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.

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.

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.

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.

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 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 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 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 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).

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.

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.