We consider a status update system consisting of one source, one server, and one sink. The source generates packets according to a Poisson process and the packets are served according to a generally distributed service time. We consider a system with a capacity of one packet, i.e., there is no waiting buffer in the system, and model it as an M/G/1/1 queueing system. We introduce a probabilistically preemptive packet management policy and calculate the moment generating functions (MGFs) of the age of information (AoI) and peak AoI (PAoI) under the policy. According to the probabilistically preemptive policy, when a packet arrives, the possible packet in the system is replaced by the arriving packet with a fixed probability. Numerical results show the effectiveness of the packet management policy.

In this paper, we propose a deep learning method for channel estimation in OFDM systems over WINNER II channel. The approach is based on a Long Short-Term Memory (LSTM) network that takes advantage of the temporal and frequency correlation across OFDM blocks. The model is trained to predict the full channel frequency response at each block using only pilot observations from current and previous blocks. We evaluate the performance of the proposed estimator under various signal-to-noise ratio (SNR), numbers of pilot subcarriers, and temporal window sizes. Simulation results demonstrate that the LSTM-based approach consistently outperforms both LS and recent deep learning models based on super-resolution. The results show that the LSTM model achieves lower estimation error across different SNR values, making it a strong candidate for reliable channel estimation in dynamic wireless environments.

We consider an Internet of Battlefield Things (IoBT) system consisting of multiple devices that want to securely communicate with each other during a mission in the presence of an adversary with unbounded computational power. The adversary has complete access to listen/read the ciphertext without tampering with the communication line. We provide an unconditionally secure encryption scheme to exchange messages among devices in the system. The main idea behind the scheme is to provide secret keys to exchange messages using a random binary matrix that is securely shared among all the devices, and pair-wise random secret keys established between each pair of devices attempting to communicate before the mission. The scheme is implemented by using finite group modular addition. We show that the scheme is absolutely semantically secure, i.e., the scheme guarantees that an adversary with unbounded computational power cannot get even one bit of information about a message, except for an exponentially small probability in a security parameter. Besides that, we show that even if the random binary matrix is revealed to the adversary, the provided scheme is computationally secure against the key recovery attack.

The unbreakable security and higher data rates offered by quantum communication networks have made quantum communication an inevitable necessity of the future. Many quantum communication frameworks, such as quantum key distribution and super dense coding, require entangled pairs to be shared between the source and destination nodes. Communication nodes in quantum networks have a minimum fidelity requirement for the entangled pairs. If the fidelity requirement is not satisfied, the entangled pairs may not be used for the desired operations. Successful sharing of the entangled pairs between the nodes is a crucial step in making quantum communication practical. In this work, we propose a framework to maximize entanglement sharing between a source and multiple destination nodes in a fair manner. We consider a system that takes advantage of the purification process to improve the fidelity of the entangled pairs when necessary. The proposed solution framework provides the optimal number of entangled pairs required for the purification process and the optimal transmission rate at the source node to achieve the desired system objective. The non-convex problem is first transformed into a convex form, and then a Lagrangian dual-based framework is proposed to find the optimal solution values. Moreover, to optimize the number of entangled pairs for purification at each link, we derive a closed-form expression that provides the optimal value in a single step. Selected simulation results demonstrate that the proposed framework exhibits excellent performance.

We provide an encryption protocol for storing highly confidential data of a user on a public cloud storage. We show that the protocol provides unconditional security. More specifically, we prove that the protocol is semantically secure against an all-powerful adversary with unbounded computational power and storage capacity who has complete access to the communication line. The provided protocol is very simple, it is implemented by exploiting finite group modular addition and XOR operations. The protocol provides a high security gain defined as the ratio of the amount of data (in bits) that can be securely stored on the public cloud and the number of secret bits required to be stored at the user end. As an illustrative example, according to the protocol, by using 40.2 Terabytes (TBs) of secret bits, a user is able to store 5.9 ×108TBs of data on a public storage with guaranteed everlasting security.

Deep neural networks (DNNs) have been widely used in recent years for wireless communication applications, including channel estimation. However, DNN performs well for environments (data) that it has been trained for. However, it is still challenging to work in a non-stationary system where the statistical characteristics of the environment change with time. This paper introduces an online adaptation approach that allows the neural network to dynamically change to cope with the non-stationary channel estimation. The idea is to use the existing detected packets to continuously update the weights of the DNN. Simulation results show that our approach can significantly improve the performance of the DNN in non-stationary environments whereas concurrent state-of-the-art algorithms fail.

In the bounded storage model introduced by Maurer, the adversary is computationally unbounded and has a bounded storage capacity. In this model, perfect secrecy is guaranteed by using a publicly available random string whose length is larger than the adversary storage capacity. The protocol proposed by Maurer is simple, from the perspective of implementation, and efficient, from the perspective of the initial secret key size and random string length. However, he provided the proof of the security for the case where the adversary can access a constant fraction of the random string and store onlyoriginal bitsof the random string. In this paper, we provide a new proof of the security of the protocol proposed by Maurer for the general bounded storage model, i.e., the adversary can access all bits of the random string, and store the output of any Boolean function on the string. We reaffirm that the protocol isabsolutely semantically securein the general bounded storage model.

This work presents a deep-Q reinforcement learning (DQ-RL) framework to achieve fairness in multi-access cognitive radio (CR) systems. The proposed framework provides fast solution and is robust to channel dynamics. Further, to remove the computational overhead and the burden to feedback thousands of weights from the secondary receiver (SR), we propose a solution where the process of learning is carried out at the secondary transmitters (STs). The simulations show that by using the proposed technique, a good level of fairness is achievable with an outage probability of the primary system less than 0.04. We also provide the comparison of the proposed technique with a brute-forcing optimization method, and show the fairness gain of the proposed framework compared to the rate maximization model.

Recently, different architectures based on coding theory have been proposed to reduce the storage and communication costs associated with a blockchain system. However, many of these methods have high bandwidth requirements for repairing the share of a failed node or decoding a particular requested block. The bandwidth required for decoding a requested block becomes an important factor in some blockchain applications like healthcare, where historical data needs to be frequently accessed. In this work, we introduce two new architectures for blockchain-based systems, which reduce the storage and communication costs associated with blockchain’s historical data and simultaneously provides confidentiality of the stored data. The two protocols are designed using a combination of fountain codes and a proposed communication and repair efficient secret sharing scheme. We also present a construction of the secret sharing scheme which meets our requirements.

In this paper, we propose a new provably secure cryptosystem for two party communication that provides security in the face of new technological breakthroughs. Most of the practical cryptosystems in use today can be breached in the future with new sophisticated methods. This jeopardizes the security of older but highly confidential messages. Our protocol is based on the bounded storage model first introduced in [1]. The protocol is secure as long as there is bound on the storage, however large it may be. We also suggest methods to extend the protocol to unbounded storage models where access to adversary is limited. Our protocol is a substantial improvement over previously known protocols and uses short key and optimal number of public random bits size of which is independent of message length. The smaller and constant length of key and public random string makes the scheme more practical. The protocol generates key using elements of the additive group$\mathbb{Z}_{\mathrm{n}}$. Our protocol is very generalized and the protocol in [1] is a special case of our protocol. Our protocol is a step forward in making provably secure cryptosystems practical. An important open problem raised in [2] was designing an algorithm with short key and size of public random string$O(\mathcal{B})$where$\mathcal{B}$bounds the storage of adversary. Our protocol satisfies the conditions and is easy to implement.

