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We consider a wireless device-to-device network, where $n$ nodes are uniformly distributed at random over the network area. We let each node caches M$ files from a library of size m\geq M$ . Each node in the network requests a file from the library independently at random, according to a popularity distribution, and is served by other nodes having the requested file in their local cache via (possibly) multihop transmissions. Under the classical “protocol model” of wireless networks, we characterize the optimal per-node capacity scaling law for a broad class of heavy-tailed popularity distributions, including Zipf distributions with exponent less than one. In the parameter regime of interest, i.e., m=o(nM) for heavy-tailed popularity distributions. This scaling is constant with $n$ , thus yielding throughput scalability with the network size. Furthermore, the multihop capacity scaling can be significantly better than for the case of single-hop caching networks, for which the per-node capacity is $\Theta (M/m)$ . The multihop capacity scaling law can be further improved for a Zipf distribution with exponent larger than some threshold > 1, by using a decentralized random caching uniformly across a subset of most popular files in the library. Namely, ignoring a subset of less popular files (i.e., effectively reducing the size of the library) can significantly improve the throughput scaling while guaranteeing that all nodes will be served with high probability as $n$ increases. [ABSTRACT FROM PUBLISHER]

The $K$ -user multiple-input and multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter is considered, where each receiver is assumed to be equipped with either conventional antennas or reconfigurable antennas in which each reconfigurable antenna is capable of choosing a subset of receiving modes from several preset modes. Under general antenna configurations, the sum linear degrees of freedom (DoFs) of the $K$ -user MIMO BC with reconfigurable antennas are completely characterized, which corresponds to the maximum sum DoF achievable by linear coding strategies. [ABSTRACT FROM PUBLISHER]

An uplink–downlink two-cell cellular network is studied in which the first base station (BS) with M1 antennas receives independent messages from its N1 serving users, while the second BS with M2 antennas transmits independent messages to its N2 serving users. That is, the first and second cells operate as uplink and downlink, respectively. Each user is assumed to have a single antenna. Under this uplink–downlink setting, the sum degrees of freedom (DoFs) is completely characterized as the minimum of (N1N2+\min (M1,N1)(N1-N2)^{+}+\min (M2,N2)(N2-N1)^{+})/\max (N1,N2) , M1+N2,M2+N1 , \max (M1,M2) , and \max (N1,N2) , where a^+ denotes $\max (0,a)$ . The result demonstrates that, for a broad class of network configurations, operating one of the two cells as uplink and the other cell as downlink can strictly improve the sum DoF compared with the conventional uplink or downlink operation, in which both cells operate as either uplink or downlink. The DoF gain from such uplink–downlink operation is further shown to be achievable for heterogeneous cellular networks having hotspots and with delayed channel state information. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the class of type-threshold functions, e.g., the maximum and the indicator functions. A simple network model capturing both the broadcast and superposition properties of wireless channels is considered: the collocated Gaussian network. A general multiround coding scheme exploiting superposition and interaction (through broadcast) is developed. Through careful scheduling of concurrent transmissions to reduce redundancy, it is shown that given any independent measurement distribution, all type-threshold functions can be computed reliably with a nonvanishing rate in the collocated Gaussian network, even if the number of sensors tends to infinity. [ABSTRACT FROM AUTHOR]

Function computation over Gaussian networks with orthogonal components is studied for arbitrarily correlated discrete memoryless sources. Two classes of functions are considered: 1) the arithmetic sum function and 2) the type function. The arithmetic sum function in this paper is defined as a set of multiple weighted arithmetic sums, which includes averaging of the sources and estimating each of the sources as special cases. The type or frequency histogram function counts the number of occurrences of each argument, which yields various fundamental statistics, such as mean, variance, maximum, minimum, median, and so on. The proposed computation coding first abstracts Gaussian networks into the corresponding modulo sum multiple-access channels via nested lattice codes and linear network coding and then computes the desired function using linear Slepian–Wolf source coding. For orthogonal Gaussian networks (with no broadcast and multiple-access components), the computation capacity is characterized for a class of networks. For Gaussian networks with multiple-access components (but no broadcast), an approximate computation capacity is characterized for a class of networks. [ABSTRACT FROM AUTHOR]

