Han-Kobayashi (HK) approach under these assumptions. Our characterization comes in a closed form and demonstrates that the HK scheme with only a common message is a singular case, which achieves the best DGR among all HK schemes for certain multiplexing gains. Finally, we show that generalized time sharing, with variable rate and power assignments for the common and private messages, does not improve the achievable DGR.

We characterize the achievable three-dimensional tradeoff between diversity, multiplexing, and delay of the single antenna Automatic Retransmission reQuest (ARQ) Z-interference channel. Non-cooperative and cooperative ARQ protocols are adopted under these assumptions. Considering no cooperation exists, we study the achievable tradeoff of the fixed-power split Han-Kobayashi (HK) approach. Interestingly, we demonstrate that if the second user transmits the common part only of its message in the event of its successful decoding and a decoding failure at the first user, communication is improved over that achieved by keeping or stopping the transmission of both the common and private messages. Under cooperation, two special cases of the HK are considered for static and dynamic decoders. The difference between the two decoders lies in the ability of the latter to dynamically choose which HK special-case decoding to apply. Cooperation is shown to dramatically increase the achievable first user diversity.

Successful spectrum sharing in a cognitive radio network depends on the correct and quick detection of primary activity. Cooperative spectrum sensing is therefore suggested to enhance the reliability of such detection. However, it renders another significant problem of increased detection delay and traffic burden. Moreover, efficient schemes for multi-sensor data fusion should be designed. In this paper, we employ sequential detection scheme together with ordered transmissions from cognitive detectors. We derive two sequential schemes, one that is capable of achieving the minimum probability of error, and another that trades-off performance with delay. For the latter we derive expressions for the likelihood functions of ordered observations and compute the thresholds via backward induction. Simulation results demonstrate the relative performance of the approaches proposed in the paper.

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.

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 the problem of admission and power control considering a scenario where licensed, or primary, users and cognitive radios, or secondary users, are transmitting concurrently over the same band. The primary users share a common receiver and the interference on this receiver from secondary users should be strictly limited to a certain level. Each secondary link is assumed to have a minimum quality of service (QoS) requirement that should be satisfied together with the interference limit constraint, otherwise the secondary link is not admitted. Under those constraints, admission and power control for secondary users are investigated for two main optimization objectives. First, we maximize the number of admitted secondary links. Second, we maximize the sum throughput of the admitted secondary links. The first problem is NP-hard, hence we provide a distributed close-to-optimal solution based on local measurements at each user and a limited amount of signaling. For the second problem, which is non-convex, we propose a suboptimal algorithm based on sequential geometric programming. The proposed algorithms are compared with previously related work to demonstrate their relative efficiency in terms of outage probability, complexity and achievable throughput.

In this paper we study the use of a high rate Low Density Parity Check (LDPC) codes in concatenated coding structures. Specifically, we use the LDPC code as an outer code, with a convolutional code as an inner code. We decode the convolutional code using a symbol based Log-MAP (Maximum a posteriori probability) decoder, and feed the soft outputs of this decoder into a non-binary Galois Field LDPC decoder. We compare this concatenation scheme using 16 QAM modulation with one using a bit based Log-MAP decoder over Additive White Gaussian Noise (AWGN) and Stanford University Interim (SUI-3) channel model. The new proposed decoding technique has shown improvements for both channel models.

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.

Efficient resource allocation is a critical component in multi-user QoS communications and high speed networks. In this paper, we devise a new mathematical model for the resource allocation problem that takes into account the users' demands in a PHY-MAC cross-layer approach. Incorporating the time axis in our model, the target is to maximize the number of bits transmitted in a given frame rather than maximizing the channel capacity or the average throughput. Our design is governed by constraints on users' demands (expressed in bits), energy expenditure, and frame duration. We model the allocation problem as an optimization problem whose solution allocates channels, time span, and power levels to each user. We also derive an upper bound on the performance of any resource allocation algorithm and use this bound to assess the performance of the solution obtained using our proposed model.

In this paper, we completely characterize the deterministic multicast capacity region of the symmetric two-pair bidirectional half duplex relay network with private messages. Towards this end, we first develop a new upper bound on the deterministic capacity region, based on the notion of a one-sided genie. We then proceed to construct novel detour schemes that achieve the upper bound by routing the bits intended for a certain receiver through the network rather than sending it directly. To the best of the authors' knowledge, this scenario corresponds to one of the rare cases where coding, across levels and time, is needed to achieve the deterministic capacity of the network.

In this paper we investigate admission control and power allocation for cognitive radios in an underlay network. We consider the problem of maximizing the number of supported secondary links under their minimum QoS requirements without violating the maximum tolerable interference on primary receivers in a cellular network. An optimal solution to our problem is shown in previous works to be NP-hard. We propose an efficient distributed algorithm with reasonable complexity that provides results close to the optimum solution without requiring neither a large amount of signaling nor a wide range of information about the system parameters. Our algorithm is compared with previously proposed algorithms to demonstrate its relative efficiency.

In this paper we propose a novel technique for hybrid automatic repeat request (HARQ) systems where turbo codes are used as the forward error correction (FEC) techniques. This technique uses the histogram of the soft values generated by the turbo decoder to control the size and the contents of the retransmissions needed when the packet can not be decoded correctly. These soft values represent the reliabilities of the information bits; hence the proposed technique is a reliability-based (RB) HARQ technique. The proposed technique is compared to the conventional RBHARQ and the conventional rate compatible punctured turbo (RCPT) codes, and is shown to achieve higher throughput and/or less number of transmissions.