For downlink multi-user non-orthogonal multiple access (NOMA) systems with successive interference cancellation (SIC) receivers, and a base-station not possessing the instantaneous channel gains, the fundamental relationship between the target rates and power allocation is investigated. It is proven that the total interference from signals not removed by SIC has a fundamental upper limit which is a function of the target rates, and the outage probability equals one when exceeding this limit. The concept of well-behaved power allocation strategies is defined, and its properties are proven to be derived solely based on the target rates. The existence of power allocation strategies that enable NOMA to outperform OMA in per-user outage probability is proven, and are always well-behaved for the case when the outage probability performance of NOMA and OMA are equal for all users. The proposed SIC decoding order is then shown to be the most energy efficient. The derivation of well-behaved power allocation strategies that have improved outage probability performance over OMA for each user is outlined. Simulations validate the theoretical results, demonstrating that NOMA systems can always outperform OMA systems in outage probability performance, without relying on the exact channel gains.

Non-Orthogonal Multiple Access (NOMA) and caching are two proposed approaches to increase the capacity of future 5G wireless systems. Typically in NOMA systems, signals at the receiver are decoded using successive interference cancellation in order to achieve capacity in multi-user systems. The leveraging of caching in the physical layer to further improve on the benefits of NOMA is investigated, which is termed cache-aided NOMA. Specific attention is given to the caching cases where the users with weaker channel conditions possess a cache of the information requested by a user with a stronger channel condition. The probability that any of the users is in outage for any of the rates required for this NOMA system, defined as the “union-outage,” is derived for the case of fixed-power allocation, and the power allocation strategy that minimizes the union-outage probability is derived. Simulation results confirm the analytical results, which demonstrate the benefits of cache-aided NOMA on reducing the union-outages probability.

In the era of big data, reducing the computational complexity of servers in data centers will be an important goal. We propose Low Complexity Secure Codes (LCSCs) that are specifically designed to provide information theoretic security in cloud distributed storage systems. Unlike traditional coding schemes that are designed for error correction capabilities, these codes are only designed to provide security with low decoding complexity. These sparse codes are able to provide (asymptotic) perfect secrecy similar to Shannon cipher. The simultaneous promise of low decoding complexity and perfect secrecy make these codes very desirable for cloud storage systems with large amount of data. The design is particularly suitable for large size archival data such as movies and pictures. The complexity of these codes are compared with traditional encryption techniques.

The fundamental power allocation requirements for NOMA systems with minimum quality of service (QoS) requirements are investigated. For any minimum QoS rate R0, the limits on the power allocation coefficients for each user are derived, such that any power allocation coefficient outside of these limits creates an outage with probability equal to 1. The power allocation coefficients that facilitate each user's success of performing successive interference cancellation (SIC) and decoding its own signal are derived, and are found to depend only on the target rate R0and the number of total users K. It is then proven that using these power allocation coefficients create the same outage event as if using orthogonal multiple access (OMA), which proves that the outage performance of NOMA with a fixed-power scheme can matched that of OMA for all users simultaneously. Simulations confirm the theoretical results, and also demonstrate that a power allocation strategy exists that can improve the outage performance of NOMA over OMA, even with a fixed-power strategy.

The de facto approach to Web security today is HTTPS. While HTTPS ensures complete security for clients and servers, it also interferes with transparent content-caching at middleboxes. To address this problem and support both security and caching, we propose a new approach to Web security and privacy called GroupSec. The key innovation of GroupSec is that it replaces the traditional session-based security model with a new model based on content group membership. We introduce the GroupSec security model and show how HTTP can be easily adapted to support GroupSec without requiring changes to browsers, servers, or middleboxes. Finally, we present results of a threat analysis and performance experiments which show that GroupSec achieves notable performance benefits at the client and server while remaining as secure as HTTPS.

As networking attempts to cleanly separate the control plane and forwarding plane abstractions, it also defines a clear interface between these two layers. An underlying network state is represented as a view to act upon in the control plane. We are interested in studying some fundamental properties of this interface, both in a general framework, and in the specific case of content routing. We try to evaluate the traffic between the two planes based on allowing a minimum level of acceptable distortion in the network state representation in the control plane. We apply our framework to content distribution, and see how we can compute the overhead of maintaining the location of content in the control plane. This is of importance to evaluate resolution-based content discovery in content-oriented network architectures: we identify scenarios where the cost of updating the control plane for content routing overwhelms the benefit of fetching the nearest copy. We also show how to minimize the cost of this overhead when associating costs to peering traffic and to internal traffic for network of caches.

Decentralized coded content caching for next generation cellular networks is studied. The contents are linearly combined and cached in under-utilized caches of user terminals and its throughput capacity is compared with decentralized uncoded content caching. In both scenarios, we consider multihop device-to-device communications and the use of femtocaches in the network. It is shown that decentralized coded content caching can increase the network throughput capacity compared to decentralized uncoded caching by reducing the number of hops needed to deliver the desired content. Furthermore, the throughput capacity for Zipfian content request distribution is computed and it is shown that the decentralized coded content cache placement can increase the throughput capacity of cellular networks by a factor of (log (n))2where n is the number of nodes served by a femtocache.

Wireless information-centric networks consider storage as one of the network primitives, and propose to cache data within the network in order to improve latency and reduce bandwidth consumption. We study the throughput capacity and latency in an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the order of the data access time does not change with network growth, and the maximum throughput order is not changing with the network growth in grid networks and is inversely proportional to the number of nodes in one cell in random networks. Comparing these values with the corresponding throughput and latency with no cache capability (throughput inversely proportional to the network size, and latency of order √n and the inverse of the transmission range in grid and random networks, respectively), we can actually quantify the asymptotic advantage of caching. Moreover, we compare these scaling laws for different content discovery mechanisms and illustrate that not much gain is lost when a simple path search is used.

In this paper, we study the effects of social interactions among nodes on the capacity of wireless networks. We consider three scenarios. In the first scenario, the size of the social group for all nodes is fixed while the frequency of communication within members of a social group follows power law distribution. In the second scenario, scale-free networks are studied where the size of the social group differs from node to node, and the destination in each group is selected uniformly among the members of that group. Further investigation in the second scenario reveals that traditional transport capacity definition provides misleading conclusions for such network models. We show that nodes with different social status impact the capacity differently. By separating nodes with different social status and allocating separate bandwidth to them, it is shown that majority of nodes scale in this network. In the third scenario, both the size of the social groups and the destination in each group are selected according to power law distributions. Our simulation results corroborate the analytical results. Further, we observe consistently that social interaction improves the capacity of wireless networks, which implies that the Gupta-Kumar results were pessimistic for practical networks.

Abstract A new approach for multiantenna broadcast channels in cellular networks based on multiuser diversity concept is introduced. The technique called opportunistic interference management achieves dirty paper coding capacity asymptotically with minimum feedback required. When there areKantennas at the base station withMmobile users in the cell, the proposed technique only requiresKinteger numbers related to channel state information between mobile users and base station. The encoding and decoding complexity of this scheme is the same as that of point‐to‐point communications, which makes the implementation of this technique easy. An antenna selection scheme is proposed at the base station to reduce the minimum required mobile users significantly at the expense of reasonable increase in feedback. In order to guarantee fairness, a new algorithm is presented that incorporates opportunistic interference management into existing Global System for Mobile communications (GSM) standard. Copyright © 2014 John Wiley & Sons, Ltd.