The capacity scaling laws of two overlaid networks are investigated, which are located in the same area sharing the same wireless resources with different priorities. The primary network can be regarded as an existing communication system operated in a licensed band and, therefore, is assumed to operate in an order-optimal fashion to achieve its standalone capacity scaling law. The secondary cognitive network must keep its interference to the primary network below a certain threshold while at the same time maximizing its own throughput scaling law based on cognition information. The existing scaling results for cognitive networks inherently assume multihop communication, which is a restricted coding model. By contrast, in this paper, a general coding model is considered without any specific physical layer coding assumptions. The capacity scaling exponents for both networks are analyzed when the numbers of primary nodes n , primary base stations l , which support the communication between primary nodes, and secondary nodes m increase with the relations , \beta >1 , and l=n^\gamma , 0\leq \gamma \leq 1 . For the extended network model, the capacity scaling exponents are completely characterized as \max \2-\alpha /2,1/2,\gamma \ and \max \2-\alpha /2,1/2\ for the primary and secondary networks respectively, where \alpha >2 denotes the path-loss exponent. That is, the capacity scaling laws for the primary and secondary networks are represented, respectively, by n^{\max \{2-\alpha /2,1/2,\gamma \}\pm \epsilon } and m^{\max \{2-\alpha /2,1/2\}\pm \epsilon }$ for \epsilon >0$ arbitrarily small. For the dense network model, when the primary network achieves its standalone capacity scaling exponent of 1, the secondary network is shown to achieve a scaling exponent of 1-{1}/({2\beta }) , which improves the previous scaling exponent of 1/2 achieved by multihop. For both models, it turns out that the conventional multihop approach is in general quite suboptimal. [ABSTRACT FROM AUTHOR]

The fading AWGN two-user two-hop network is considered where the channel coefficients are independent and identically distributed (i.i.d.) according to a continuous distribution and vary over time. For a broad class of channel distributions, the ergodic sum capacity is characterized to within a constant number of bits/second/hertz, independent of the signal-to-noise ratio. The achievability follows from the analysis of an interference neutralization scheme where the relays are partitioned into M pairs, and interference is neutralized separately by each pair of relays. When M=1, the proposed ergodic interference neutralization characterizes the ergodic sum capacity to within 4 bits/sec/Hz for i.i.d. uniform phase fading and approximately 4.7 bits/sec/Hz for i.i.d. Rayleigh fading. It is further shown that this gap can be tightened to 4\log\pi-4 bits/sec/Hz (approximately 2.6) for i.i.d. uniform phase fading and 4\-4\log (3\pi/8) bits/sec/Hz (approximately 3.1) for i.i.d. Rayleigh fading in the limit of large M. ref refid="fn1"/ id="fn1" asterisk="no"paraThroughout this paper, log(.) denotes the logarithm of base two.para [ABSTRACT FROM AUTHOR]

In this paper, we study a layered linear binary field network with time-varying channels, which is a simplified model reflecting broadcast, interference, and fading natures of wireless communications. We observe that fading can play an important role in mitigating interuser interference effectively for both single-hop and multihop networks. We propose new coding schemes with randomized ergodic channel pairing, which exploit such channel variations, and derive their achievable ergodic rates. By comparing them with the cut-set upper bound, the capacity region of single-hop networks and the sum capacity of multihop networks are characterized for some classes of channel distributions and network topologies. [ABSTRACT FROM AUTHOR]

We consider a wireless network in which a single-source node having m antennas transmits independent messages to n destination nodes, where each destination node has a single antenna. We assume that the source is located at the center of a unit area and the destinations are located uniformly at random in the same area. By applying transmit beamforming at the source, an achievable sum rate can scale as \min \m,n\, which is defined by the aggregate rate of all messages. For transmit beamforming, however, channel state information (CSI) is essentially required at the transmitter (CSIT), which is hard to acquire in practice because of the time-varying nature of wireless channels and feedback overhead. We show that, even without CSIT, almost the same sum rate scaling law assuming CSIT is achievable by inducing cooperation between destinations. Specifically, we study the sum rate scaling law when both the number m of the source antennas and the number n of destinations increase such that n=m^\beta for \beta >0. If \beta >1 the optimal sum rate scales as m\log m and if 0< \beta \leq 1 the optimal sum rate scales between m^\beta (1-\epsilon) and m^\beta\log m, where \epsilon >0 is an arbitrarily small constant, which shows significant improvement compared to the case of no cooperation between destinations. Our result is of particular interest because we did not assume any additional bandwidth for cooperation. [ABSTRACT FROM PUBLISHER]