A scheme is proposed for adaptively changing the code rate of coded OFDMA systems via changing the puncturing rate within a single codeword (SCW). In the proposed structure, the data is encoded with the lowest available code rate then it is divided among different resource blocks (tiles) where it is punctured adaptively based on some measure of the channel quality for each tile. The proposed scheme is compared against using multiple codewords (MCWs) where the transmitter divides the data over tiles and encodes them separately. We investigate two different adaptive modulation and coding (AMC) selection methods. The first is a recursive scheme that operates directly on the SNR whereas the second operates on the effective SNR value that is obtained using Mutual Information Effective SNR Mapping (MIESM). We then compare our scheme to Per-Frame Adaptation (PFA) where we fix the modulation and coding scheme (MCS) over a given frame. We show via simulations that when using the recursive rate selection method the SCW scheme significantly outperforms the MCWs and the PFA. It is also shown that applying the MIESM rate selection method, the PFA improves significantly, yet the SCW scheme is the best performer. We also introduce a novel interleaving method prior to puncturing that improves the performance for certain restricted adaptation mechanisms.

In this paper, a cross-layer adaptive resource allocation (XARA) algorithm for channel division based systems, such as OFDMA, is proposed. XARA design is based on a PHY-MAC cross-layer approach which yields better channel utilization compared to separate PHY or MAC designs. XARA uses a joint power and channel allocation algorithm to determine both the channel assignment and the transmission power for each user in order to maximize the overall system capacity. Through an iterative algorithm, XARA enhances the channel utilization by taking into account the demands of the users so as to assign the minimum number of time slots needed to fulfill the requirements of each user. The saved time slots are reported to the scheduling and admission control functions of the MAC layer in order to either allow more users to enter the network or to allow the current users to request more quality of service "QoS" sessions. The proposed algorithm can fit in different wireless systems such as WIMAX and LTE. The algorithm is also flexible enough to accommodate the dynamic nature of the spectrum in the case of cognitive radio networks and considers the power constraints associated with such networks.

In this paper we study low density party check (LDPC) codes used in the IEEE 802.16 physical layer standard. We introduce two novel techniques to enhance the performance of such codes. In the first technique, we use the binary parity check matrix proposed in the IEEE 802.16 standard, and propose a novel parity check matrix for LDPC codes over GF(4) with the non-zero entries chosen to maximize the entropy. We show that our proposed code outperforms the binary code proposed in the IEEE 802.16 standard over both AWGN and SUI-3 channel model. In our second technique, we use a high rate LDPC code, in a concatenated coding structure, as an outer code, with a convolutional code as an inner code. We compare the performance of such a concatenated code with the commonly used one utilizing Reed-Solomon codes over the standard SUI-3 channel model, and show better performance.

There is an ever growing need for higher speed communications over existing wireline plant. To achieve even higher throughput, bonding and joint optimization of multiple-input-multiple-output cable bundles attracted attention recently. In this paper we first explain a technique which allows several users to use the same communication medium while at the same time allowing their transmission to be separated at the receiver. This technique would handle single-channel-multiple-users case. The technique is then extended to handle multiple input multiple output (MIMO) channel by jointly optimizing the transmit filters to maximize the throughput over the MIMO channel. This optimization is suitable for multiple-channels-single-user and multiple-channels-multiple-users cases. A 2-D MIMO channel example is given and simulation results show that the joint optimization achieves higher throughput than independent optimization for each channel.

Gaussian frequency shift keying modulation has been chosen as the modulation technique for the physical layer of Bluetooth. Bluetooth is a standard for low cost and low power wireless communications between various mobile devices. The optimal demodulation of a GFSK signal involves an extremely complex Viterbi decoder. Therefore designers have opted for the noncoherent detection of GFSK which uses a frequency discriminator, followed by symbol by symbol detection. We describe a decision feedback equalizer to be added after the discriminator. The DFE receiver gives gains in excess of 2 dB. We also describe how to increase the current data rate of a Bluetooth system by increasing the symbol rate and not the alphabet size.

In this paper, we describe a new tree-based CDMA receiver that can optimally trade complexity for detection performance. It yields the detector with the best detection performance for a given desired complexity level. Alternatively, it yields the lowest complexity receiver for any given desired detection performance. We describe a technique for designing receivers with linear complexity (including the optimal linear detector and decorrelator). We then explain how we can increase performance at the expense of a minimal increase in complexity. We show that as complexity increases to the level of that of the optimal receiver, our design approach automatically produces the optimal receiver. We also explain how our approach can be used with a minimum-mean-square-error design criterion and coded CDMA transmission. Finally, we illustrate with several examples the superiority of the receivers designed with our approach and discuss their advantages.

We present a progressive refinement approach to M-ary detection problems. The approach leads on average to a logarithmic reduction in the complexity of the detector. It relies on designing binary decision trees that trade complexity with probability of error. We also discuss simplified solutions that can be used in several cases of interest in wireless communications such as CDMA multiuser detection and blind equalization.

In discrete multitone (DMT) a time domain equalizer is used to shorten the length of the channel to less than the length of the cyclic prefix. The weights of this equalizer are set during initialization using a training sequence. Current techniques that rely on a version of on-line frequency domain LMS show low and uncertain convergence. Here, we show that off-line techniques that estimate the channel first, have much lower complexity, while providing much better performance. We describe a solution that requires a minimum eigenvalue to be found and show that this can be done with relatively low complexity. We also describe an off-line technique based on time domain LMS.

A number of over-complete dictionaries such as wavelets, wave packets, cosine packets etc. have been proposed. Signal decomposition on such over-complete dictionaries is not unique. This non-uniqueness provides us with the opportunity to adapt the signal representation to the signal. The adaptation is based on sparsity, resolution and stability of the signal representation. The computational complexity of the adaptation algorithm is of primary concern. We propose a new approach for identifying the sparsest representation of a given signal in terms of a given over-complete dictionary. We assume that the data vector can be exactly represented in terms of a known number of vectors.