Tactical and emergency-response networks require efficient communication without a managed infrastructure. Recent work demonstrates that applying information-centric paradigms to the tactical edge can provide performance benefits over traditional address centric approaches. We propose SOCRATIC (SOCial RATe control for Information Centric networks), an approach that unifies replication and network coding to disseminate content by taking advantage of social content and context heuristics. SOCRATIC replicates network encoded blocks according to a popularity index metric that is shared during neighbor discovery. The number of encoded blocks that is relayed to a node depends on its own interest in a data object and its social popularity, i.e., how often and for how long the node meets other nodes. These blocks are subsequently replicated towards the subscriber if a stable path exists. We evaluate an implementation of SOCRATIC through network emulation of a tactical scenario and demonstrate that it can achieve better performance than traditional socially agnostic approaches.

A network model with both social and communication characteristics is considered. Different capacity regions are computed as a function of the social network size for each node. It has been shown that as the social connectivity among nodes improves, the likelihood of finding shorter path between source-destination pairs in the network increases which results in increase in the capacity compared to the original results by Gupta and Kumar [3].

A multi-user diversity approach, called Opportunistic Interference Management (OIM), is considered in connection with Orthogonal Frequency Division Multiplexing (OFDM) systems. The OIM is applied to each consecutive group of OFDM sub-channels that are highly correlated. We use the OIM to transmit information in Qg consecutive sub-channels to d users in parallel. The expected parallel transmissions per group of sub-channels is then computed. The results show that the maximum expected parallel transmissions is achieved almost surely when enough mobile users exist.

The capacity of a wireless network is studied when nodes communicate with one another in the context of social groups. All the nodes are assumed to have the same number of independent long-range social contacts, one of which each selects randomly as its destination. The Euclidean distance between a source and its social group members follows a power-law distribution and communication between any two nodes takes place only within the physical transmission range resulting in communication over multi-hop paths. The capacity order of such a composite network is derived as a function of the number of nodes, the social-group concentration, and the size of social groups. Our results demonstrate that when each node has constant number of contacts which does not increase with network size growth, and are geographically concentrated, then the network behaves similar to social networks and communication network does not have any effect on the throughput capacity. On the other hand, when the social contact population grows in time, or social connectivity among nodes is highly distributed, then the communication network is the dominant factor and the composite network behaves similar to wireless networks, i.e., the capacity is the same as Gupta and Kumar results. When neither social connectivity nor communication network is dominant, then the throughput capacity results are between these two extreme cases.

We study the impact of social connectivity on the capacity of wireless networks by considering different values of concentration factor and degree dispersion in scale-free networks. The result shows that a capacity similar to Gupta and Kumar [1] is achieved. Further investigation reveals that traditional transport capacity definition provides misleading conclusions for such network models. We show that nodes with different social status impact the capacity differently. By separating nodes with different social status in frequency and allocating separate bandwidth to them, it is shown that majority of nodes scale in this network. The results imply that in a network with social and communication characteristics, social behavior of the nodes has significant influence on the performance of such networks.

We proposed an analytical model to study the interplay between medium access control (MAC) and packet forwarding disciplines in multihop wireless networks. The model jointly considers the channel access procedure and the active portions of the topology, which is determined by packet forwarding discipline. The model allows the computation of per-node performance metrics for any given network topology and the combination of specific MAC protocols and packet forwarding methods. As an example of the applicability of our modeling framework, the analytical model is used to study the performance of multihop wireless networks using a contention-based MAC protocol (the IEEE 802.11 distributed coordination function) and a schedule-based MAC protocol (NAMA), together with different packet forwarding schemes in multihop networks. The analytical results derived from the model are validated with discrete-event simulations in Qualnet; the analytical results are shown to be very close to those attained by simulations.

A new routing metric for multi-hop wireless ad hoc networks is presented. The proposed metric is based on the computation of Signal-to-Noise Ratio (SNR) and minimization of wireless network outage probability in a fading environment. This metric improves the Quality-of-Service by reducing dropped packets. Further, by modeling the network with a Trellis diagram and then using Viterbi Algorithm to select the best routing path, we reduce the routing complexity of our approach. Simulation results demonstrate the improvement achieved by implementation of this new metric. Performance of the proposed metric is compared to other commonly used routing metrics such as Minimum Hop Count (MinHop), Expected Transmission Count (ETX) and two other SNR-based metrics in both mobile and stationary networks.

We study capacity of social networks when nodes communicate in a wireless environment. Such hybrid networks that are combination of wireless communication and social networks are defined as composite networks. Each node has at least one local contact in each of four directions of the network area and q(n) independent long-range contacts, one of which is selected as the destination. We study the throughput capacity for such networks containing n nodes assuming the same number of social contacts for all nodes. The nodes communicate using multi-hop communications through relaying the packet to one of their local contacts until the packet reaches the destination. The distance between source and its long-range social contacts follows power law distribution with parameter α. The order capacity is derived and compared for different values of α and q(n).

Previous work has shown that distributed cooperative MIMO systems (e.g., the hierarchical MIMO cooperation scheme) can provide large gains in capacity if the size of the MIMO systems is a function of the total number of nodes in the network (n). However, no results have been reported on the scaling laws of distributed cooperative MIMO systems when the number of transmit and receive antennas are of finite size, which is the case in real networks. This paper uses the extended network model to demonstrate that, if the size of distributed MIMO systems is restricted to a finite size, then there is at most a constant gain compared to point-to-point communications. Opportunistic interference management (OIM) is introduced as an alternative to distributed MIMO, and it is shown that it provides higher order gains than distributed cooperative MIMO systems under the same assumption of having a finite number of transmit and receive antennas. More specifically, OIM achieves a throughput capacity of C1(n) = Θ (D log log 2/θ log n/√n log n) in fading channels when the transmission range T(n) is Ω (√2/θ n), where θ is a constant parameter close to zero. This constitutes an order gain of Θ(log log 2/Θ log n) compared to point-to-point communications and distributed MIMO systems! Given that it is much easier to implement OIM schemes than distributed cooperative MIMO systems, these results indicate that OIM is a far better choice to making wireless ad hoc networks scale than distributed cooperative MIMO systems.

We define composite networks when nodes communicate only with their long-range social contacts and there is no direct link between a node and its long-range contact. Each node has a single long-range contact and all nodes within its transmission range are local contacts for the node. The long-range contact is the destination for each node in the network and since there is no direct link from source to its destination, nodes communicate using multi-hop communications. This is an extension of the famous work by Kleinberg to random wireless ad hoc networks. The throughput capacity of such networks is studied. The routing is based on each node sending the packets to one of its local contacts until the packets reach the destination. The long-range contact distance from a source follows power law distribution with parameter a which is a characteristic of social networks. A tight bound of throughput capacity for different values of a is derived. The results demonstrate that when a increases or equivalently the distance between source and destination decreases, the throughput capacity increases. For α >; 3, throughput capacity of ⊖(1/ log n) is achieved by utilizing simple point-to-point communications where n is the total number of nodes in the network. This is the maximum feasible throughput that can be achieved in point-to-point communications. The result demonstrates the effect of social groups on wireless ad hoc networks. A new parameter called degradation factor is defined which illustrates the asymptotic behavior of networks for large values of n1.