This paper analyzes the impact and benefits of infrastructure support in improving the throughput scaling in networks of n randomly located wireless nodes. The infrastructure uses multiantenna base stations (BSs), in which the number of BSs and the number of antennas at each BS can scale at arbitrary rates relative to n. Under the model, capacity scaling laws are analyzed for both dense and extended networks. Two BS-based routing schemes are first introduced in this study: an infrastructure-supported single-hop (ISH) routing protocol with multiple-access uplink and broadcast downlink and an infrastructure-supported multihop (IMH) routing protocol. Then, their achievable throughput scalings are analyzed. These schemes are compared against two conventional schemes without BSs: the multihop (MH) transmission and hierarchical cooperation (HC) schemes. It is shown that a linear throughput scaling is achieved in dense networks, as in the case without help of BSs. In contrast, the proposed BS-based routing schemes can, under realistic network conditions, improve the throughput scaling significantly in extended networks. The gain comes from the following advantages of these BS-based protocols. First, more nodes can transmit simultaneously in the proposed scheme than in the MH scheme if the number of BSs and the number of antennas are large enough. Second, by improving the long-distance signal-to-noise ratio (SNR), the received signal power can be larger than that of the HC, enabling a better throughput scaling under extended networks. Furthermore, by deriving the corresponding information-theoretic cut-set upper bounds, it is shown under extended networks that a combination of four schemes IMH, ISH, MH, and HC is order-optimal in all operating regimes. [ABSTRACT FROM PUBLISHER]

Two distinct, but overlapping, networks that operate at the same time, space, and frequency is considered. The first network consists of n randomly distributed primary users, which form an ad hoc network. The second network again consists of m randomly distributed ad hoc secondary users or cognitive users. The primary users have priority access to the spectrum and do not need to change their communication protocol in the presence of the secondary users. The secondary users, however, need to adjust their protocol based on knowledge about the locations of the primary users to bring little loss to the primary network's throughput. By introducing preservation regions around primary receivers, a modified multihop routing protocol is proposed for the cognitive users. Assuming m=n^\beta with \beta>1, it is shown that the secondary network achieves almost the same throughput scaling law as a stand-alone network while the primary network throughput is subject to only a vanishingly small fractional loss. Specifically, the primary network achieves the sum throughput of order n^1/2 and, for any \delta>0, the secondary network achieves the sum throughput of order m^1/2-\delta with an arbitrarily small fraction of outage. Thus, almost all secondary source-destination pairs can communicate at a rate of order m^-1/2-\delta. [ABSTRACT FROM PUBLISHER]

We study a layered K-user M-hop Gaussian relay network consisting of Km nodes in the m^th layer, where M\geq 2 and K=K1=KM+1. We observe that the time-varying nature of wireless channels or fading can be exploited to mitigate the interuser interference. The proposed amplify-and-forward relaying scheme exploits such channel variations and works for a wide class of channel distributions including Rayleigh fading. We show a general achievable degrees of freedom (DoF) region for this class of Gaussian relay networks. Specifically, the set of all (d1,\ldots , dK) such that di\leq 1 for all i and \sum i=1^{K} di\leq K\Sigma is achievable, where di is the DoF of the i^th source-destination pair and K\Sigma is the maximum integer such that K\Sigma \leq \mathop min\limits m\{Km\} and M/K\Sigma is an integer. We show that surprisingly the achievable DoF region coincides with the cut-set outer bound if M/ \mathop min\limits m\{Km\} is an integer; thus, interference-free communication is possible in terms of DoF. We further characterize an achievable DoF region assuming multi-antenna nodes and general message set, which again coincides with the cut-set outer bound for a certain class of networks. [ABSTRACT FROM PUBLISHER]

We show that the 2\,\times \,2\,\times \,2 interference network, i.e., the multihop interference network formed by concatenation of two two-user interference channels achieves the min-cut outer bound value of 2 DoF, for almost all values of channel coefficients, for both time-varying or fixed-channel coefficients. The key to this result is a new idea, called aligned interference neutralization, that provides a way to align interference terms over each hop in a manner that allows them to be canceled over the air at the last hop. [ABSTRACT FROM PUBLISHER]