We consider a network with n nodes distributed uniformly in a unit square. We show that, under the protocol model, when ns= Ω (log(n)1+α) out of the n nodes, each act as source of independent information for a multicast group consisting of m randomly chosen destinations, the per-session capacity in the presence of network coding (NC) has a tight bound of Θ(√n/ns√mlog(n)) when m = O(n/log(n)) and Θ(1/ns) when m = Ω(n/log(n)). In the case of the physical model, we consider ns= n and show that the per-session capacity under the physical model has a tight bound of Θ(1/√mn) when m = O(n/(log(n))3), and Θ(1/n) when m = Ω(n/log(n)). Prior work has shown that these same order bounds are achievable utilizing only traditional store-and-forward methods. Consequently, our work implies that the network coding gain is bounded by a constant for all values of m. For the physical model we have an exception to the above conclusion when m is bounded by O(n/(log(n))3) and Ω(n/log(n)). In this range, the network coding gain is bounded by O((log(n))1/2).

We present capacity and delay scaling laws for random wireless ad hoc networks under all information dissemination modalities (unicast, multicast, broadcast and anycast) when nodes are endowed with multi-packet reception (MPR) capabilities. Information dissemination modalities are modeled with an (n, m, k)-cast formulation, where n, m, and k denote the number of nodes in the network, the number of destinations for each communication group, and the actual number of communication group members that receives the information (i. e., k ≤ m ≤ n), respectively. We show that Θ(R(n)\√m/k), Θ(1/k), and Θ(R2(n)) bits per second constitute a tight bound for the throughput capacity of random wireless ad hoc networks under the protocol model when m = O(R-2(n)), Ω(k) = R-2(n)= O(m), and k = Ω(R-2(n)), respectively. R(n) denotes the receiver range which depends on the decoding complexity of the nodes. For the minimum receiver range of Θ(√(log n/n)) to guarantee network connectivity, a gain of Θ(log n) for (n, m, k)-casting is attained with MPR compared to the capacity attained when receivers can decode at most one transmission at a time in . Furthermore, we derive the capacity-delay tradeoff of (n, m, k)-casting when MPR is used. We show that the use of MPR can lead to both increased network capacity and reduced delays in wireless ad hoc networks.

ABSTRACT A new routing metric for multihop wireless ad hoc networks is presented. The proposed metric is based on the computation of signal‐to‐noise ratio and path minimization of wireless ad hoc network outage probability in a fading environment. This metric improves the quality of service by reducing the number of dropped packets. Further, by modeling the network with a Trellis diagram and then using Viterbi algorithm to select the best routing path, we reduce the routing complexity of our approach. The performance of the proposed metric is compared with other commonly used routing metrics such as minimum hop count, expected transmission count, and two other signal‐to‐noise ratio‐based metrics in both mobile and stationary networks. Simulation results demonstrate the improvement achieved by this new metric. Copyright © 2011 John Wiley & Sons, Ltd.

A new cross-layer design taking advantage of OFDMA in ad hoc networks is presented. OFDMA technology is exploited at the physical layer to improve data rate through multiuser diversity and to enhance network throughput by enabling multiple concurrent transmissions over orthogonal subchannels, each consisting of a group of tones. A new tone-assignment algorithm is presented that takes advantage of channel fading and is adapted to the limitations of ad hoc networks and operates alongside the signaling of the resulting medium access control (MAC) protocol called Concurrent Communication medium Access or CoCo-MAC. The new MAC addresses the synchronization requirements of OFDMA and the tone assignment algorithm's necessities, and also enables concurrent initiation of data transmissions from multiple nodes to the same receiver or from a single transmitter to multiple receivers. We present simulation results on the throughput advantages of our technique compared to traditional tone assignment algorithms and MAC protocols based on contention-based avoidance of interference.

We study the scaling laws for wireless ad hoc networks in which the distribution of n nodes in the network is homogeneous but the traffic they carry is heterogeneous. More specifically, we consider the case in which a given node is the data-gathering sink for k sources sending different information to it, while the rest of the s = n - k nodes participate in unicast sessions with random destinations chosen uniformly. We present a separation theorem for heterogeneous traffic showing that the optimum order throughput capacity can be attained in a wireless network in which traffic classes are distributed uniformly by endowing each node with multiple radios, each operating in a separate orthogonal channel, and by allocating a radio per node to each traffic class. Based on this theorem, we show how this order capacity can be attained for the unicast and data-gathering traffic classes by extending cooperative communication schemes that have been proposed previously.

A new cross-layer design taking advantage of OFDMA in ad hoc networks is presented. OFDMA technology is exploited at the physical layer to improve data rate through multiuser diversity and to enhance channel throughput by enabling multiple concurrent transmissions over orthogonal subchannels, each consisting of a group of tones or subcarriers. The proposed Subchannel Selection Algorithm (SSA) addresses the distribution of subchannels and the new Tone Assignment Algorithm (TAS) takes advantage of fading and is adapted to the limitations of ad hoc networks. TAS operates alongside the signaling of the resulting medium access control (MAC) protocol called Concurrent Communication medium Access or CoCo-MAC. The new MAC addresses the synchronization requirements of OFDMA and the needs of the tone assignment algorithm, and also enables concurrent initiation of data transmissions from multiple nodes to the same receiver or from a single transmitter to multiple receivers. We present analysis and simulation results on the throughput advantages of our technique compared to previous spectrum allocation and MAC protocols based on the avoidance of multiple access interference.

An analytical model is introduced for the study of the interplay between medium access control (MAC) and packet forwarding disciplines used in multi-hop wireless networks. The model incorporates the likelihood with which nodes access the channel, which is determined by the MAC protocol, and the creation of active portions of the topology, which is given by the packet forwarding discipline. The model allows the computation of per-node performance metrics for any given network topology and the combination of specific MAC protocols and packet forwarding methods. As an example of the applicability of our modeling framework, the analytical model is used to study the performance of multi-hop wireless networks using a contention-based MAC protocol (the IEEE 802.11 distributed coordination function) and a schedule-based MAC protocol (NAMA), together with different packet forwarding schemes in multi-hop networks. The analytical results derived from the model are validated with discrete-event simulations in Qualnet; the analytical results are shown to be very close to those attained by simulations.

We introduce a new multiuser diversity concept with which multiple transmitters can communicate without causing significant interference to each other. The new scheme, called Opportunistic Interference Management (OIM), significantly reduces the feedback required in distributed Multiple-Input Multiple-Output (MIMO) systems, and requires an encoding and decoding complexity that is similar to that of point-to-point communications. We show that our proposed OIM scheme achieves a per-node throughput capacity of Θ (log(T(n))/√nT(n)) in a wireless network of n nodes and communication range of T(n) = Ω(√log n). This represents a gain of Θ (log(T(n))) compared to simple point-to-point communication. As such, OIM represents a practical alternative to attaining capacity gains similar to those attainable in theory with distributed MIMO systems, and opens up a new area of research for the development of medium access control protocols aimed at managing interference.

We compute the throughput capacity of random dense wireless ad hoc networks for multi-pair unicast traffic in which nodes are endowed with multi-packet reception (MPR) capabilities. We show that ¿ ((R(n))(1-2)/¿/n1/¿) and ¿ (R(n)) bits per second constitute tight bounds for the throughput capacity under the physical and protocol model assumptions, respectively, where n is the total number of nodes in the network, ¿ > 2 is the path-loss parameter in the physical model, and R(n) is the MPR communication range. In so doing, we close the gap between the lower and upper bounds of throughput capacity in the physical model. Compared to the capacity of point-to-point communication reported by Gupta and Kumar, MPR increases the order capacity of random wireless ad hoc networks under both protocol and physical models by at least ¿(log n) and ¿ ((log n)¿-2/2¿), respectively. We address the cost incurred in increasing the throughput capacity of wireless ad hoc networks over what can be attained when sources and destinations communicate over multi-hop paths under the physical model assumption. We define the power efficiency ¿(n) as the bits of information transferred per unit time (second) in the network for each unit power, and compute such power efficiency for different techniques. We show that a lower power efficiency is attained in order to achieve higher throughput capacity.

This paper presents a mathematical framework for the evaluation of the performance of proactive and reactive routing protocols in mobile ad hoc networks (MANETs). This unified framework provides a parametric view of protocol performance, which in turn provides a deeper insight into protocol operations and reveals the compounding and interacting effects of protocol logic and network parameters. The parametric model comes from a combinatorial model, where the routing logic is synthesized along with the characterization of MAC performance. Each wireless node is seen independently as a two-customer queue without priority, where the two types of customers are unicast and broadcast packets. The model captures the essential behavior and scalability limits in network size of both classes of routing protocols, and provides valuable guidance on the performance of reactive or proactive routing protocols under various network configurations and mobility conditions. The analytical results obtained with the proposed model are in close agreement with simulation results obtained from discreteevent Qualnet simulations.

We study the scaling laws for wireless ad hoc network in which the distribution of nodes in the network is homogeneous but the traffic is heterogeneous. More specifically, we consider the case in which a node is the sink to k sources sending different information, while the rest of the nodes are part of unicast communications with a uniform assignment of source-destination pairs. We prove that the capacity of these heterogeneous networks is ¿(n/Tmax), where Tmaxand n denote the maximum traffic for a cell and the number of nodes in the network, respectively. Equivalently, our derivations reveal that, when n - k ¿ constant, the network capacity is equal to ¿(¿(n/(log n))) for k = O(¿(n log n)) and equal to ¿ (n/k) for k = ¿(¿(n log n)). Furthermore, the network capacity is ¿(1) when n - k = constant. These results demonstrate that the capacity of a heterogeneous network is dominated by the maximum congestion in any area of the network.

We introduce a new multiuser diversity scheme for interference management in cellular networks. A base station with K antennas communicates with at most K out of M mobile stations. It is proven that, if K ¿ M, then K independent data streams can be transmitted to K mobile stations with no need for cooperative joint decoding by such stations. This result is based on a new multiuser diversity concept that allows parallel communication in the network without any cooperation among mobile stations. If the network does not have enough mobile stations, then some of the users need to jointly decode their corresponding data streams. The result suggests the existence of a tradeoff between multiuser diversity and cooperation in the downlink of cellular networks. Our interference management approach is based on a new multiuser diversity concept that achieves the capacity of dirty paper coding (DPC) asymptotically. Surprisingly, this gain is achieved without requiring full channel state information (CSI) and only K integers related to CSI are fed back from mobile stations to the base station. An additional advantage of this scheme is the fact that the encoding and decoding of signals for this distributed MIMO system is based on simple point-to-point communications.

We demonstrate that the gain attained by network coding (NC) on the multicast capacity of random wireless ad hoc networks is bounded by a constant factor. We consider a network with n nodes distributed uniformly in a unit square, with each node acting as a source for independent information to be sent to a multicast group consisting of m randomly chosen destinations. We show that, under the protocol model, the per- session capacity in the presence of arbitrary NC has a tight bound of Theta (1/radic(mnlog(n))) when m = O(n/(log(n))) and Theta(1/n) when m = Omega(n/(log(n))). Our result follows from the fact that prior work has shown that the same order bounds are achievable with pure routing based only on traditional store-and-forward methods.

We present the concurrent transmission or reception multiple access (CTRMA) protocol as an example of embracing interference in wireless ad hoc networks, even when each node is endowed with a single half-duplex radio and a single antenna. CTRMA uses OFDMA to enable each node to either send or receive multiple concurrent transmissions over orthogonal subchannels (groupings of subcarriers). With CTRMA, a node transmits multiple transmissions at the same time by negotiating the subchannels over which transmissions take place by using information attained with a channel priority assignment algorithm. CTRMA supports dynamic bandwidth selection and enhances channel reuse. We prove the correctness of CTRMA and use simulation experiments to illustrate the major performance advantages of CTRMA over prior channel access protocols proposed for single-radio single-channel, single-radio multi-channel and multi-radio multi-channel wireless ad hoc networks.

We show that network coding (NC) does not provide any order gain in the multicast capacity of random wireless ad hoc networks. We consider a network with n nodes distributed uniformly in a unit square, with each node acting as a source for independent information to be sent to a multicast group consisting of m randomly chosen destinations. We show that, in the presence of NC, the per-session capacity under the protocol model has a tight bound of Theta (1/(mnlog(n))) when m = O (n/log(n)) Theta (1/n) when m = Omega (n/log/n). Furthermore, we show that the per-session capacity under the physical model has a tight bound of Theta (1/(mn)) when m = O (n/(log(n))3), and Theta (1/n) when m = Omega (n/log(n)). Prior work has shown that these same order bounds are achievable utilizing only traditional store-and- forward methods.

We establish a tight max-flow min-cut theorem for multi-commodity routing in random geometric graphs. We show that, as the number of nodes in the network n tends to infinity, the maximum concurrent flow (MCF) and the minimum cut-sparsity scale as ¿(n2r3(n)/k), for a random choice of k = ¿(n) source-destination pairs, where n and r(n) are the number of nodes and the communication range in the network respectively. The MCF equals the interference-free capacity of an ad-hoc network. We exploit this fact to develop novel graph theoretic techniques that can be used to deduce tight order bounds on the capacity of ad-hoc networks. We generalize all existing capacity results reported to date by showing that the per-commodity capacity of the network scales as ¿(1/r(n)k) for the single-packet reception model suggested by Gupta and Kumar, and as ¿(nr(n)/k) for the multiple-packet reception model suggested by others. More importantly, we show that, if the nodes in the network are capable of (perfect) multiple-packet transmission (MPT) and reception (MPR), then it is feasible to achieve the optimal scaling of ¿(n2r3(n)/k), despite the presence of interference. In comparison to the Gupta-Kumar model, the realization of MPT and MPR may require the deployment of a large number of antennas at each node or bandwidth expansion. Nevertheless, in stark contrast to the existing literature, our analysis presents the possibility of actually increasing the capacity of ad-hoc networks with n even while the communication range tends to zero!

We introduce a collaboration-driven approach to the sharing of the available bandwidth in wireless ad hoc networks, which we call many-to-many communication, that allows concurrent multi-packet transmissions (MPTs) and multi-packet receptions (MPRs). Many-to-many communication also permits one-time multi-copy relaying of the same packet, which reduces the packet delivery delay compared to single-copy relaying without any penalty in capacity. Our scheme is based on the integration of multi-user detection and position-location information with frequency and code division in mobile ad hoc networks (MANETs). Transmissions are divided in frequency and codes according to node locations, and successive interference cancellation (SIC) is used at receivers to allow them to decode and use all transmissions from strong interfering sources. Consequently, the interference is divided into constructive interference (COI) and destructive interference (DEI). We show that, if each node is allowed to expand its bandwidth, both the link's Shannon capacity and the per source-destination throughput scale like O(nalpha/2) (upper-bound) and Omega[f(n)] (lower-bound), for n nodes in the network, a path loss parameter alpha > 2, and 1les f(n)alpha/2.

We present the first unified modeling framework for the computation of the capacity-delay tradeoff of random wireless ad hoc networks. This framework considers information dissemination by means of unicast routing, multicast routing, broadcasting, or different forms of anycasting. We introduce (n, m, k) -casting as a generalization of all forms of one-toone, one-to-many, and many-to-many information dissemination in wireless networks. In this context, n, m, and k denote the total number of nodes in the network, the number of destinations for each communication group, and the actual number of communication-group members that receive information (k ¿ m), respectively. We describe the capacity-delay tradeoff for (n, m, k) -casting in wireless ad hoc networks in which receivers perform single-packet reception (SPR). Our results are consistent with prior results in wireless networks and extend them to the general (n,m,k) -cast case.

We present statistical models to accurately evaluate the distribution of the lifetime of wireless links in a mobile ad hoc network (MANET) in which nodes move randomly within constrained areas. We show that link lifetime can be computed through a two-state Markov model and further apply the computed statistics to the optimization of segmentation schemes of an information stream. Summarizing all these results, we further provide a comprehensive analysis on throughput, delay, and storage requirements for MANETs with restricted node mobility.

We study the broadcast throughput capacity of random wireless ad hoc networks when the nodes are endowed with multipacket reception (MPR) capability. We show that, in such networks, a per-node throughput capacity of Theta(R2(n)) bits per second can be achieved as a tight bound (i.e., upper and lower bounds) for broadcast communication, where R(n) is the receiver range that depends on the complexity of the nodes. Compared to ad hoc networks in which receivers decode at most one transmission at a time, the minimum capacity gain of MPR-based networks is Theta(logn). This is attained when the minimum value for R(n) is used, which equals the minimum transmission range needed to guarantee connectivity in the network (r(n) = Theta(radiclogn/n)).

We propose ORCHESTRA, a channel access protocol that uses reservations and virtual MIMO to provide high throughput and bounded channel access delays. Channel access process is divided into a contention-based access period and a scheduled access period. To attain high throughput, nodes build the channel schedule using the contention-based access period, and utilize the spatial multiplexing gain of virtual MIMO links in the scheduled access period. To attain bounded channel access delays, nodes reserve time slots through opportunistic reservations. We evaluate the performance of ORCHESTRA through numerical analysis and simulations, and show that it results in much better throughput, delay, and jitter characteristics than simply using MIMO nodes together with scheduled access (i.e., NAMA) or contention-based access (i.e., IEEE 802.11 DCF).

We present a mathematical framework for the performance evaluation of proactive and reactive routing protocols operating in mobile ad hoc networks (MANETs). The model captures the functionality of the routing protocols together with the characterization of the performance of the medium access control protocol (MAC). It reveals the interplay between the protocol functionality and network parameters, and provides new insight on the relative benefits of proactive and on-demand routing in MANETS. The analytical results are corroborated with results obtained using discrete-event simulations.

We present the first unified modeling framework for the computation of the throughput capacity of random wireless ad hoc networks in which information is disseminated by means of unicast routing, multicast routing, broadcasting, or different forms of anycasting. We introduce (n,m, k)-casting as a generalization of all forms of one-to-one, one-to-many and many-to-many information dissemination in wireless networks. In this context, n, m, and k denote the total number of nodes in the network, the number of destinations for each communication group, and the actual number of communication-group members that receive information (i.e., k lesm), respectively. We compute upper and lower bounds for the (n, m, k)- cast throughput capacity in random wireless networks. When m = k = ominus(1), the resulting capacity equals the well-known capacity result for multi-pair unicasting by Gupta and Kumar. We demonstrate that ominus(1/radic(mnlogn)) bits per second constitutes a tight bound for the capacity of multicasting (i.e., m = k < n) when m les ominus (n/(log n)). We show that the multicast capacity of a wireless network equals its capacity for multi-pair unicasting when the number of destinations per multicast source is not a function of n. We also show that the multicast capacity of a random wireless ad hoc network is ominus (1/n), which is the broadcast capacity of the network, when m ges ominus(n/ log n). Furthermore, we show that ominus (radicm/(kradic(n log n))),ominus(1/(k log n)) and ominus(1/n) bits per second constitutes a tight bound for the throughput capacity of multicasting (i.e., k < m < n) when ominus(1) les m les ominus (n/ log n), k les ominus(n / log n) les m les n and ominus (n/ log n) les k les m les n respectively.

This paper presents the first comprehensive capacity-delay tradeoff study for random wireless ad hoc networks under all information dissemination modalities (unicast, multicast, broadcast, anycast) when nodes operate either with multi-packet reception (MPR) or single-packet reception (SPR) capabilities. Our results demonstrate that for unicast, increasing capacity requires additional delay for SPR similar to the results in [1] while MPR incurs no penalty, i.e., we can increase capacity and decrease delay simultaneously for MPR. For multicast, there is no tradeoff for both SPR and MPR. However, similar tradeoff can be observed for broadcast when MPR is used while there is no tradeoff with SPR.

We establish a tight max-flow min-cut theorem for multicommodity routing in random geometric graphs. We show that, as the number of nodes in the network n tends to infinity, the maximum concurrent flow (MCF) and the minimum cut-capacity scale as Theta(n2r3(n)/k) for a random choice of k ges Theta(n) source-destination pairs, where r(n) is the communication range in the network. We exploit the fact, that the MCF in a random geometric graph equals the interference-free capacity of an ad-hoc network under the protocol model, to derive scaling laws for interference-constrained network capacity. We generalize all existing results reported to date by showing that the per-commodity capacity of the network scales as Theta(1/r(n)k) for the single-packet reception model suggested by Gupta and Kumar, and as Theta(nr(n)/k) for the multiple-packet reception model suggested by others. More importantly, we show that, if the nodes in the network are capable of multiple-packet transmission and reception, then it is feasible to achieve the optimal scaling of Theta(n2r3(n)/k), despite the presence of interference. This result provides an improvement of Theta(nr2(n)) over the highest achieved capacity reported to date. In stark contrast to the conventional wisdom that has evolved from the Gupta-Kumar results, our results show that the capacity of ad-hoc networks can actually increase with n while the communication range tends to zero!

We address the cost incurred in increasing the transport capacity of wireless ad hoc networks over what can be attained when sources and destinations communicate over multi-hop paths and nodes can transmit or receive at most one packet at a time. We define the energy efficiency ·(n) as the bit-meters of information transferred in the network for each unit energy. We compute the energy efficiency of many different techniques aimed at increasing the capacity of wireless networks and show that, in order to achieve higher transport capacity, a lower energy efficiency must be attained. Using the physical model, we compute the throughput capacity of random wireless ad hoc networks in which nodes are endowed with multi-packet reception (MPR) capabilities. We show that λ(n)= Θ (R(n))(1-2/α) / n1/α) bits per second constitutes a tight upper and lower bound for the throughput of random wireless ad hoc networks, where α>2 is the path loss parameter in the physical model, n is the total number of nodes in the network, and R(n) is the MPR receiver range. In doing so, we close the gap between the lower and upper bounds for the throughput capacity of wireless networks in the physical model. Compared to the original result derived for plain routing by Gupta and Kumar, MPR achieves a capacity gain of at least Θ((log n)α-2/2α) when RR(n)= Θ(√log n/n).

We propose the distributed channel access scheduling using virtual MIMO protocol (CHAMP). In CHAMP, nodes build a channel schedule in a distributed fashion to utilize the spatial multiplexing gain of virtual MIMO links. We also use a cooperative relay strategy to fully utilize the available degrees of freedom of virtual antenna arrays. We analyze the single-hop saturation throughput of CHAMP and evaluate its multi-hop performance through simulation. The results show that CHAMP can achieve better performance than a contention-based MAC protocol using MIMO links.

We introduce a collaboration-driven approach to the sharing of the available bandwidth in wireless ad hoc networks, which we call many-to-many cooperation, that allows concurrent many-to-many communication. This scheme is based on the integration of multi-user detection and position-location information with frequency and code division in mobile ad hoc networks (MANETs). Transmissions are divided in frequency and codes according to nodal locations, and successive interference cancellation (SIC) is used at receivers to allow them to decode and use all transmissions from strong interfering sources. Consequently, the interference is divided into constructive interference (COI) and destructive interference (DEI). We show that, if each node is allowed to expand its bandwidth, both the link's Shannon capacity and the per source-destination throughput scale likeO(nalpha/2) (upper-bound) and Omega[f(n)] (lower-bound), for n nodes in the network, a path loss parameter alpha > 2, and 1 les f(n)alpha/2. Many-to-many cooperation allows multi-copy relaying of the same packet, which reduces the packet delivery delay compared to single-copy relaying without any penalty in capacity.

We propose the topology-aware hybrid channel access using virtual MIMO protocol (THAMP). In THAMP, nodes build the channel schedule in a distributed fashion based on the topology information and utilize different antenna gains of virtual MIMO links. Through the joint utilization of spatial diversity gain and spatial multiplexing gain at different nodes, THAMP increases the spatial reuse of the system and reduces the possible collisions of control packets. Simulation results show that THAMP can achieve a better performance than a contention-based MAC protocol using MIMO links.

The protocols used in ad hoc networks today are based on the assumption that the best way to approach multiple access interference (MAI) is to avoid it. Unfortunately, as the seminal work by Gupta and Kumar has shown, this approach does not scale. We demonstrate that protocol architectures that exploit multi-packet reception (MPR) do increase the order of the transport capacity of random wireless ad hoc networks for multi-pair unicast applications by a factor of Θ(log n) and Θ(log (log n)) under the protocol and physical models, respectively, where n is the number of nodes in the network. By contrast, Liu, Goeckel, and Towsley have shown that network coding (NC) does not increase the order capacity of wireless ad hoc networks under the protocol and physical models.

rdquoThe paper presents a mathematical framework for quantifying the overhead of proactive routing protocols in mobile ad hoc networks (MANETs). We focus on situations where the nodes are randomly moving around but the wireless transmissions can be decoded reliablely, when nodes are within communication range of each other. We explicitly present a framework to model the overhead as a function of stability of topology and analytically characterize the statistical distribution of topology evolutions. The OLSR protocol is further singled out for a detailed analysis, incorporating the proposed analytical model. Results are compared against Qualnet simulations for random movements, which corroborate the essential characteristics of the analytical results. The key insight that can be drawn from the analytical results of this paper is that nodal movements will drive up the overhead by a penalty factor, which is a function of the overall stability of the network.

The protocols used in ad hoc networks today are based on the assumption that the best way to approach multiple access interference (MAI) is to avoid it. Unfortunately, as the seminal work by Gupta and Kumar has shown, this approach does not scale. Recently, Ahlswede, Ning, Li, and Yeung showed that network coding (NC) can attain the max-flow min-cut throughput for multicast applications in directed graphs with point-to-point links. Motivated by this result, many researchers have attempted to make ad hoc networks scale using NC. However, the work by Liu, Goeckel, and Towsley has shown that NC does not increase the order capacity of wireless ad hoc networks for multi-pair unicast applications. We demonstrate that protocol architectures that exploit multi-packet reception (MPR) do increase the order capacity of random wireless ad hoc networks by a factor Θ(log n) under the protocol model. We also show that MPR provides a better capacity improvement for ad hoc networks than NC when the network experiences a single-source multicast and multi-pair unicasts. Based on these results, we introduce design problems for channel access and routing based on MPR, such that nodes communicate with one another on a many-to-many basis, rather than one-to-one as it is done today, in order to make ad hoc networks truly scalable.

Multiuser diversity has been shown to increase the throughput of mobile ad hoc wireless networks (MANETs) when compared to fixed wireless networks. This paper addresses a multiuser diversity strategy that permits one of multiple one-time relays to deliver a packet to its destination. We show that the throughput of the original single one-time relay strategy is preserved by our multi-copy technique. The reason behind achieving the same asymptotic throughput is the fact that, as we demonstrate in this paper, interference for communicating among closest neighbors is bounded for different channel path losses, even when goes to infinity. We show that a significant delay reduction is possible by multi-copy relaying when is finite. Furthermore, we find that the average delay and delay variance for both the one and multi-copy relay strategies scale like and , respectively. We derive an approximation of the delay for multi-copy forwarding scheme and demonstrate that this approximation is very close to simulation results in MANET systems.

Design of space-time codes that scale with the number of transmit antennas is a difficult problem. In this paper, we introduce a new family of space-time trellis codes (STTC) that can be applied to any arbitrary number of transmit antennas. This family is constructed by utilizing QPSK STTCs as component codes to construct STTCs with larger constellation size. Unlike the design of existing STTC, the search space in our design does not grow exponentially with the constellation size or the number of transmit antennas. Additionally, we propose a practical approach to reduce the computational complexity of our proposed scheme using interference mitigation techniques. Simulation results compare the performance of our approach with that of space-time block codes for the case of two transmit antennas and several different number of receive antennas, a spectral efficiency of 4 bits/s/Hz, and slow Rayleigh fading channels.

Space-time convolutional code (STCC) is a technique that combines transmit diversity and coding to improve reliability in wireless fading channels. In this paper, we demonstrate a technique to design MQAM STCCs with high spectral efficiencies utilizing QPSK STCC as component code. The approach is based on a unique construction of M-QAM signal from several QPSK signals. The upper bound on the pairwise block error probability of the new scheme is derived. Simulation result demonstrates that the new technique outperforms existing M-QAM STCC design for M = 16

Space time convolutional codes (STCCs) are an effective way to combine transmit diversity with coding. The computational complexity of designing STCCs generally increases exponentially with the constellation size of the transmitted symbols. In this paper, we first present an innovative approach to design STCCs with high spectral efficiencies by utilizing QPSK STCCs as component codes and consequently. Unlike existing techniques, the search space does not grow exponentially with the constellation size. Then, we present two approaches to reduce the computational complexity of our proposed scheme. This scheme is applicable to cases with any number of transmit antennas without any requirement to change the encoder design. Simulation results evaluate the performance of our approach for the case of two transmit antennas and several different number of receive antennas, a spectral efficiency of 4 bits/s/Hz, and slow Rayleigh fading channels.

We introduce a new communication scheme for mobile wireless ad hoc networks (MANETs) utilizing the concept of cooperative many-to-many communication, called opportunistic cooperation1, as opposed to the traditional approach that emphasizes on point-to-point communication. In the new paradigm, the adjacent nodes no longer interfere with each other but rather cooperate. Our analysis is for MANETs when all the nodes in the network are endowed with M antennas. We derive two upper bounds on the ergodic capacity per node in the network. These upper bounds are compared with Monte-Carlo simulation of point-to-point and many-to-many communications. We show that one of our upper bounds is a tight bound. Also, we demonstrate that the capacity of MANETs with multiple antennas is improved significantly using cooperation as compared to non-cooperative schemes, i.e., point-to-point communication.

In this paper, we propose a new two-stage (TS) structure for computationally efficient maximum-likelihood decoding (MLD) of linear block codes. With this structure, near optimal MLD performance can be achieved at low complexity through TS processing. The first stage of processing estimates a minimum sufficient set (MSS) of candidate codewords that contains the optimal codeword, while the second stage performs optimal or suboptimal decoding search within the estimated MSS of small size. Based on the new structure, we propose a decoding algorithm that systematically trades off between the decoding complexity and the bounded block error rate performance. A low-complexity complementary decoding algorithm is developed to estimate the MSS, followed by an ordered algebraic decoding (OAD) algorithm to achieve flexible system design. Since the size of the MSS changes with the signal-to-noise ratio, the overall decoding complexity adaptively scales with the quality of the communication link. Theoretical analysis is provided to evaluate the potential complexity reduction enabled by the proposed decoding structure.

Multiuser diversity has been shown to increase the throughput of mobile ad hoc wireless networks (MANET) when compared to fixed networks. We present a different multiuser diversity strategy for packet relaying, which permits more than one-copy (multi-copies) of a packet to be received by relay nodes, thus allowing us to decrease the delay on such networks for a fixed number of total users n. We show that the /spl theta/(1) throughput is preserved by our multi-copy technique when n goes to infinity. In addition, we find that the average delay and variance scale like /spl theta/(n) and /spl theta/(n/sup 2/) respectively for both one-copy and multi-copies techniques. We also show that for a fixed n and by multi-copy forwarding, a maximum bounded delay value can he guaranteed.

This work presents a maximum-likelihood (ML) decoding algorithm for linear block codes. In this algorithm, the optimal performance is achieved at low computational complexity through a two-stage processing. At the first stage, a minimum sufficient set S that includes the optimal solution is estimated. With the minimum sufficient set, the decoding complexity can be greatly reduced without performance degradation. At the second stage, ordered processing is performed within the estimated minimum sufficient set S to obtain the optimal solution. During the ordered processing, S is adoptively updated to minimize the computational complexity, and an effective stopping criterion is used to decide whether the optimal solution is found. Ordered processing not only helps to find the optimal solution quickly, but also enables simplified sub-optimal solutions with bounded block error rates. The proposed algorithm is also extended to decode block turbo codes. Finally, simulation results are given to show that this algorithm achieves optimal performance with a low average computational complexity.

Polarization Mode Dispersion (PMD) imposes a new challenge for high speed optical transmission. This paper proposes a novel Single-Input Multiple-Output (SIMO) Decision Feedback Equalizer (DFE) technique to combat all orders of PMD-induced distortion. The scheme is based on a new SIMO PMD channel model, which utilizes information embedded in both polarization states. Explicit expressions for the filter coefficients are provided. The simulation results show that the new scheme provides improvement over first order optical compensator and conventional DFE.

Multiuser diversity has been shown to increase the throughput of mobile ad-hoc wireless networks (MANET) when compared to fixed wireless networks. This paper addresses a multiuser diversity strategy that permits one of multiple one-time relays to deliver a packet to its destination. We show that the /spl theta/(1) throughput of the original single one-time relay strategy is preserved by our multi-copy technique. The reason behind achieving the same asymptotic throughput is the fact that, as we demonstrate in this paper, interference for communicating among closest neighbors is hounded for different channel path losses, even when n goes to infinity. We find that the average delay and its variance scale like /spl theta/(n) and /spl theta/(n/sup 2/), respectively, for both the one and multi-copy relay strategies. Furthermore, while for finite n the delay values in the single-copy relaying strategy are not bounded, our multi-copy relay scheme attains bounded delay.

We present a technique to derive M-quadrature amplitude modulation (QAM) signals from quaternary phase-shift keying (QPSK) constellations when M=2/sup n/ and n is an even number. By utilizing QPSK Golay sequences, we have constructed M-QAM sequences with low peak-to-mean envelope power ratios. Several upper bounds for these M-QAM sequences were derived.

We propose a construction scheme of composite QAM sequence by weighted sum of the QPSK sequences that have relatively low peak-to-mean envelope power ratio (PMEPR). We derive a general expression of the upper bound on PMEPR for such composite QAM sequences. For the proposed QAM sequence construction, which we call 'linear-sum mapping', we investigate the information transfer capability. Although it is inferior to Gray mapping, by utilizing the decisions of the previously decoded codeword and employing successive decoding, we can obtain almost the same performance as that of Gray mapping.

We propose an adaptive and parameter-independent per-survivor processing algorithm to improve the receiver performance on time-varying channels. With a variable step size for a plurality of survivor paths, this new method eliminates the dependency of all the survivor paths and improves the convergence rate of channel estimation.

The performance of a turbo code with short block length depends critically on the interleaver design. There are two major criteria in the design of an interleaver: the distance spectrum of the code and the correlation between the information input data and the soft output of each decoder corresponding to its parity bits. This paper describes a new interleaver design for turbo codes with short block length based on these two criteria. A deterministic interleaver suitable for turbo codes is also described. Simulation results compare the new interleaver design to different existing interleavers.

A pseudo-maximum-likelihood data estimation (PML) algorithm for discrete channels with finite memory in additive white Gaussian noise environment is developed. Unlike the traditional methods that utilize the Viterbi algorithm (VA) for data sequence estimation, the PML algorithm offers an alternative solution to the problem. The simplified PML algorithm is introduced to reduce the computational complexity of the PML algorithm for channels with long impulse response. The adaptive version of the PML algorithm suitable for time-varying channels such as frequency-selective Rayleigh fading channels is also introduced. Computer simulation results demonstrate the performance of these algorithms and compare them to the VA-based techniques for different types of channels. The performance design criterion for the PML algorithm is derived in the Appendix.

The performance of a Turbo code depends on the interleaver design. There are two major criteria that can be considered in the design of an interleaver. Distance spectrum properties of the code and the correlation of the extrinsic information with the input data are the two major criteria in designing an interleaver. This paper describes a new interleaver design based on these two criteria. Simulation results compare the new interleaver design to different existing interleavers. The distance spectrum properties of the Turbo code are compared for different interleaver choices. A new solution to the interleaver edge effects is proposed here.

We propose a new 2-stage soft-output equalizer (TSSOE) structure for spatial-temporal processing in EDGE. The TSSOE is the cascade of a delayed decision-feedback sequence estimator (DDFSE) and maximum a posteriori probability (MAP) estimator. The TSSOE uses the final-decision symbols from the DDFSE to estimate the noise variance and truncates the channel memory for the following MAP estimator. Compared with the soft-output DDFSE, the TSSOE reduces both the feedback symbol errors and the noise variance estimation error. At a 10% block error rate and 20 dB signal-to-noise ratio, the TSSOE requires about 10 dB lower signal-to-interference ratio than the soft-output DDFSE for the GSM typical urban channel profile.

A multi-tone QAM modulation technique suitable for discrete multi-tone (DMT) systems based on the combination of the so called turbo codes and trellis code modulation (TCM) is presented. The advantage of this system is its high coding gain together with the bandwidth efficiency which is suitable for asymmetric digital subscriber line (ADSL) modems for twisted pair wires. Some suggestion is given to combat burst noise, frequency selective noise, or interference in the design of the turbo code. The results are compared to the recommended 16 state 4-dimensional Wei code in the ANSI standard. Simulation results demonstrate substantial coding gain for all QAM modulation levels from 4 QAM to 256 QAM.